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Today is Wednesday, June 11th, 2025.
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We are live from the Palace of Party Rounds.
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Oh my god, it's YC Demo Day.
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Welcome to our YC Demo Day stream. That is insane.
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We have Gary Tan joining us.
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Wow, you absolutely destroyed my laptop. That is insane.
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We brought lots of party favors.
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We brought lots of activities for when we uh talk to founders who are doing extremely amazing things.
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If that's going off every time a founder hits a million dollars in ARR or signs term sheet, I think we are going to be up to our necks in confetti.
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We got a lot of confetti.
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We got some gifts we're going to be giving out.
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We got some surprise gifts, some hats.
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We're going to take you all through it.
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Gary Tan, welcome to the stream. There he is. What's going on?
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The president of Y Comier, Gary.
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Gary Tan, good to see you. Great to see you.
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Always great to see you all.
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Uh the uh there's a line around the block still. Is that right? People are pumped. Oh my god.
1:05
Yeah, it's it's absolutely slammed.
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Uh take us through what are you seeing? How's this one going?
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Uh what's actually changed cuz we're in a different location. Break it all down.
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In the middle of uh this is like our HQ, you know.
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This is uh you know, we uh we got the spring batch together.
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This is the first spring batch that we've ever done. So X25 now. Yeah. Yeah.
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Paul Graham doesn't like X.
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So we're slowly replacing it with spring. Spring. Okay, there we go.
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You know, when you create a place like this, I think you get to dictate little things like, you know, not liking X. So yeah.
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So we got to write out spring, but you know, I don't know.
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What do you think it should be? It could be P.
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Maybe if it's not X, it's pron mathematical notation for this stuff.
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Bring in some like different, you know, we have the Y combinator algorithm.
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We need a different algorithm to define the different seasons.
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I think just full word, you know, winter, spring, summer, fall. Have fun. Summer fall.
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The uh the energy from the founders is really electric. Honestly, it's insane. Seems fantastic.
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Like downstairs, uh we got a Well, the fun thing about hosting all of the investors in our house is that uh I got a whole house, our house champ downstairs.
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So, so we Yeah, we got Give us an overview of the We We heard a little bit of your talk earlier, but give us kind of a breakdown of of how you introduced today. Yeah, absolutely.
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I mean, dude, it's like 90% AI.
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It's about 10% uh 11% hard tech, which is awesome.
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And then the really crazy stat is, you know, how the last four batches about the last year, uh, you know, the batch itself as a whole has been growing revenue by 10%. Uh, this time it's 12. Wow. There we go.
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So, we're actually in up and, you know, that's what you would expect.
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We're in the middle of the age of intelligence.
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you know, uh, six months ago, nine months ago, you know, the models were 90 IQ, you know, then they were 110.
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Now they're about 130, you know, we're sort of entering super intelligence zone and IQ incoming for,000.
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I don't even want to talk to that, but yeah, probably very valuable.
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I thought um Sam's essay yesterday was very precient and that um like that's that's sort of the silver lining like everyone's sort of worried, you know, what's going to happen to the jobs.
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what's going to happen to the jobs. Like to me what's going to happen is the exact uh I mean it's actually an an opening right like uh the wild stat that we're seeing is actually the number of 18 to 22 year olds applying to YC and getting it is up 110% year on year right
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so you know is that driven by people liking to drop out of college or skipping college entirely is that because they're they're viewing college as kind of like I mean there was always a meme about like oh what you put YC in the education section of your LinkedIn now it's Oh, wait. No, YC could actually
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No, YC could actually be the replacement. Is that intentional?
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Well, the extreme meme here that is interesting to think about.
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Like, I don't believe this, but you know, the memes among uh you know, the 18 to 22 year olds in particular is uh this might be the last time you can start businesses. Oh, interesting.
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Because you know once super intelligence hits then uh you know the moes that you you know the businesses that will exist will sort of uh ensconce like the seven powers of the moes out there. Sure. Sure.
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There's maximally efficient. Yeah. Exactly.
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they just reach their terminal value immediately and maintain it forever.
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So you're trying to get network effects, you're trying to build uh we're trying to we're trying to get brand, you're trying to get a cornered resource.
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Uh and then the wildest thing here is that you know this uh perfect uh someone was telling me yesterday uh right now if you look at college grads uh the rate of unemployment for CS grads is actually 2x that of art history majors.
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I have not looked this up yet.
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So everybody everybody's been quoting that. We've heard that too. We talked about it.
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might there might just be something crazy going on with art history majors who found some they found some hack and they're all getting employed.
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It's full employment for them. Uh very interesting.
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Um question on the AI side.
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How are the companies feeling about the current battle between little tech and big tech?
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We saw with WWDC it feels like Apple's kind of retreating from some territory.
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We could be seeing more opportunities for developers for like mobile apps.
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We could see another mobile app boom because Apple's saying, "Hey, look, maybe we're not the company to build every single AI experience on the iPhone."
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We're seeing new hardware maybe come from OpenAI.
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There's different stuff going on with open source.
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How what's the interplay between the average YC company and and the Mag 7 right now?
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Oh, I mean the good thing is we still have you know we have net neutrality.
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So, and you know that thing we've you know we have seven companies in the you know mega tech world but you know what like anyone can just put something on the internet and they get distribution right so uh I think that you know the most important thing right now that I think all of us should really be
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considering is we need platform neutrality right you know the second that you know today you open your Siri and you don't get to choose you know do I want perplexity do I want anthrop do I want you know chat GPT on there you know no like that this is the next sort of unfolding that needs to happen. We
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We actually need the platforms to allow other people to enter.
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But if we do that, we can actually have tens of thousands or hundreds of thousands of companies each of which can get to a billion dollars net revenue, you know?
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Uh and like you could do it probably with 10 people, right?
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So if you link up these two super mega trends, like that's the future that we want to live in, right?
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Like you can be 18 to 22, you know, you don't necessarily have to go and like the credential matters a lot less.
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You know what matters now?
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It matters, you know, your agency and your taste. Yes. Right.
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And so, and you don't have to like go and get anyone's nature of LLM, you could actually get bet a better tutor from an LLM than you could from at times working under somebody at some big company who would maybe explain here's how you make a financial model for a software company, but now you could just talk enough with Chad GBT that you could probably figure it out even better than having like a mentor in some cases.
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I want to ask about applying to YC.
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Have you noticed that the apps are becoming more GPT driven?
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Are people using AI to write their apps?
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Do you recommend against that? What do you think?
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I mean, if anything, like I think the best apps, you know, in the past, we might say, "Oh, this is AI slop."
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I think we're because the models are now smart enough like my writing process for instance has totally changed to this point.
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Like I am, you know, you're actually able to come up with better ideas.
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I think like, you know, I I would rather um I would rather people actually prompt to get like all of the ideas out there.
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You know, one of the things I've been using in chat GPT lately is like give me 10 options for different concepts or ideas that might fit here.
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And then what I'm doing is I'm using my tech like I'm using my prompting to do that and then on the back end it'll give me like 10 things.
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Five of them make no sense.
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Two or three of them in my brain I'm like, "Oh, I didn't think about that.
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that actually is a useful thing that I can put in with these other concepts that are in my head. Yeah.
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concepts that are in my head. Yeah. And so I think it's actually uh you know the computer is a bicycle for the mind like if you can prompt really really well um you know using just I mean you have to treat it like a vehicle right it is not
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a destination of its own it's actually you know it's this is like the self-driving car for the mind right I mean even just treat it like a coworker all that matters is the end output and if you're working on any type of project not working with a smart collaborator is going to lead to a worse output. Yeah. Yeah. Yeah.
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Condensing down these ideas because I' I've read a lot of apps where it's like, wow, there's actually like some really incredible KPIs in here, but you buried it in paragraphs of exposition that were completely unnecessary.
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And I know that the people that are actually reviewing the YC apps are not going to read this far.
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And so just having it as a co-pilot seems like a really really how have you and the other group partners push to guide uh the batch around re reporting on revenue, right?
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There's a lot of conversation around what is ARR?
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It's sort of this flexible definition.
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Yeah, there's obviously a lot of pressure for every founder coming into demo day to like show results.
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How how do you guys kind of uh guide uh founders? Absolutely.
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Absolutely. What we'd like people to do is put a contracted ARR if it is and then if it has an opt out clause where you know people can sort of get out they should just have a little star on it and it's like you know opt out at 30 days or whatever this I think it is very very
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important that founders um are just don't engage in securities fraud is like kind of a basic thing right so you know I think that it is a you amazing thing about uh the tech today is like the demos are so impressive that people are willing to take a big chance
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to sign up for big deals and yeah they obviously want some flexibility but but being really clear about that I mean these are non-GAAP metrics you know there is some gray area but we need to define new metrics as we move forward are you seeing companies able to pivot more times within a single batch and
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just iterate faster because historically it wasn't unreasonable for a company to pivot a few times to get to something great and maybe they only have two weeks at the end to really sprint and show progress now I could imagine certain companies like really really really pushing it. Have you seen that at all? Yeah, abs. I
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Have you seen that at all? Yeah, abs.
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I mean something like 30% of the companies change their idea during the batch and that's actually great.
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I mean you start as you're researching and building. Yeah. Yeah.
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And I I think that that's always been true.
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I mean some of the biggest companies end up being you know literally pivots from like 2 3 weeks ago and then I think that you know people might say oh that you know that kind of sucks or you know why is that?
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I mean I think it's good.
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The good news is like you know uh you can just do things.
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The good news is like so so when I think of the YC mantras I think build something people want uh talk to your customers is you can just do things.
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A third that we're adding is that important to have that valition that that uh uh that a agency.
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It's the distillation of agency right I think so. Yeah.
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Yeah. I mean a lot of it actually I think the most important thing that uh I feel like everyone has to learn the hard way is uh to learn you know the sound of your own voice to say uh you know not to get all bicameal mind about it but you know like that's sort of where we're at do well no I mean if you uh read you know PG's old essays like one of the things that really jumps it out at me is
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like to what degree you know your childhood your schooling like he has so many essays about you know what high school is like being a nerd like all these things like you know really spoke to me and that um the process of becoming actually a founder is actually a journey inward to actually learn the sound of your own voice that like you can make your own way you can have
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agency you know just because I mean actually by definition the startups that create new categories require a level of courage that like people have to find within themselves actually you have to say actually you know what like I know the Wall Street Journal says that and you know the hater del journalists say this and all this you know you have to actually separate yourself from the
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default view of how the world works and then you're actually trying to divine secret knowledge by going into the markets going to talk to people that have never you know even touched chat GPT yet right like they don't know the re it's like that meme where you're you know you're the tech guy like in the corner and then like everyone's dancing and they just don't know they don't Like that's where we're at still. Like it
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Like it won't be like that for another year or two, but like for now that's still true.
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You go into any business in the world, they don't know this revolution is about to happen to them and we get to create it. Yeah. Yeah. Yeah.
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Like last demo day, we talked to a company that was doing uh AI voice interactions to help the elderly process Medicare receipts essentially and they discovered that the the elderly were talking to their chat bots for like three hours. Yeah.
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And that's just something that like you might you might be able to predict intuitively, but I thought it was just a very a very funny like discovery that only happens from actually trying to build in that in that market with the latest and greatest technology and that's what I love about YC Demo Day.
12:57
What's your latest thinking on batch sizes?
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Is that is that are we are we staying you know where where we're at?
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Uh the high level is like we want as much prosperity in the world as possible.
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You know Brian Chesy is on my board.
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Um you know Paul Graham and Jessica Livingston, Carolyn Levy.
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uh the board has given me my directives.
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It's uh you know what we need to this is the tree of prosperity.
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Let's have the tree of prosperity grow.
13:21
But you know I think that YC fundamentally is the managed marketplace.
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You look at an Airbnb I still super I'm still you know bullish on Airbnb and that you look at the amount of space in the world.
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Like the amount of space that has been listed on Airbnb is still a tiny fraction of what it could be.
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And what does that unlock?
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and it unlocks new experiences, travel like a human, like all these things, you know, it's hundred billion dollar company from nothing.
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And uh I think that the same thing is about to happen to innovation and venture.
13:48
Um but we have to do it thoughtfully, right?
13:50
Like you know, we're at demo day here.
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We have uh more than a thousand of the top investors in the world all congregated here, right?
13:58
We have a thousand people in this building. That's amazing.
14:00
And um you know, we need to grow them thoughtfully.
14:04
Like we need, you know, what I need is I need YC to continue to provide returns, right?
14:08
And you know, uh can't comment on, you know, the rumors about scale this week, but like we need a lot more things like that and we're getting it.
14:17
Like this is sort of uniquely the community where that happens.
14:20
Talk to us about the two new partners that were added to the YC partnership.
14:23
Oh yeah, there's three actually. Yeah, sorry. Two. Yeah.
14:24
Uh Andrew Nicholas and John Shu actually. Okay, cool.
14:27
Sorry about I almost announced. No. Yeah, Tyler 2. Okay. Yeah. Yeah, that's Tyler 2.
14:31
Um I mean all of them created uh companies that exited for you know hundreds of millions to you know pedager duty as you know a public company uh you know north of a billion is that's remarkable that those are exactly the kind of partners that we want at YC.
14:46
It's like they've been there and they've done that.
14:48
So roughly how big is the partnership now? It's 15 partners total. 15 partners. That's great. Yeah.
14:53
So you can still keep the actual uh like group sizes fairly small within the batch.
14:58
I mean that's the main you can just basically guess at what the batch size will be because each partner can do 10 to 25 companies depending on uh how hard they want to work.
15:10
But uh you know I I don't think it's a numbers game.
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I think it's you know we want to fund all the really really good founders and I feel a little bit embarrassed about you know we're accepting companies at a 0. 8% rate right now. Wow.
15:23
So, you know, I think that we're behind the eightball actually.
15:29
Like, you know, I I feel really good about this.
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Like, we're going to keep growing what we got here.
15:32
Um, but I also need to grow the partnership and then we need to fund better and better companies.
15:38
And then, you know, this is a 10, 20, 50, 100year thing.
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Like, we're trying to build Y Combinator into a multiundred-year institution. And we we need it.
15:48
Have you had any companies go through this batch and decide not to raise additional capital at this point because they're just making so much revenue that they they have no need for famously uh Tom funded Axiom last uh last batch. Yeah. Yeah.
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And they're doing hundreds of Yeah.
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Hundreds of millions of dollars in pure profit.
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So I saw that and I was like trying to look back through our stream and like did we did we I mean crypto's wild, man. Yeah. It's a wild west. It's a wild west. That is insane.
16:12
Well, we'll let you get back to it.
16:14
Thank you so much for coming on the stream. as always. Have fun out there. Thanks. Great.
16:19
Well, we will be moving into interviews with founders and VCs who are coming on the the show who are here at YC Demo Day. Stay mo.
16:30
Uh while we bring in the first uh Oh, we're ready. Let's do it. Fantastic.
16:37
I thought we were going to have new news. What up? What up? Welcome to the show. I'm John. Welcome. Nice to meet you. Nice to meet you. How you doing? What's going on? Break it down for us. Break it down for us.
16:51
How's How's demo day going? Grab a water. Uh introduce yourselves.
16:55
Introduce your company, please. All right.
16:57
Ken, hold up the microphone a little bit. Both of you guys. Good. Ken, cool. CEO of Kaizen. Nice. Michael, CTO. Okay.
17:06
You guys pitched like 5 minutes ago or 10 minutes ago? Five minutes ago.
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We came right down here to spread the word. Yeah.
17:11
How were the How were the nerves?
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Did you guys was that like a walk in the park? Yeah, it was fun. It was fun.
17:17
It was You've done it at alumni and then and then probably like three to five full partnership pitches before, right? Yes.
17:23
Um so I mean I've probably Yeah.
17:26
said this a h 100 times, a thousand times almost a Well, you got to say it one more time. Give us the high level.
17:31
You don't have to give us the whole pitch, but break it down. All right.
17:33
So Kaizen helps developers instantly integrate into websites without APIs.
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You know, we work with companies across logistics, healthcare, and financial services to integrate to a wide variety of legacy portals. Very cool.
17:42
Talk to me about how you're doing that. Is there MCP involved?
17:44
Are you kind of using AI and LLMs to read the HTML kind of reverse engineer an API from the front end? What's going on? 100%.
17:51
The latter of what you said, uh, computer use has changed the game.
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A lot of this stuff, you know, you think about it.
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Hey, there's a so such a small subset of software that has APIs that people can integrate with, build products on top of, but now with computer use, computers can do anything, anything available on the internet.
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And that's what we help companies do.
18:07
Wait, reactions to 03 Pro? Have you tested it yet?
18:10
Is it uh is it improving things or do you build on open source? Like what do you like?
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What are you excited about in the in the AI race at the foundation model level?
18:18
Yeah, I mean we love using all of them. We're friends.
18:19
We're we we're Switzerland, right? Google Google.
18:25
We have them all on the show.
18:28
Please let the fox in the hen house. We're Switzerland. We're Switzerland. Yeah.
18:32
No, I mean truly like different models are different for different things like you know clicking on an item on the page like we like the computer use model from Enthropic for that right pulling data from a very large table Gemini they come and clutch a little bit the biggest bigger context window exactly 100%.
18:46
So I mean that like our approach we abstract all this away from the end users they don't want to think about it they just it just happens.
18:52
So, walk me through some of those use cases.
18:55
Like, what's the first customer that you've had that has been like, "This solved my problem. This is amazing."
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Walk me through like a very concrete demo.
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One of our most f one of our favorite customers to talk about is, you know, they're a voice station for hotels. Okay.
19:06
So, in the Rio, the hotel in Vegas, you know, you call down, you say, "Hey, I want a a burger up to my room or I don't know what kind of fancy stuff you all order, but yeah, you'll talk to a voice agent.
19:16
Uh, the voice agent will take your request, right?
19:18
And then they'll use like calling to to get like tooth.
19:23
Last night we were staying at the Rosewood, of course.
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And uh we call to get toothpaste and we're like it's like it's you know you got to I don't even want to wait like you know I don't know 20 seconds while it rings and oh let me transfer you here and all that stuff.
19:39
You should just be able to pick up toothpaste please.
19:40
And it just and it just comes. Exact.
19:42
So how how does your service integrate with that experience?
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Cuz I know I pick up the phone.
19:46
I'm talking to a voice agent.
19:46
I imagine you're using voice APIs to actually mediate that, but then you're designing that interaction, right?
19:51
Or rather, our customer is traversing.
19:55
Maybe I want to shout them out.
19:55
They are a voice agent for hotels.
19:57
Uh and then they use us to write the data back into the property management system, create that service order.
20:05
So they a toothpaste goes right up to your room.
20:06
So instead of talking to a person and they're trying to understand you, all this stuff, it just happens instantly.
20:11
What were you guys doing before this?
20:12
We were I was head of engineering at a company called Truck Smarter.
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I've worked with small trucking companies my whole career. Love them. Great job. Big truck guy. Big truck guy.
20:20
Has lots of experience working with legacy systems, web forms. Exactly.
20:24
That's that's where it comes from.
20:25
Like every shipper in the United States is a completely different website.
20:28
I must have written dozens of these. I managed teams.
20:29
I wrote hundreds uh and probably a lot of web scraping.
20:34
But you know, now you're on and we're building Kaizen so that no one has to do that again. I love it.
20:37
Talk to us about the metrics.
20:40
Did you share a headline number of users arr something to get the investors excited today?
20:44
Yeah, I mean we're in the hundreds of thousands of dollars of AR started working on this. Yeah, let's blow.
20:51
We got the We got all the acronyms, all this the you know what the A16Z you guys you guys got term sheets yet? We're we're close.
21:04
We have the first term sheet of the TV show.
21:11
Congratulations I love this.
21:15
Spreading so much debris across this room. It's terrible.
21:18
Anyway, thanks for playing along with us, guys. This is awesome.
21:21
We're super excited for you. That's awesome.
21:23
Um, what's next on the buildout? How big is the team?
21:25
I imagine you're raising money.
21:26
You're going to scale that or are you building like a much smaller team?
21:29
How are you thinking about that?
21:30
Yeah, I mean, this is a massive opportunity and we're excited to sprint after it.
21:32
We actually have an employee right now. Yeah.
21:34
Crazy enough to to join us during the bash with the 500k in the bank account and we're we're we're doing a work trial tomorrow.
21:43
So, we know we have the money.
21:45
We got to go spend it and and then we're going to build a big business. Fantastic.
21:48
Well, we're rooting for you. Amazing, guys. Congratulations. Good luck. Thank you. Good luck, my man. Good stuff. Yeah, we'll see you. Fantastic. All right.
21:58
These party poppers are a big problem.
21:59
They like it basically was spraying like, you know, little shards of of of paper everywhere. But, uh, we're doing it. We're not going to stop.
22:07
I think it as long as it didn't go in my Red Bull, I think we're good.
22:10
Um, let's uh let's ideally bring in the next person. You want to come on?
22:13
Let's let's let's come on.
22:15
Okay, we got some people coming into the stream.
22:16
The YC Demo Day stream 2025. Welcome to the stream. Come on. Come on and sit down.
22:23
You're going to have to rush off all the confetti. What's up?
22:25
We got a little excitement. What's up? What's up? Hey, how you doing, man? What's going on? All right. Hey, congrats. What's happening?
22:32
So, so we've emailed or or chatted before, right? Yes. Yes.
22:34
Back in the Stack Share days.
22:36
People don't know your history, by the way.
22:38
I I I was talking to a bunch of founders. They were like, "What?" He did what?
22:41
Crazy around uh around Silicon Valley for uh over a decade.
22:48
YC 2012, my batch good times.
22:52
But this we're here to talk about your batch. What are you building? Introduce yourselves. All right.
22:55
So, we are building cursor for DevOps. Okay.
23:00
Basically, the challenge right now is you're using cursor and it's like this futuristic agentic experience, right?
23:06
And then as soon as you leave the code editor the microphone up a little bit you're back in the past and so you're dealing with broken CI builds you're dealing with exceptions you're dealing with outages like service outages from pager duty.
23:17
All of those things are manual.
23:19
So what we're doing is we're bringing AI agents to all of your developer tools outside of the code editor. Okay.
23:24
Walk me through how how that actually works because in cursor I'm in the IDE.
23:29
Am I am I are you puppeteering the AWS dev, you know, like interface or are you operating at a lower level?
23:38
Um what's the actual interfaces?
23:40
Is this are you run pill?
23:40
Is this like a text is the universal interface play? Yeah.
23:44
So basically you land on a developer homepage and you see all of your tasks from across those tools.
23:50
So like exceptions from Sentry and then you see an autofix button for each of those tasks.
23:54
So it's like a priority inbox, right?
23:57
that prioritizes everything across those developer tools and then gives you oneclick actions.
24:01
How much of what you're doing requires just uh building on top of an API for something like pedag duty or actually doing a deal with them to integrate at a deeper level or just uh puppeteering and computer use and not even know they they they're never known the wiser. Yeah.
24:17
So so we're actually doing both, right?
24:19
Um, so some of the dev tools haven't built out a lot of agentic features.
24:23
So we're building on top of their API and then other partners like one of our first integrations is with Sentry.
24:28
Um, and we integrate with Century. Yeah. Okay. I remember Century. Yeah. Cop is actually here. Oh, cool.
24:34
Uh, so did you guys come in with this idea?
24:37
Did you have to iterate to it?
24:38
How what did that look like? Yeah. Yeah, we did. We came in with it.
24:43
So, so before this uh uh Daniel here um at Netflix uh I I was on the team that built the internal developer portal which was the most used engineering tool at Netflix.
24:52
Um that helped accelerate the company.
24:55
You probably heard like you know they shipped like ads and live streaming and all these things and it really helped the organization move faster.
25:00
Everyone thought that they were going to have to partner with Microsoft and I think they wound up doing it internally because they move so fast. Right. Yeah.
25:04
That's a great narrative about Netflix. Exactly. Right.
25:08
So it really helped accelerate the team and that had no AI. Yeah. No AI in it. Right?
25:12
And you can squeeze all that productivity.
25:14
So then Yonas and I were chatting.
25:16
We're like, "Wait, what if we did this developer first? We did it with AI.
25:19
How productive could you make engineers?
25:21
You just go from cursor to stars sling and you're just talking to agents. Slanging slang.
25:29
How uh what is the go to market motion?
25:31
Cursor obviously just goes bottoms up directly to the dev.
25:33
Is this something that like a DevOps engineer can bring in or do you need to go through a CTO get approval before you do an enterprise deal?
25:41
any developer can actually just sign up, connect your account and start using it.
25:45
The beautiful part is this isn't for DevOps engineers.
25:47
This is actually for all the engineers that have to touch those tools.
25:50
And so it's like pretty much every engineer at the modern software engineering or can just sign up on their own without talking to anyone else and start using the product. Uh how's the progress? Are are you live? Are you growing?
26:02
What metrics did you share with the demo day crew today? Yes.
26:06
So less than a month ago we launched and we have over 400 companies that have signed up for the private beta including Congratulations Snowflake.
26:14
Congratulations [Music] Golden up for big agents. Everyone wants agents. Yeah. Yeah. Uh that's crazy.
26:24
Where are you guys going from here?
26:24
Did you you close the round already? Yes, we have closed. Oh, there we go. There we go. Yes. Yes.
26:32
We were happy to give you these ramps. Awesome. Thanks for living. Put the money in ramp. Yes. Exactly. Exactly. Awesome. That's incredible.
26:41
What's What's next for the company?
26:41
You guys hiring, scaling?
26:43
We're hiring very slowly.
26:45
How big is the company right now? It's just the two of us. Just the two of you. Old school YC. This is the way it was.
26:52
Now there's folks coming through with 25 employees. Yeah.
26:53
No, no, we incorporated right after getting into YC. No way. Awesome.
26:58
We were like, "All right, the team that's great. Build the MVP."
27:01
What were you doing before, by the way?
27:03
So I started a company called stack share is a developer community.
27:05
Um we scaled it to over a million developers.
27:10
By the end of the journey it was used by over 40 million developers and we I think we did like a interview or something.
27:15
It was an interview of the Soilent tech stack.
27:16
Yeah that's how the hell are you shipping all these calories and so we talked about all the tools.
27:20
So yeah it was a big developer community and then sold the company last year. Awesome. Congrats. That's amazing.
27:26
You guys are in an incredible position.
27:30
Feeling feeling really good about this.
27:32
Yeah, you you should be confident.
27:32
It's going to be hard, but I think the the confidence should be high.
27:35
I mean, it's it's amazing how much we can get done now just with like two, right?
27:39
It's a it's it's it's never been done before. So, yeah, we're excited.
27:44
It also feels like an interesting market in that uh we've seen like it's just less monopolistic.
27:50
It's not like trying to break through a social network where it's like you're either a trillion dollar company or zero.
27:54
Like I feel like in DevOps, in enterprise, like you can understand the road map ahead, chop wood, create a great product, and carve out like a fantastic business.
28:03
That's why we see so many companies going public every year.
28:07
So many decacorns in this category. So congratulations.
28:09
I'm really keep in this batch.
28:11
Yeah, we're huge TV fans.
28:14
Come on the next should be watching if you're a founder. There we go. Love you.
28:19
Have a great rest of every day. Good luck. Thank you guys soon. All right.
28:24
And we will bring in the next crew. Stoked for you guys. Oh yeah. Bring the phone out. Run out of those.
28:32
How many more do we have?
28:33
We We have a variety of goodies.
28:38
Oh, I love the sweatshirts. You're owning a color. There we go. Ramp yellow.
28:42
You guys are wearing pink.
28:42
Uh you can have you can have those if you want. Feel free.
28:46
They're limited edition to this demo day.
28:50
You can only get them this year. There we go. There we go.
28:52
The colors are working together perfectly.
28:56
Roughly the same saturation.
28:56
Roughly the same on the orange background. On the orange paint. Yeah.
29:00
This is This is Jaspberry.
29:04
It feels kind of vintage.
29:04
It feels like I've known it. I've known it.
29:07
What do you guys bring it down?
29:07
Oh, we're building an AI agent for bug finding. Okay.
29:10
So, right now we have a PR bot.
29:12
Um, so you make a pull request.
29:15
We'll take your code, uh, clone it into a sandbox, and then we let an agent just go ham at it. Okay.
29:19
Um, and then we tell you how we break it. Okay.
29:21
Uh h how much of this is just about speeding up the pace of development versus like uh is there a pen testing angle here?
29:28
Is that just a completely separate cyber security play?
29:31
No, I think we do some pin testing.
29:33
So it's we want to basically find any kind of bug. Yeah.
29:35
Um so a lot of people take like a a limited a limited approach at bug finding.
29:42
So they ether do like coverage testing or they try and find integration bugs.
29:46
Y we really want to basically build an agent that can do any of that or kind of what's best for your tool.
29:52
So you like when people are vibe coding cuz they're just creating vibes all the time. Keep vibe coding. Yeah. No, we love vibe coders.
30:01
We we're here to help you make better code.
30:04
No problems with it whatsoever.
30:06
As long as you buy our software. Yeah. Yeah.
30:07
You vibe code, we'll test it.
30:09
Then you take our output, you put it back into cursor. Just feed it back in.
30:13
Talk to me about the the prompts that you're using to actually have the agent go and hammer it.
30:17
Like I imagine that that's not just try and find a bug.
30:22
You've probably gotten very like designing flows.
30:25
There's probably a lot of work that goes into that.
30:27
What goes into actually getting an agent to effectively uh hunt for bugs. Yeah.
30:31
So like the most important part is just to have like a sandbox where it can like it can run code, can compile your code, it can it can run like unit tests. Yep.
30:40
Um, and so then we just get the agent to, yeah, go ham.
30:44
And, uh, each time that it like runs a small experiment on your code, it learns a little bit more.
30:48
And it's able to do run a better test the next time.
30:52
And so, it's able to search a repository, able to run commands to, you know, see if you've, you know, changes you made actually were propagated through all the files.
30:58
So, in we found a bug, which was that someone updated a path but didn't update it everywhere.
31:03
And so, that was those these sorts of things.
31:04
So, the agent's able to run these like every any command that a person would. Yeah.
31:07
Are you doing stuff like like trying to stuff multiple variables in a single function like that type of stuff where like there isn't as much fall tolerance built into the code?
31:16
Maybe they need like a you know if else try except clause in there or something like that.
31:21
Is that the type of like bugs that you're trying to find or is it more about like scalability of code like okay you're making a database call right here it looks fine now but if we scale this up and there's and there's a lot of demand you're going to get cooked.
31:32
I think it really depends.
31:35
So we use the pull request as kind of the initial seed.
31:38
So what change you make there kind of determines the path that we use for testing.
31:43
So if you're trying to scale then yeah we'll we'll kind of test as if you're trying to scale.
31:47
Um but if you're making path changes we'll test as if you're making path changes.
31:51
One of the things we find is like vibe coding often it there's a different flavor of bugs that are that are happening because of vibe coding. Okay.
31:59
So they don't LMS don't make the same kind of errors that people do because people it with people code grows organically.
32:05
LM is like oneshotting things.
32:07
So it'll often like forget to add functions.
32:10
Um so it's not as easy as pointing to a line and going like this variable is wrong.
32:14
It's like no no you you like fundamentally missed like this whole section of things you were supposed to implement. Got it.
32:20
Um so yeah I think it's okay.
32:22
Talk to me about the go to market motion.
32:24
Uh is this just a landing page?
32:26
You're driving traffic to it.
32:27
People sign up by themselves.
32:28
Are you doing founderled sales? All the above? No. No.
32:30
We're we're landing page like this is our go to market right now. Go to jaspberry. com jaspberry. ai. Go sign up. Go sign up. Yeah.
32:39
You can just go you install the bot.
32:41
We have a 7-day free trial. Okay.
32:43
Uh so it's consumption versus seatbased pricing. What are you thinking?
32:45
Yeah, it's seatbased pricing. Okay.
32:47
So for every developer, it's 20 bucks a month. Okay.
32:51
Um just simple kind of flat rate.
32:53
Are you running into cost problems?
32:56
because we've seen this like you know the latest and greatest LLM comes out it's really expensive GPT03 just dropped by 80%.
33:02
So anyone who was having a problem with their with their cost is probably fine right now.
33:06
Uh but but how are you thinking about that side? You go.
33:11
Yeah, we found that like actually for just like you know running lots of experiments on your code to find bugs that it's actually better just to have a really fast and small model. Okay.
33:19
And so we've actually yeah we haven't had these sorts of problems yet.
33:22
So what does that mean like llama fine-tuned?
33:24
Are you we we've talked to LLM training companies that have trained even smaller models like just for JSON to you know formulation or just translation models or just profanity finding.
33:36
Um are are you thinking about uh going so small you could run it on a gaming GPU or are we still talking about like the big boys? Yeah.
33:42
So like right now it's it's we've actually gotten like a lot of mileage out of Gemini Flash.
33:48
started by um you know we're we fine-tuned with RL a model that was specifically good at using tools and um and so yeah we're like we're getting ready to do that once we like find all our pain points exactly in our current architecture we can train the exact right thing and these smaller faster
34:03
models that are targeted for the specific use case are better so what were you guys doing before YC we were both researchers so I was doing research in software testing using large language models cool and Matteo was doing his PhD in reinforcement learning in formal methods Very nice. Very nice. So, our Very nice.
34:17
So, our our kind of research has come together to make this happen. How are the metrics?
34:23
How's the raise coming together?
34:25
How's the pitch for demo day? What are the goals? Excited about demo day.
34:28
Goals are raise a lot of money here. Let's go. Good luck. We're going big.
34:33
Bring some big napkins around.
34:35
Recommend Sharpie napkin. Just do it here. Perfect.
34:37
Um and then yeah, it's we're slowly kind of growing.
34:40
Well, I wouldn't say slowly.
34:42
We've doubled our growth kind of every every week for the past kind of couple weeks.
34:46
So, that's a better way to frame it. There we go.
34:50
But, yeah, we've gotten I think we're up to like 18 um different kind of companies using our tool. That's great.
34:55
So, yeah, it's been awesome. Cool. Well, good luck to you. 1,800 soon.
34:57
Yeah, 18 after this when all of you go subscribe. Yeah. Then we'll be at 1800. Fantastic. Thanks, boys. Congratulations. It's been a pleasure. Yeah. Cheers. We'll talk to you soon. Show the Crocs off, too.
35:11
Oh, he's got the full completely done everything.
35:14
Let's bring in the next team. How you guys doing? Welcome to the stream.
35:18
We got They've got the shirts on. The shirts are tucked. Do you need one? I need one. Thank you. Take it. Eddie, good to meet you. Nice to meet you. Nice to meet you. Nice to meet you. Nice to meet you guys.
35:28
Look, thank you for tucking your shirts in. We're keeping it.
35:31
We're keeping it respectful. Okay. Introduce the company. What are we building? Uh, so we're Code Tool.
35:34
Uh, we are building AI agents for security teams. Cool. Sorry.
35:37
Uh, we're building AI agents for security teams.
35:39
is specifically cyber security teams. Are we talking DDoS?
35:42
Are we talking somebody goes in and tries to steal secrets, steal data?
35:46
What are we talking about?
35:47
So like you know you can think of cyber security is split into like appsac and opsseac where apps like you know defending you know the your deployed software out into the world and then opsec is like operational security right where it's like uh you know protecting your your employees from fishing.
35:58
We're definitely more on the automation side for the opsseack side of house.
36:01
So, think of like basically like allowing security teams to like triage their tickets a lot faster for like impossible travel problems or for like Oh, impossible travel problems.
36:10
That's like a that's like a buzz word for Yeah.
36:12
It's like, you know, uh Eddie signed in from Singapore. Is that legit or not?
36:16
And typically, well, he was in the office earlier today.
36:19
He couldn't have possibly gotten there cuz hypersonic travel doesn't exist. Exactly. Not quite yet.
36:24
But that's going to make it really complicated for when you get from LA to Tokyo in 2 hours.
36:31
Well, I guess we did log in Tokyo. No, but going for sushi.
36:34
It's funny because I think like a lot of people have like this like hacker aesthetic in their mind when they think of cyber security, which is like a lot of like, you know, in the movies around on a terminal or something like that.
36:43
And it's just like when in reality it's like most of the time it's like people triaging tickets day in and day out and that kind of thing.
36:49
So like our goal is basically to like automate a lot of the BS that these teams have to go through and like a lot of like the annoying stuff and then like allow them to get back to work kind of thing.
36:56
Uh so what's the go to market motion?
36:58
Uh, are you doing enterprise deals, founder le sales, selling to other YC companies?
37:02
What's the scale of company that needs to use?
37:04
Our first customer is Ramp. Let's go, baby. Wow, that's hilarious.
37:07
I mean, where do you I mean, that's tough.
37:11
You're kind of starting to keep time is money. Save both. Come on. There you go.
37:17
Um, I mean, Eric is just an incredible CEO. I see a lot of them.
37:23
But we really want to cutting edge like the best teams like ramp that can actually help them operate.
37:31
Uh and so we're looking for like sort of tech forward enterprise is totally is like would be awesome but uh you know anyone that's like you know pushing the boundaries on what's you know possible automation. Okay.
37:41
And what does the integration point look like?
37:43
Is it is it a single uh you know security person at a company can get set up or is it something that needs to be deployed throughout the enterprise and has a much more like like staged roll out?
37:54
Yeah, it's it's I think basically where it is is like ideally what we would have is like we'd probably first like start working with like your detection and response team and like get that team plugged in.
38:03
Basically like we're you know it's we're heavy heavily leveraging AI tool calling.
38:07
So the idea is is like we plug into all the different points in your Slack.
38:10
think like Octa, think like Panther, think like all of these different products kind of thing.
38:14
And like basically then what we're able to do is deploy out like allow these teams to write their own agents.
38:19
So they're in there customizing their own system prompts and all this kind of stuff to go out and like tackle their task dayto-day.
38:23
their task dayto-day. So I think the initial go to market motion is work with these high-tech teams who are really used to automating already and then basically kind of like build up a nice collection of agents kind of start getting a good network effect IKEA effect where like people are like
38:35
building their own agents sharing them out into the world and then from there we can kind of like move out to wider and wider and like less technical teams where it's basically like we can kind of like start to plug into people's stacks and like wholesale automate out of the gate and like solve a lot of these problems. How did how did you two meet?
38:47
How did how did you two meet?
38:49
Uh so we grew up together in Santa Barbara, California.
38:50
Uh we uh we have you know lived together for since you know we went to school.
38:55
Uh but yeah our third co-founder is just outside.
38:58
He's he's uh he's probably watching this right now.
39:01
But um but yeah we we we were really stoked when you guys watched our our launch video on on for the on the video.
39:09
You guys are that company the single best the single best ad I've seen this year.
39:15
100% because because there are so many ways to do that and have it be just bad.
39:18
Oh yeah, it could have been that a million ways. But it was extreme. It was tasteful. It was funny. It was perfectly timed.
39:26
Yeah, it it it just made it funny.
39:28
Where where did that where did that come from? Uh well, so it's funny.
39:32
We we were scared it was going to flop to be honest.
39:33
I mean like we we we didn't know how it land and we're we're happy with how it did.
39:36
But uh no, I we we came with the idea.
39:37
We worked with like one of my friends growing up does comedy in in LA and I live in LA but like um she knew a director who like was like amazing and and his friends who were also like actors and stuff got in and and and acted for us and so it's like it all came together with friends of friends and it looked incredibly polished.
39:53
Can you give us an order of magnitude on the budget for that thing?
39:57
Uh it was it was it was uh let's see five digits but extremely low extreme extreme digits.
40:03
We were able it it looked like a it looked like a $100,000 project, but it was actually it was it was actually pretty funny.
40:09
We uh we showed the the original idea came from Gary actually.
40:13
We showed him the demo on the first week of uh and he's just like we started like showing him how you can like query Slack and that kind of stuff.
40:19
He's like, "Oh, you guys got to do the rippling thing."
40:20
And we're like, "Oh my god, yeah, we got to do the rippling thing."
40:23
So just like literally and then we showed him like the final cut like the night before we went with it.
40:26
He's like, "You guys should tweak these these couple things." And we're like, "Fuck." Okay.
40:30
And so we got back and we're like editing and stuff like that. It was funny.
40:33
It's funny cuz it's like YC on YC on YC violence, but it's really just like look like they're going to sort their thing out.
40:39
You guys are just having fun.
40:40
Did that ad catalyze around for you guys? It did in some ways. Yeah. Yeah. Yeah. I think we Yeah.
40:45
I think a ton of investor inbound off that. Yeah. No. No.
40:49
It makes it really grounds it because it like not everyone works in cyber security every day.
40:53
It can be a little abstract. There we go, boys. Let's go.
40:58
What do you do with that?
41:00
You push it up or Yeah, we're figuring out. We got a lot of these. We have Congratulations. Exactly.
41:03
No, it's uh I'm super excited for you guys.
41:05
I think we got to give him a different hat for this. I mean, it's the best.
41:11
We can give you We Yeah, we can give you two of these here. It's a special edition. Congratulations.
41:17
Really great chatting with you guys.
41:18
Yeah, great chat with you. Excited for you. We'll follow up.
41:19
Yeah, we'll talk to you soon. Cheers. That was fantastic.
41:23
I'm so glad we got to talk to those guys.
41:24
That was such a good video. Out of the year. Out of the year. Right.
41:26
and and and right at the perfect time because we we were just hitting like peak vibe reel, right?
41:31
If they dropped it even a month later, it would have been gone. Welcome to the stream. I'm John. Nice to meet you. Nice to meet you. I'm John. How you doing?
41:39
PMF for or die since they everyone died. Everyone died.
41:45
You have a story about PMF or die? They died. They died. It happens sometimes. Sometimes.
41:51
Never lock yourself in a room for 90 days.
41:53
Move to sunny San San Francisco. do YC.
41:55
That's my recommendation from here on out. Philadelphia.
42:00
So anyway, uh please introduce yourselves in the company. Yeah, I'm Tom. I'm Eric.
42:03
You guys, you guys look you're not related at all, right?
42:12
You could go by brothers.
42:12
People ask us, people ask us brothers.
42:15
Uh what does the company do?
42:17
We're doing aic people search.
42:17
So we have a database, people database of around 200 million people.
42:22
And um we use a genetic search to search over that for uh companies and businesses to do like sales recruiting uh GTM and uh so so are we talking about specifically like I am a recruiter and I need a saleserson and I'm going to yod you to try and hire them.
42:37
No no so basically like you can put in a criteria like essentially what we do is hold the microphone up here.
42:44
Push the microphone a little closer to there. Yeah.
42:46
I mean, essentially what we do is we like like like deploy an LLM, assign every profile to that LLM, and then given your criteria that could be like one paragraph long.
42:53
We we just ask the LLM if if this profile like meets that criteria and then and then we built like a the load load distributor to run like 10,000 LM calls in parallel. Wow. Do do that at scale.
43:03
You know, we can we can search over like 5 million profiles in like 30 minutes and insane.
43:07
Uh so so walk me through one of the key examples. I'm sure this is live.
43:12
You have customers What's an example of someone using this?
43:17
So, for example, um you know, we had a query come in yesterday actually.
43:19
It was just like every founder that was acquired that was the CTO of their startup was acquired by data bricks or snowflake in the last three years and they and they still work there.
43:28
And there's only probably like 25 people in the world that fits that profile and we found all 25 of them just by using because we can use have an LM go in just like because we have like we can throw as much compute at the problem as we want and then and then and then the LM get better the more comput.
43:41
It's interesting to be able to find you're able to find information that is historically effectively impossible to find without doing all the work that you guys did ahead of time. Makes tons of sense.
43:53
So, uh, who's who what buyer or what buyer archetype within an enterprise or business is most excited to buy your product? Yeah.
44:01
I mean, like mega recruiters by far recruiting firms. Yeah. Oh, no.
44:06
Just like people that you know or like a big recruiter at Yeah.
44:08
know or like a big recruiter at Yeah. I mean we work with mercore right I know for example mercore yeah so so you know like like just like people hunting for talent but it's like a generalized type skill right so for example you know like
44:20
an AI lab's training a new voice model and they need like people that speak Cantonese then it's like okay find me every Cantonese speaker in the US that has like a podcast presence and then like okay great these guys can come
44:30
train our voice models right like that's kind of or they might even need someone who speaks Cantonese and also is an expert in biology so they so they can talk about the biology terms and that's something that how are you going to search that It's so funny because I you
44:42
I run these type of queries in my own head where I'm like we need a videographer who's in LA that has experience in film but you know but it's also part of teapot that's basically what we need often times like has a sense of humor. It's like how would you
44:56
It's like how would you even know that?
44:57
Well, if you look through their post I'm sure you can figure out basically like as close as you can if you just give like a criteria to human recruiter.
45:03
to human recruiter. So you can imagine like 5,000 human recruiters just like manually looking over profiles and then you know okay uh business model are you uh most recruiting firms they charge on like a per fee basis $30,000 to place an engineer somewhere um are you are you doing like a seatbased pricing
45:21
consumption based pricing this sounds expensive if you're talking about running 20 million LLM queries at the same time it's actually not as inexpensive as people think because because you know open source models have gotten so good yeah um like like I'm guessing like you know any like deep research search query cost us like $10 maybe. Okay. But then um you know like Okay.
45:35
But then um you know like we we we charge for conversion with with our PP conversion. Okay. Yeah.
45:41
We charge by conversion customer.
45:43
So that's probably pretty expensive. Exactly.
45:45
And also um we have like a platform that's that's just available to everybody.
45:49
So they can pay us a subscription fee search as much as they want and do email enrichment phone number.
45:54
I feel like we could use this.
45:55
This is we might be customers. Yeah.
45:57
We need a guest that doesn't hate tech that can about this.
46:03
you two meet uh what were you doing before YC?
46:05
Yeah, so we met in elementary school actually.
46:07
So we were originally from Canada. Let's go.
46:08
Um we met in elementary school and we became close friends.
46:16
Yeah, it's been great here.
46:16
But um uh we became close friends when Eric he uninstalled Windows on my computer.
46:20
Um and I was really pissed at him for a day and then we fixed it.
46:23
So then we became great friends after that.
46:25
Windows couldn't load anything homework.
46:31
That was it was during school and then uh ultimate prank is uninstall Windows on your best friend's computer. Boys being boys.
46:37
We spent one semester of college each.
46:39
So So I was at Penn, he was at UC San Diego and then and then come January we were both like like why are we even there? Let's start 18 19. We're both 18 right now. Here we go. Came down here.
46:51
What's What's the youngest team that you've met here besides yourselves? 17.
46:55
There is a high school senior. Okay.
46:58
I met when I was in jail. Okay. Yeah.
47:03
And it's getting younger. Yeah. Yeah. Yeah.
47:05
We have a bottle of wine here.
47:06
We're going to give it to the I'm only hopefully you're not going back through YC in 3 years.
47:12
Hopefully you're at the NASDAQ or something.
47:16
Talk to me about traction metrics.
47:18
Anything that you're sharing here at demo day?
47:19
Anything to get the venture capitalist excited? Yeah. 270 paying customers.
47:23
First version of the So, I don't know if you guys heard about linked linked. No. Yeah. Yeah. All right.
47:28
So, so, so, so a very early version of this product we launched which is like rank Stanford like like Stanford rank. Okay.
47:33
We which was so we basically built this we basically scraped the entire alumni the database of Stanford. I'm sure they love that. Yeah. They were okay with it.
47:42
We we put it online and then uh and then and and then and then we had this uh we had we had this app where people can like see two random alumni put next to then next to each other and then you and then you vote for who's more correct. Who's more correct? Correct.
47:57
And that version of the Yeah.
47:58
And that version of the app picked up like 80,000 users was how we got into YC and stuff. Very cool. Very cool. And then Yeah.
48:04
And then you know we came down here uh 270 paying customers about 16,000 my monthly recurring revenue. Um since ago Yeah. No, but Yeah. Wow. Isn't just you two?
48:18
It's a So there's three of us.
48:18
We were two combo founding engineers from high school. She just graduating.
48:30
No, I'm super excited for you guys.
48:33
Congratulations on the product and I actually have a bunch of people to send this to. Yeah, this is fantastic. We should give it a try. Fantastic. Thank you so much. We'll talk to you soon. Great meeting you guys. Fantastic.
48:43
Uh let's bring in the next team if we have one. Come on down. How you doing? Aaron, what's up? How you doing?
48:51
This is a YC alumni and he just he just raised a series A today. Congratulations A here. Yeah.
48:58
So, we were trying to make this happen for the last week, but he just announced his series A today. 17 million, right? 17 million. Congratulations. There we go.
49:06
I mean, we have stuff to celebrate. I already got the hat. I got the hat. Hey, congratulations.
49:15
Seems like you've done that a couple times. Yeah. Yeah.
49:17
This is the biggest round of the day. All right. Uh, who did the round?
49:22
Uh, how far along are you? How big is the company? Give me some stats. Yeah. Yeah. Okay.
49:25
Uh, so 8 8C did the By the way, guys, this is awesome.
49:29
I did like the interview with Venturebe and this I'm way more starruck by this.
49:32
So, like I'm not just saying that, but I'm uh Yeah. So, 8VC led the round. Absolute dog.
49:39
Uh, what what partner are you working with? Uh, Jack Moshkovitz. He's great. He's fantastic. Um, yeah. Yeah. So, how far along?
49:46
So, we were uh And were you in the last batch?
49:49
No, we were we were a couple batches ago. We were summer 23. Um, great vintage.
49:52
Was that still excellent or was that back?
49:56
No, we were the first back. We were Yeah. Yeah. Yeah. We had an advantage. Um, but yeah.
50:00
So, Outset does AI moderated research. So, what does that mean?
50:04
It's like when C when when big companies have to do a ton of research like Nestle has to go figure out what, you know, whether they should launch this weird version of Desjouro pizza or something, they go do research.
50:12
So, either they're running massive surveys and they're getting like very low fidelity data.
50:17
They don't really know much.
50:18
It's just a bunch of numbers.
50:18
or they're running interviews and that's where it's a one-on-one interview with everybody, right?
50:22
Which not actually cost effective. So, totally.
50:23
So, now you can run AIE interviews.
50:25
That means AI is leading the conversation, digging in, following up, probing deeper, and synthesizing all of that for you. Got it.
50:32
Uh, and we How big is that?
50:32
How big is the legacy market?
50:34
So, so the research market is like 140 billion.
50:38
It's it's actually a really big one. Uh, just like Yeah.
50:41
And there's like huge companies that you probably may have never heard like Ipsos and Contour and like these like big guys that are uh just kind of sitting there.
50:49
So, so there's a lot of opportunity and uh yeah, we work with like Microsoft, Nestle, Weight Watchers.
50:53
So, we've been super enterprise focused and uh yeah, we're a couple years in.
50:57
What are the interaction patterns that you like or you think are kind of unlocked by AI?
50:59
I imagine that voice phone calls is top of mind versus like forms which was always like available and already computerized essentially.
51:10
It's actually I think the cooler thing is what you can get from participants and synthesized.
51:13
So it's like so now we do video interviews and they do audio and they can even share their screen, right?
51:18
So all of that is being ingested and then like people ask like to say I have an avatar when it's interviewing and we actually did research and people don't want that.
51:25
They don't want the avatar.
51:25
No, they don't want the avatar.
51:26
The avatar is something like weird uncanny valley stuff where I'm like and you're just like used to phone calls.
51:31
Yeah, people used to phone calls and they're fine sharing their video, but like if you suddenly see an AI, you're like, I'm trying to make, you know, 15 bucks doing some research.
51:38
You like suddenly see that, you're going to be all weirded out.
51:41
So, it's actually much better to have AI come through with voice and text. Yep.
51:44
Talk to me about recruiting. You said 15 bucks.
51:45
That's enough to get someone to jump on, but how do they even find out that 15 bucks is on the table? Yeah.
51:51
So, we partner with a number of different like companies that do nothing but panels, like nothing but recruiting. Nothing but recruiting.
51:56
So, you have like uh user interviews and prolific are they probably get some demographics and some base All that and they have millions of people that are like ready to It's like gig work, right? And and so they Okay.
52:06
I need 100,000 people that drink energy drinks to give me feedback. Exactly. Exactly. And you could Yeah.
52:11
You can do all that through our platform.
52:12
Is there a certain unlock when an AI doesn't need to like, you know, if a human is scheduling research calls, you know, you could imagine they do like four 30 minute blocks and then they take a little break and they do some more or something like that.
52:24
I I don't know how it works, but an AI could hypothetically talk for hours and hours and hours and hours like kind of 100%.
52:30
So there's like, you know, I think a lot of AI stuff is like, oh, where can it replace the human thing and now it's cheaper, but actually like this this is uh taking on the stuff that like humans can't physically do.
52:42
We only have 24 hours in a day.
52:44
And so it happens that people use it to like interview 500 people, right, in a day or two.
52:48
And that's like it's literally not possible.
52:49
It's like just the laws of physics don't allow it.
52:50
And so they're able to do that.
52:52
They can do multilingual.
52:53
They kind of do it all at once.
52:55
So, you can wind up like unlocking actual like stuff you've never heard.
52:58
I don't Can I curse on this?
53:00
Uh, we usually don't, but you uh stuff that they like would not have uncovered anywhere else.
53:05
Um, and they actually are able to get that like in this way. Yeah.
53:09
What's your what's your stack under the hood?
53:12
What models are you using getting the most value out of?
53:13
Yeah, we're using a combination.
53:15
So, it's, you know, it's like we're hitting multiple models constantly, but Azure we we're using a lot of Azure actually.
53:20
OpenAI models under the hood through Azure and it is your model router helpful?
53:24
I saw they announced that at Build.
53:26
I haven't talked to anyone that's actually used it.
53:28
Um I I don't know yet actually.
53:28
I so I don't think we rolling it out.
53:31
So basically like what we need is just incredible amount of reliability because what we'll have is like three customers are all running like 500 simultaneous interviews.
53:40
So we have to actually scale very very quickly.
53:42
Um and also like a lot of our customers like the Nestics of the world like they care a lot about like super safe, super reliable.
53:47
So we kind of like wind up the kind of Azure. Yeah.
53:52
And then you're also probably going through like peak LLM usage hours too cuz you're not doing it in the middle of the night.
53:57
No, we can't process it on our own time.
53:59
It like has to happen in that moment.
54:01
But then we also fall back to OpenAI. We use Gemini for stuff.
54:04
So we're like hitting a lot. Yeah.
54:06
Talk about the uh uh the is the voice modality beyond the uncanny valley at this point?
54:12
Is that why voice is valuable?
54:13
Are you using voice a lot?
54:15
because you can imagine that uh this might have been possible via text interactions.
54:19
You're texting your responses back and forth.
54:20
Probably get more out of a voice interaction.
54:22
Uh are we just if we if we talk to you again in like two years, do you think it'll be like okay yeah now I'm a believer in the in the avatar thing because it is photoreal. Okay. So so two things.
54:31
So one right now what matters most is obviously the modality of the participant.
54:36
Like if you think about like all we care about is the most deep like like uh thoughtful in-depth data that we can like pull from you that respond.
54:45
So that matters way better than text and that's way better than our first product that we like talking. Yeah.
54:50
Our first like pilot with Weight Watchers back in 2023 was like all text and it was actually pretty good but like it's nothing compared to what people actually say.
54:56
Um and so that's what matters most is like video screen share uh uh uh voice from the participants from AI. Yeah.
55:03
Like so we use voice a lot.
55:05
So there's a voice to voice mode where there's like no buttons, it's just conversation and like people like it but like not as much.
55:11
And I think there's still just if it's not a person, then it's still got just the minor imperfections, the kind of slight bits of latency.
55:18
And so I do think in 2 years we'll talk more about that, but ultimately like people know it's a computer.
55:24
Like they know it's AI and like they're kind of cool about it.
55:26
Like we we've done a bunch of this research.
55:29
We're like do you care that it's AI? Like no like I I get it. Yeah. Right.
55:30
In fact, they like have even expressed that like they'll share more because there isn't a person.
55:36
It's this idea of like social desiraability bias.
55:38
You're like, I don't want to come off as a person that is X, Y, and Z to another human.
55:41
I will just tell you, look, I want this to be faster.
55:46
I want you to taste better. Like, yeah.
55:48
Or or like or like the real reason I'm not using your product is this.
55:51
I'm not going to say that to a PM or a researcher who's like at the company, right?
55:54
But instead, you'll tell the real truth.
55:56
And that was like our initial pilot with Weight Watchers was all about weight loss.
56:00
And like that was like a thing people don't want to share a lot about, but with AI they like shared everything about their lifestyle. Yeah.
56:07
I mean it sounds like you've done like you've worked with really big companies and that's where the money is.
56:11
But uh when you went through YC or if you're here uh you know there's a big theme of talk to your customers.
56:14
Has there been any pull at the lower end of the market? Yeah. It it's funny.
56:18
I I sometimes get a founder reaching out like I I really want to use this cuz I don't want to talk to my customers.
56:23
Like talk to your customers.
56:25
We don't want you as customer. Yeah.
56:30
There's basically I like I think a good a good reason not to use an AI moderator is like if you could sell to that person probably don't outsource that, right?
56:37
Like maybe to build the relationship yourself.
56:39
So the truth is especially all the B2B stuff there's not as like we usually turn around and say come back when you're like a couple hundred people and like you're kind of scaling that out.
56:47
Um but yeah, with with some consumer stuff where you really have millions of people you're trying to learn from, it can make a ton of sense.
56:55
uh talk to me about the like data processing and the intelligibility that goes into once you have all that data.
57:01
Uh it's very nice to be like hey we have like you know 5,000 hours of video we prepared a 200page report. Yeah. But nobody reads that.
57:08
So how are you thinking about actually compressing that down because that seems uniquely suitable for AI but there's still a lot of art in terms of like a lot of people say oh yeah I did a deep research report and then I uh the next query was give me 10 bullet points about that because I didn't actually want the full report. Yeah. Yeah. So so all right.
57:23
So, so our vision here is like we should be building we are building the like deep research but for primary research.
57:29
So you think about deep research is like all right all desk research now commoditized.
57:33
commoditized. So what if you just ask a question you just want to like learn from real people that's much more upto-date that whatever like your own proprietary data it should be the same kind of idea right end to end agents are doing that but today like the premise of AI kind of uh uh scaling your qualitative research is like you also have to help them do something with all
57:51
that conversational data right because otherwise you're like left with just like hours and hours of transcripts I'm like I'm not going to review that the application of this is I know this is not what you're focusing on but if I was a a a VC that wanted to write a a multi multi00 million growth check being able to like get live interviews with like 500 customers. People are going to do
58:09
People are going to do this with GLG and that's right.
58:10
No, this is a huge opportunity actually.
58:13
So, so um yeah, I have a whole side thought like I think one of the challenges there is with the expert networks is all about finding the right people.
58:21
But if you're in a situation where you can find the right people and you can find a hundred of the right people.
58:26
Well, we just had Plato AI on you because you you should talk to them. They're in this batch.
58:30
They do like LLM based people search.
58:30
So you could find like every person that at at data bricks that was a former founder, you know.
58:35
No, there's an opportunity to connect all of that through through that.
58:38
But what I was going to say with the synthesis is is what we do is basically taking all the video stuff and then we like process it and we give you basically reports, but it's like not just a like here's what it's telling you like deep research style.
58:49
But what you can do is like start like uh uh slicing and dicing it.
58:51
You could like we quantify it. We give you breakdowns.
58:55
We like build highlight reels for you.
58:57
And then like people can like cut it and segment it.
58:59
And so it's like a whole analytic suite on top of qualitative data which is like not a thing that has ever been done cuz what were you doing what were you doing before this?
59:07
So before this I was VP of product at triple bite if you know yeah harsh hired me. Yeah. Exactly. Exactly.
59:15
He uh yeah he anyway so so uh I I worked at Triple Bite at at uh Jumpstart another company.
59:20
So, I was like leading product and design teams, but earlier in my career, I was like a I was a consultant where I was doing like this work non-stop where I was like, "Are you a Are you a nominative determinism guy?" Yeah. Yeah.
59:30
He's looking for the capital to fire a billion dollars into research. Yeah.
59:35
I have not capitalized on that.
59:38
I was looking at, but we're big we're big uh we're big into the names or the truth. The name like that. Yeah. It works well for you.
59:46
I have a friend who always calls me the loose cannon.
59:50
Like you can never know what to expect.
59:52
It's a little bit too much.
59:52
Dial it in the capital cannon.
59:54
You can trust it with your capital.
59:56
Just give it to fire in the capital cannon and boom. Yeah.
1:00:01
I'm going to pivot off of loose cannon off to capital. Aaron capital cannon. There you go.
1:00:06
Anyway, this has been fantastic. Thanks so much. Congratulations.
1:00:08
We'll have you back on sometime. $17 million series A. Let's go. Fantastic.
1:00:13
Biggest round we've heard yet.
1:00:16
Let's bring in the next guest.
1:00:18
Operative are going the set of pit pipers. Welcome to the stream. How you doing? How's it going? Good to meet you. I'm John.
1:00:28
Eric, nice to meet you guys. Eric, good to meet you.
1:00:32
You're going to want to keep those mics close to you because it is noisy here at YC Demo Day 2025. Good to meet you.
1:00:39
Can you introduce and the company that you Awesome. Yeah.
1:00:43
Uh we're we're operative. Uh I'm I'm Chris. I'm Chris Settles.
1:00:45
This is my co-founder, Eric Kintania.
1:00:47
You can introduce yourself as well, but um we're we're friends from high school.
1:00:51
We met at West Aurora High School in Aurora, Illinois in 2014.
1:00:55
We were doing our first Java programming class together. Wow. Wow.
1:01:00
And uh 10 years later, here we are. Deep deep.
1:01:02
What What did you guys do between uh then and now? Yeah.
1:01:04
Do you want to tell other programming languages?
1:01:08
Do you want to tell more of the story? Yeah.
1:01:09
I mean, we went to college.
1:01:11
Maybe you still write Java. I don't know. Yeah.
1:01:12
We went to college, worked at a couple big tech companies, worked a couple Chris was at Uber. You can talk about that. There you go. Uh, nice.
1:01:25
Did you wear the Pit Vipers during your your main pitch? Sorry.
1:01:29
Oh, you're asking the Sun.
1:01:32
Did you wear them while you were pitching the the Oh, no.
1:01:33
I just got these from Marco. I don't know.
1:01:35
We saw Marco in here wearing these.
1:01:37
We're like, Marco, you look so cool.
1:01:42
So, break down the company. Yeah. What are you guys doing?
1:01:43
All right, so we're working on web app code generation for internal APIs.
1:01:47
So you can imagine having like a lovable plus a retool for your company where you can on demand just create any kind of application that you're thinking about whether it's like a new dashboard or it's some kind of like app to manage your airflow and you want to have a nice UI with it and you want to connect it to all these different pipelines.
1:02:06
I mean that's just one use case you can think about but you can build any kind of front-end application that connects to existing APIs that you have in your company.
1:02:14
Yeah, I remember like when you when you set up like a Django website you kind of get like the Django admin like like out of the box and you can just in in you know uh in investigate all the different classes that you've kind of defined in the database.
1:02:25
Uh what are some examples you could give us of these internal APIs that typically float around in companies or you can either give like a precise example or just a general example. Yeah. Do you want to give one? Yeah.
1:02:36
I mean um a lot of the use cases are centered around like customer service.
1:02:40
So people like want to interact with like a database.
1:02:42
People who are doing support want to uh want to like change like payments and stuff like that, data visualization, stuff like that. Okay.
1:02:48
So uh yeah, I mean it is it is it unique about like bringing different services together because a lot of like smaller companies would say you want to you want to look at the payments admin head over to your Stripe dashboard.
1:03:00
Stripe's already built that.
1:03:02
Where where are where are companies currently falling short?
1:03:05
Is it that they're they're not bringing the data together across services?
1:03:08
Or is it that they're developing like like their own databases and their own their own tables that just don't have a don't have an API out of the box or don't have a don't have a web app in front of their API out of the box. Yeah. Yeah.
1:03:21
box. Yeah. Yeah. So as so definitely startups it's super easy to just say okay yeah check out the stripe dashboard manage and then that's what stripe does physical customer service flow it's like you you go to Shopify for this and then
1:03:32
you go to the the CMS for this you go to Stripe if there's a problem over there and then you go payroll it's all SAS products yeah but one of the things like we we noticed especially at our our jobs in big tech is that eventually your
1:03:44
product gets really complicated and you actually don't there's not a SAS product that those that those uh services offer and so you end up needing to build something on top of it in order to manage it and then you end up building
1:03:55
needing to build all these different internal tools to like have all of that organized in a nice way where you can connect it all together because the traditional SAS doesn't uh support the features that you're looking for. Got Got it.
1:04:05
And so then as a result you hire a team to build out those kinds of applications and then spend a lot of money and that's what uh we're trying to bridge that.
1:04:13
What was the aha moment for you guys?
1:04:16
Were you seeing the the kind of explosion of tools like lovable and things like that and then and then you saw wait why aren't people doing this internally or what what was the kind of moment that you guys decided to focus on this?
1:04:27
I mean I I think for us we saw like we launched this like lovable type product and we saw a lot of people from companies using it as a consumer product actually at first. Yeah.
1:04:34
To build internal tools for their company.
1:04:36
So we actually we were like oh we should just bring this directly B2B. Cool. Very cool.
1:04:40
Yeah, in some ways it makes sense being able to like quickly generate something, test it, and then like it's very different than sort of these like ephemeral products that exist and uh ultimately will need to be I don't know sometimes completely rebuilt.
1:04:53
Uh talk about the go to market motion.
1:04:56
Uh it sounds like this is not a company where you need to sell to every other startup in YC.
1:05:01
Uh who are you selling to?
1:05:01
How are you actually convincing them to take the leap and go with you? Yeah.
1:05:05
So we're we're starting uh from the initial sort of traction we saw with the consumer product, we decided we want to work on this enterprise direction andor like larger organization direction uh because of these like use cases we saw with uh people signing up from all of their work emails and building apps.
1:05:21
Uh so we're starting some design partnerships with large organizations.
1:05:25
I can't say I won't say the exact name.
1:05:27
Um, and we're planning to kind of just leverage our our warm uh warm intro outbound network or warm intro network to be able to talk to some more organizations.
1:05:36
And I think like there's some uh like there's actually a large percentage of companies that even will try to use like retool to build uh internal apps.
1:05:43
And so uh we like we think we can work with some of the other YC companies that are doing things like that using that and but maybe have you guys demo day.
1:05:54
Are you guys are you guys working with retool or you you you competing kind of competing in some sense of it?
1:06:00
Good luck with talking smart but I good luck to market.
1:06:05
Yeah, we have a pretty cool direction that's like pretty unique at least at the moment.
1:06:11
So talk to me about the actual instantiation of the web app.
1:06:13
I'm sure you're using AI and code generation. What's working?
1:06:17
what uh uh how much is uh are you leveraging 03 or claude or or open source or Gemini?
1:06:24
What's uh what are you looking for?
1:06:27
Where are the models falling short?
1:06:29
Where are you kind of like trying to stay ahead of the puck because everything's developing so quickly? You want to take it? Yeah.
1:06:33
So, I think uh on the platform I think the foundation models provide like a nice foundation. Yeah.
1:06:39
Um but like we try to leverage uh good tools.
1:06:42
So like viewing a file tree, we had a browser agent on top to test and validate the app. Okay.
1:06:48
Uh the model's far short in I think they're good at like going zero to one, but I think like if you go 0ero to one and then there's a bug, going back and finding what file it is, what's implicated in it, I think it's very hard for the models and it's better to just start over. Okay. Yeah.
1:07:01
start over. Okay. Yeah. Uh, have you benchmarked against how long it takes someone to build a web app for a on top of a private API using cursor and just saying I'm going to vibe code this myself versus your product because it feels like it's getting faster and faster and there's a lot of I mean
1:07:19
there's like there's whole there's whole open source projects for like build out the API docs around an API just from you know this was programmatic this wasn't even uh this wasn't even AI you know you just have like oh you want to you want to put this you want to instantiate this as a blog Okay, here you go. Um, uh,
1:07:31
Um, uh, what are you benchmarking against?
1:07:34
Yeah, actually, um, maybe a cool story like on the on the backtory of how we came across this is that we actually started with people wanting to develop apps like inside cursor.
1:07:44
And so one of the kind of unique insights we had is that uh today like it it require like developing any kind of like front end requires that you ask cursor for a prompt and then you open up the web page and go click on it and just verify that it looks how you want it to and you can go and like then tell cursor like okay I want to you know move the blue button inside the black box and you have to like just keep prompting it until it do does that.
1:08:05
So actually one thing Eric and I worked the first thing Eric and I worked on was like a actually an MCP tool.
1:08:10
Oh yeah, that uh allows people to like opens up a browser agent that can go and view changes that a coding agent makes.
1:08:17
Uh and it will it'll just test to see if the like visually if the app actually works.
1:08:24
Actually there's uh there's one of our users over there just giving us feedback on it.
1:08:30
So we grew that to like around a thousand GitHub stars and so people got really excited about that.
1:08:35
But we wanted to bring those same tools into a product like Lovable or like Codegen and be able to have all of this code generation with testing built in.
1:08:44
So that way we can allow users to like just go from prompt to a working web page without any interaction. Very cool.
1:08:50
Are you guys still raising raising right now? We're still raising.
1:08:54
Uh we have uh we've been backed by weekend fund and also a few other angel investors.
1:08:59
Um and we are we're still raising and open to with other investors.
1:09:04
We have an angel investor and retool investor in us. So, um, play the hits. Play the hits. Play the hits.
1:09:11
Find something you love and just Do you have any metrics that you show that you shared here at demo day? Yeah.
1:09:16
Uh, as I mentioned, we had the GitHub repo.
1:09:18
We la we like scaled to 100 or sorry um, thousand a,000 stars. That's pretty good.
1:09:23
We just launched the consumer product.
1:09:25
We had it got around 2500 different users building using operative to build apps. Crazy. Yeah, that's great.
1:09:31
And right now there's like about a 4% conversion from free to pro plan.
1:09:35
We have a pretty generous free tier.
1:09:36
So you can go and use the app however you want.
1:09:38
But the for the the power users like there's around 4% of them converting. So we have about one 1.
1:09:43
5k monthly revenue at the moment. Amazing.
1:09:45
And uh we're that's our as with the consumer product but uh we're planning to scale more uh revenue.
1:09:49
You could probably get that on your first contract. Exactly.
1:09:54
Thank you for stopping by. Please enjoy your guys. Thank you so much. Have fun out there.
1:09:59
It's great having you on. We'll talk to you soon.
1:10:01
All right, let's bring in the next crew. We are at YC demo day. Hey, how you doing this?
1:10:09
It's time to talk sleep scores. Let's talk sleep.
1:10:11
How did you sleep last night? It was brutal.
1:10:13
I was I was at the Rosewood.
1:10:15
The Rosewood doesn't have eight sleep. This is a big problem. Yeah. Yeah. Yeah.
1:10:19
90% of the guests are good. Good to see you. What's happening?
1:10:25
I want to talk I want to talk F1. I want to talk F1.
1:10:27
Uh you just did a interview with Charlotte Clair. Uh break it down.
1:10:31
What did you learn from him?
1:10:31
Uh his obsession for uh every single detail in his uh preparation.
1:10:37
He goes for two weeks at the mountain in January to prepare for the season. Elevation elevation. Elevation.
1:10:44
And then he does every sort of skiing for like eight hours a day.
1:10:50
And then he goes to the gym and then he brings the pod.
1:10:52
He sleeps on the pod while he's there.
1:10:56
there is when he really prepares the season. Yeah.
1:10:57
Um and and then his obsession for every single detail when when he travels, all the gadgets that he brings with himself from, you know, devices for recovery, ice bath, obviously the pod, the neck training.
1:11:10
Is he doing the leg compression thing? That's a big one. He does.
1:11:14
And I don't know if you saw it.
1:11:16
So we So Charles was talking to us about the fact that uh when he's on the grid, it's really hot. Yeah. Yeah.
1:11:23
And a lot of athletes in Formula 1 now, they use these vests, cooling vests.
1:11:28
But they don't really work.
1:11:30
And so the way you want to really cool your body, uh, you need to cool the palm of your hands. Oh, interesting.
1:11:35
And so I was with my co-ounder, Max, and we said, "What if we build cooling gloves for you?"
1:11:42
He said, "Oh, that would be interesting."
1:11:44
So we built the gloves in 3 days. No way.
1:11:46
And then one of us, one of our people, they flew to meet him in Barca.
1:11:53
In Barca, there were like 35° Celsius. It was super hot.
1:11:56
And so Charles started using these gloves, cooling gloves that we built for him.
1:12:02
And then as he goes in the box, uh, Ferrari takes a picture of him just, you know, for scooter Ferrari blah blah.
1:12:07
And so he was on the cover of the Instagram account with so it was pre-branding for us with the device we built for him.
1:12:17
So now so you see that with the tires they have the tire warmers then you have the hand coolers.
1:12:22
Every different part of the F1 machine needs to be temperature controlled perfect saw him using this and so paddle players tennis players they all say can I use it and say but man we did we didn't.
1:12:37
And so now we have a team that is building this cooling blows for a few outlets.
1:12:40
That's that's incredible. Um great partnership.
1:12:42
What has YC demo day been like for you?
1:12:44
Are you here just trying to sell eight sleeps or are you also doing some investing?
1:12:49
What are you What are you getting out of of YC Demo Day today? Yeah.
1:12:52
Yeah, I do a bunch of investing.
1:12:54
I invested like probably 20 companies in this batch already. Wow. Amazing.
1:12:59
You got to get I mean you got to get them in here.
1:13:01
You need to start early or then you're out.
1:13:03
Oh yeah, you got to get in early. You got to get in early.
1:13:07
And so in every batch I try to invest in around 20% of the batch. Oh, cool. More or less. That's great.
1:13:11
Um, and I have been doing this for two years.
1:13:15
Have you seen anyone doing cool hardware, cool consumer devices?
1:13:17
I know that there's a ton of AI.
1:13:19
There's some hard tech, defense tech's becoming cool, but I always like I like the aid because it's a gadget.
1:13:26
You can give it to someone for, you know, Christmas and they like experience it every day in a very different way than just nap on their phone. Have you seen anything?
1:13:32
So the I I I I I'll answer your question, but it's cool because I walk around with my head and people stop me and they say, "Oh, I sleep on your product."
1:13:40
I just met two two founders and one had a 75 score, the other one a 48 score. 48 the night before. That doesn't work.
1:13:52
I've been smoking Jordy this week. I got I beat him twice. I got it. I'm up in the 90s. I'm doing great. I've had a rough one.
1:13:58
But there is not a lot of consumer hardware. It's hard. It's so hard. Yeah, it's really hard.
1:14:03
I was just talking to a few founders.
1:14:05
Even when I look back, uh other companies starting with us, they all struggle.
1:14:09
So, we have been so lucky to be here today.
1:14:11
Uh but you see a lot of really cool stuff now in robotics. Yep. Yep.
1:14:15
Matic robots, we've been in the office and at home and so usually there is an hardware section and that is the first section where I go.
1:14:22
So, art techch or hardware that is my passion and then Yeah. AI is everywhere. So, yeah. Yeah.
1:14:28
I mean, you see a lot at CES.
1:14:30
You'll see the AI connected oven and the AI connected toaster and YC's kind of stayed away from that because it feels like it's hard to build like an independent business around.
1:14:37
Uh but but I am optimistic that that once the software side of AI is so commoditized and so uh just ubiquitous.
1:14:45
We'll see another revolution in hardware, another and I think with robots things will get easier because robots will explode and a lot of consumer will buy different shapes.
1:14:57
Matt Freriedman was talking about he wants the the the robot that picks up the leaves one by one instead of leaf blower and and it's like a funny idea but it feels like yeah that's only a couple years away and it'll just be even for security.
1:15:07
I have this idea about a robot that goes around your house for security cameras everywhere cameras and lights right I would immediately buy that you could go around my house and make sure that especially if you could put a gun on it.
1:15:20
I mean Amazon Amazon did launch a a drone that will or maybe they just launched a video about this.
1:15:26
There's a drone that takes off from a base station where it charges and it can fly around your house and kind of and kind of patrol inside your house.
1:15:34
But yeah, I wanted to add when the when the fires were happening, I figured out that a lot of fires in LA are just started from a single ember landing in like a backyard or on a house or get stuck and you just realize that, you know, there's probably an opportunity for drone based.
1:15:46
Yeah, there's actually a couple companies that did uh uh like water turrets that you mount to your to your roof and then if they see fire, they can just spray right there. It's a hose.
1:15:57
It's literally just a hose on an articulated arm.
1:15:58
It's like not that complicated, but you could What about What about at 8?
1:16:01
Any any any other hardware coming down the line that you can talk you can kind of allude to yet?
1:16:07
So, actually, we have an office in SE.
1:16:09
So, I just landed I came here.
1:16:09
I'll be here for a couple of hours then I go to the office to see the new products. Very cool.
1:16:15
I'm already sleeping on the next generation. Such an edge. That's such an edge. Edge. You're on five on pod. I'm already on pod six.
1:16:24
All my friends, they always make jokes because I always sleep on the next generation and there are new devices.
1:16:31
So, they buy the latest, but I'm already one one generation. This is how you win. This is how you win.
1:16:37
We started working with some new sensors that are incredible in terms of computer vision.
1:16:42
So, we really want to double down on body scanning and scan your body while you're asleep to save your life.
1:16:49
And that to me is the one of the most exciting things because if we can convert your bed in a health platform and save your life, that's that's pretty sick. Yeah, that's amazing.
1:16:56
What uh what are the companies that you're most excited about in the batch without picking too many favorites out of the 20?
1:17:02
Any anything that you're most kind of excited about?
1:17:04
At the end of the day, I just get excited with founders.
1:17:07
I mean, I just met this guy and he's a high school dropout. He's 18 and he's what?
1:17:14
Yeah, because I was at school. I decided to drop out.
1:17:17
I thought there I thought there was this opportunity for AI to help teachers and so I dropped out.
1:17:23
I built it and now I'm selling it to my teachers. What? That's amazing.
1:17:24
So when you see these people, right, I don't even I don't care what happens with your company, but I admire you so much that can I can can I want to back the founder. Exactly.
1:17:36
And so that is what excites me like to stay young and see these generations shaping the future. That's fantastic.
1:17:44
Well, thank you so much for stopping by. We will see you soon. Great job, guys. Thank you. Yeah. Yeah. Glad you did. It's been great.
1:17:51
Let's bring in the next team.
1:17:53
Welcome to the YC Demo Day 2025 stream. Some good.
1:17:57
I put so much of the the Yeah, it's okay. I'm working through it. How you guys doing?
1:18:01
Oh, you guys already got the hats on.
1:18:02
We'll see if there's if there's other surprises in store.
1:18:04
We might need to blow the whistle.
1:18:06
Welcome to the live stream. How you doing?
1:18:08
I like I like how you guys just said uh made in SF, not made with love.
1:18:12
Made with [Laughter] taking shots.
1:18:18
We have a made in with love in San Francisco as well. So Oh, you do? Okay. Well, what is Throxy? Break it down for us. Explain the business.
1:18:25
We building AI agents that help people selling in traditional industries such as manufacturing, distribution. Okay.
1:18:33
There are sectors in which selling is very hard especially from a B2B perspective. Sure.
1:18:37
So we're helping those companies prospect into legacy industries. Okay.
1:18:42
And we manage the entire outreach to those. Okay.
1:18:47
Whenever someone's interested in speaking with my clients, I connect them with their buyers. Sure.
1:18:50
And uh to help them grow.
1:18:53
And so that's like selling super technical products.
1:18:55
What does that what does that look like?
1:18:57
Yeah, it's selling super technical products but also professional services such as consulting.
1:19:02
The important thing is we help people selling into traditional spaces like manufacturing. Okay.
1:19:07
So, so, so there's a manufacturing company out there.
1:19:12
They're making microphones, for example.
1:19:14
I am a company that's going to sell, you know, better software design software that runs on this or or or automates the the facility.
1:19:21
You're going to help me find clients to sell to.
1:19:23
Is this more about the prospecting and developing a lead list, doing the actual outreach?
1:19:32
Is this an AI uh business development representative SDR play?
1:19:35
Are we going to see a billboard on the 101 for you pretty soon? What's going on?
1:19:41
So, it's a bit of like everything you've mentioned.
1:19:43
So, like we don't like to micro ourselves as AI SDRs because they have like a bad reputation reputation and we think like focus is a multiplier on like the work we do and that's why we're like serving these traditional industries which are like traditionally like underserved.
1:19:57
um everyone's ignoring them, but they're like huge market opportunity and like really high average contract values.
1:20:04
So we can like have people serving these industries both with AI but with a bit of human in the loop right now and now we're automating those humans in the loop as models get better as agents improve and like rolling them out.
1:20:18
So talk about the co-pilot era where is it important for in the sales process to keep the human in the loop right now?
1:20:25
What is the most automatable part of that process?
1:20:27
So the most automatable part is qualifying the whole companies.
1:20:32
So like actually like we just like pull a list of companies from like our crawlers and then we look for like specific stuff with AI agents and we just qualify them.
1:20:42
Could they even be a buyer? Do they have budget? Are they big enough?
1:20:45
Are they declining in sales?
1:20:46
Are they about to get rolled up into some private equity thing?
1:20:48
The thing is like because we're focusing only in manufacturing companies, we can check for very specific stuff.
1:20:53
So like does this machine like fit like any specific specifications?
1:20:57
Do they have like this grind type?
1:20:59
Do they do like CNC milling?
1:21:01
That kind of stuff which is really important where like horizontal AISDRs fail and they fail to serve them because they're too generic because if I'm selling CNC software and some manufacturer doesn't use CNC's, why should I even talk to them?
1:21:13
So you're saving me time that way.
1:21:15
How did you guys get into this?
1:21:16
So uh I think it's I was in sales.
1:21:20
I was doing a lot of manual work myself.
1:21:21
Uh I've been an SDR three companies completely different uh value propositions.
1:21:27
But I think one of the big issues was actually finding the company I can sell to.
1:21:31
I was doing all of that very manual research.
1:21:33
Do they have buying power?
1:21:35
Do they have this specific certification?
1:21:37
When I was selling into hospitals, I had to check what their team staff looked like to see where they fit my software. And I hated my life.
1:21:46
I was like, but you were still performing.
1:21:48
You were still performing, right?
1:21:50
You were putting up big numbers. Yeah, I actually was.
1:21:52
And uh but but yeah, I I generally felt like my my job was going to be replaced soon.
1:22:01
So, I was like, let me get ahead of this. Let me replace myself. Disrupt yourself.
1:22:04
Talk to me about what it takes to actually qualify a lead.
1:22:07
What are the data sources?
1:22:09
I've heard LinkedIn's extremely rich, but it's very locked down and they don't let you play with the API anymore.
1:22:14
Uh obviously you can crawl around on Google search and some companies have a lot of information on their websites.
1:22:20
Some of these manufacturers barely even have websites at all.
1:22:23
How are you getting data? That's our insight.
1:22:25
Like our insight is like LinkedIn doesn't like serve these manufacturing people because the owner of like a manufacturing company is not on LinkedIn.
1:22:31
Their prospects are not there.
1:22:33
So we built our owners which are like the whole knowledge graph and then agents qualify these people which have access to like specific tools with directories of other manufacturing companies or API like access to like machine specification um access to vision so we can like check out the content of the website like take a screenshot.
1:22:55
Oh interesting take a screenshot. Hey that's a CNC. Exactly. This is a CNC company. Talk about traction.
1:23:00
When did you guys come into YC with this idea and you've just been working on it or did you iterate towards it?
1:23:05
Yeah, we came in with this idea.
1:23:05
Uh in 6 months we've gone to 1.
1:23:08
5 million in annual revenue.
1:23:11
Oh, that might be the biggest one we've heard yet. Let's go. 1. 5 million, baby. Let's go. Congratulations. That's sick. That's amazing.
1:23:23
So, the round's already closed, I imagine. Absolute dogs. Absolutely. That's great. That's great. Um that's fantastic.
1:23:33
What's your guys' backstory? How did you get to YC?
1:23:34
Um we met in high school and we've always be like building stuff since we were kids. Awesome.
1:23:39
Um Pablo was like I hate sales but like I love money.
1:23:45
I was like let's go build a company together.
1:23:47
I was working in AI JP Morgan.
1:23:50
It was like the most boring thing to do ever. Um working in a bank.
1:23:54
So I was like let's go do it for the money. That's amazing. How big is the team?
1:23:58
I mean it sounds like you you've already scaled this business a little bit. Yeah.
1:24:01
So we're a team of four right now. Okay.
1:24:03
Um focus is very important.
1:24:06
So when you asking where does humans perform better than AI that's what we're testing is whenever AI does better we'll automate it but if not we have us actually doing that work.
1:24:17
We want to be very thick into the workflow understand the problem and uh at the end of the day is my reputation down the line. It's not the AID of me.
1:24:26
So, we're showing face in front of our clients and ensuring that this works.
1:24:32
Yeah, that makes a ton of sense. Well, good luck to you. Amazing, guys. Congratulations. Awesome. Thanks for cheers. Nice meeting you.
1:24:37
We will talk to you soon and we will continue our coverage of YC Demo Day 2025.
1:24:42
We will bring in the next guest.
1:24:46
I see some people out there.
1:24:47
Come on down to the Palace of Party Rounds.
1:24:50
Tell us about your company. How you doing? Morphix in the studio. I see one hat.
1:24:54
I got to give out a second hat. How you doing? Welcome to the stream. Good catch. Come on down. Good catch. Uh, who are you? What do you do?
1:25:04
Uh, we are Morphic AI and we build open-source multimodal search for AI agents and applications. Okay.
1:25:10
Open- source multimodal search.
1:25:12
What are uh give me some examples of the multimodality.
1:25:16
Uh, what are we searching?
1:25:19
because some of these data sets I'm imagining if you're trying to search over YouTube videos, YouTube's going to shut you down if I'm trying to search across that.
1:25:24
No, that's a great question.
1:25:26
So, for multimodality, it includes not only like just plain textual documents, but documents that might have pictures, photos, images embedded inside of them.
1:25:34
What a lot of other people approach it as is uh trying to do OCR parsing on top, but that doesn't work cuz documents are Yeah, PDFs are a nightmare. PDF is a disaster. We know this. It's a disaster.
1:25:46
We've known this for decades.
1:25:47
It's not getting any better. Adobe, clean it up.
1:25:49
What what we do is we edit pages directly as images and retrieve over those.
1:25:55
That is much higher accuracy, much much better performance. Yep. Very cool.
1:25:59
Are you guys going to be able to fix the photos app searching photos? Very.
1:26:03
We have to if Apple gives us a chance. Yeah. Yeah. Give them a shot. Give it a shot.
1:26:07
It does seem like they're trying to do that type of multimodal search on cross of it, but they're just not there yet in terms of like I'll be searching for, you know, a dog jumping on a couch.
1:26:16
I know that I have it in my camera roll, but it's a video and that scene happened later and they haven't indexed it properly.
1:26:22
So, lots of opportunities.
1:26:24
Talk about where people are implementing this.
1:26:26
Is it enterprise private data sets?
1:26:28
Is it public scrape the web?
1:26:28
I want to search everything. Narrow it down for me. Mhm.
1:26:31
It's a little bit of both.
1:26:33
Uh the most adoption is in the legal tech space.
1:26:35
Also in the health tech space, they have like lots of documents with like tables, charts.
1:26:41
Patent drafting for example has like a lot of technical diagrams in there course and and it works really well for those people as well. Okay.
1:26:47
Uh talk to me about the other major players in the space.
1:26:51
We saw Glean yesterday raised what 150 million at 7. 2 billion.
1:26:53
Uh this feels somewhat adjacent.
1:26:56
You're kind of eating off their plate a little bit.
1:26:59
Is that a direct competitor or is there something different where you can play nicely with them? Yeah.
1:27:03
So I mean uh the kind of benefit for us is that we provide APIs and we're much more of a developer tool and the way we see this going is actually not as a competitor to glean but like more of like a provider to glean right and not just glean but to uh people that are building like cursor for x and you need to deal with multimodal documents that's exactly what we can help you with.
1:27:24
So, we're starting with search, but that's not it, right?
1:27:28
One of the things that cursor uh the reason why like tools like cursor and like coding agents have become really good is because code is low entropy, which means you can predict like well into the future what code is going to look like.
1:27:38
Um, one thing that we can do is help you get that low entropy with multimodal information.
1:27:43
And so, like what video editing looks like kind of like three or four steps in the future, if I've like cut a clip and like cut another clip, I kind of know that I'm going to delete the thing in the middle, right?
1:27:52
And so if you can use that and essentially provide that to models as like code uh that ends up like performing a lot better and uh you can start building cursor for video editing and you can start building curs. How did you guys meet?
1:28:07
What were you doing before YC? We're both brothers.
1:28:08
Uh before yeah before YC I was a software engineer at MongoDB. Oh cool.
1:28:13
And this guy dropped out the open source thing tracks dropped out aware. Right. Yes. Exactly. Cornell. Nice. Very cool.
1:28:18
Uh yeah, talk to talk to us about the open source strategy.
1:28:23
How closely are you mimicking MongoDB?
1:28:25
We heard earlier on the show that MongoDB didn't have a managed service, a SAS product until they almost went IPO.
1:28:31
Um are you planning to monetize the open-source uh program earlier?
1:28:36
What is the play between am I using the open source version or am I paying you look like? Yeah, good question.
1:28:42
The way we see it is for people who if it benefits a single community member then we want to open source it.
1:28:50
If it benefits a team then we want to leave it close source. Interesting.
1:28:54
So things like SSO, things like connectors like Google Drive etc.
1:28:58
or maybe like speeding it up for like making queries much faster.
1:29:01
This is all going to fall apart when people start building oneperson billion dollar companies because you're going to be like it all has to be open source because you only have one person. That's true.
1:29:09
That'll be a good problem.
1:29:09
That's a good problem to have. Yeah.
1:29:11
Um but but but uh digging in more into the open source, what's the traction been like?
1:29:17
Do you have a GitHub project that has a lot of stars?
1:29:19
What what do you what are you tracking in terms of roll out? 2600 stars today. Congratulations. That's fantastic. 4,000 monthly downloads. Amazing. Thank you.
1:29:28
And uh 200 active deployments in production. Fantastic. There we go. Here we go.
1:29:35
Audience is uh probably mad at me in the chat for that one, but uh it's amazing. Amazing. Yeah, it's fantastic.
1:29:40
You guys came into YC with this specific idea or did you iterate to it uh throughout?
1:29:44
We came in with a much uh broader idea.
1:29:46
We weren't too focused or indexed on multimodal before.
1:29:51
We were like hey just we want to be the data layer.
1:29:53
What sort of helped us was trying to narrow down on the multimodal aspect seeing how people are building more and just yeah building on from there.
1:30:02
Did you always want to start a company together? Yes.
1:30:06
That's been a dream since we were kids but yeah. Incredible. Incredible.
1:30:08
Uh how's uh how's fundraising going?
1:30:13
Fundraising is going well.
1:30:13
We're kind of close, but uh yeah, looking looking to do it faster. Another one. Well, congratulations.
1:30:20
It's been great chatting with you.
1:30:21
Good luck on the next stage of your journey.
1:30:23
We'll be we'll be following along along.
1:30:25
We're excited to use cursor for video whenever whenever that send them our way.
1:30:28
Yeah, they'll probably build it on top of your company.
1:30:32
So, thank you so much for stopping by. Sounds so much. Thanks for coming on. Bye. Do we have anyone else?
1:30:38
There's a little bit of lunch break going on.
1:30:40
Giving you some inside baseball here at YC Demo Day 2025.
1:30:44
But we have one more team.
1:30:44
They don't need to take lunch breaks. They're owning purple. They're working. They're owning purple.
1:30:51
And and the Pit Vipers have made a return.
1:30:54
I think it's all one pair of Pit Vipers. Recycling.
1:30:56
We know the Pit Viper family.
1:31:00
There's not enough color going on here.
1:31:01
Let's put on some yellow hats as well.
1:31:03
Let's just really get crazy with the the the the fever dream that's going on with the orange, the purple, the yellow. We love clity. What are you guys up to?
1:31:12
What are you guys building?
1:31:13
Uh we're building automatic technical documentation for codebase.
1:31:16
So saving 30% of uh employee time. Okay. Yeah.
1:31:19
Um explain the first customer.
1:31:22
Are you going after larger enterprises?
1:31:24
Are you selling to other YC companies? Yeah.
1:31:26
Uh ideally to enterprises, but we're starting off with series AB onwards companies.
1:31:29
Um majorly because that's when you start onboarding people.
1:31:33
you need internal documentation to actually give like technical specification for your product so on.
1:31:38
So yeah, initial focus is series AP on specifically for companies that are uh delivering APIs that they sell access to.
1:31:45
Not just APIs but any any sort of like right now it's a web application but any sort of application um in theory.
1:31:51
So like API is part of it. Yeah. Yeah.
1:31:53
I I there's a number of open source projects that kind of allow you to uh stand up a boilerplate for open source documentation or or API documentation.
1:32:01
uh how is your product different?
1:32:03
What what what are you hydrating?
1:32:05
Because at a certain point if there's kind of internal sacred knowledge around how an endpoint works, you have to get that from the person that designed it or can you instantiate everything from the code? Yeah, that's the plan.
1:32:15
Like the idea is for us to not depend on one person.
1:32:17
The idea is like uh we actually go across the organization all the code bases and uh understand those like technical specifications from like in the background, right? So there's no different.
1:32:28
How are you dealing with security?
1:32:30
I imagine that if you're going across all the code bases, all of a sudden there's like secrets that could leak.
1:32:34
There's there's internal tooling that they maybe they don't want to have out there in their documentation.
1:32:37
How do you think about that?
1:32:38
So, we make it completely self-hostable, the best part.
1:32:41
So, um especially for an enterprise when they have to be compliant, regulations and so on.
1:32:45
So, we completely make it uh self-hostable.
1:32:47
People can actually just use our product like it's packaged so you can spin it up, put the repositories in and nothing leaves their network.
1:32:53
How did you guys get to YC?
1:32:55
Uh like in terms of the place. Yeah. What's the backtory?
1:33:01
You want to go car plane. What was Yeah.
1:33:03
I mean I mean through plane that was the last time but I've known this guy.
1:33:05
We've been through so many places.
1:33:07
I've known him for about 10 years.
1:33:09
We met in uni hackathons tons of projects. Very cool.
1:33:13
Um and to get to YC just a couple failed applications and here we are now. Always so many.
1:33:17
Everyone has one at least in your belt.
1:33:20
Um how's the traction been?
1:33:22
What what are you sharing today? Yeah.
1:33:24
So in the we launched about two and a half weeks ago.
1:33:26
Uh we already are around 3,000 in revenue. Congratulations.
1:33:31
We have we have about six six seven customers now.
1:33:33
Um so we are Yeah, it's it's going well.
1:33:36
We have we're increasing 30 over 30% week on week actually. There we go. Week on week on week.
1:33:41
Just do that for the next like a thousand weeks. We get to go hopefully. Yeah. 73 days again. Nice.
1:33:48
How's how's fundraising going?
1:33:48
You guys in the midst of it? Yeah.
1:33:50
Uh we're about 40% there. Uh 40 50% there.
1:33:52
So we're getting we're getting close. Um hopefully. Yeah.
1:33:57
Uh what is it just you on the team right now? Do you have anyone else?
1:34:00
Just keeping it that way for a while or you think you'll you'll start really scaling?
1:34:04
We we are thinking of getting people on board.
1:34:08
Um but uh yeah, we want to make it we want to keep it lean.
1:34:10
We're trying to automate documentation.
1:34:12
So you got to automate, right? Yeah. Exactly. You got to live it. That's great.
1:34:16
Uh well, thank you so much for coming on the stream. Awesome day. Thank you so much. We'll talk to you soon. Thank you guys. Bye.
1:34:25
And we are ready for our next guest coming into the Palace of Party Rounds. Welcome to the stream.
1:34:29
Um the the the hum of YC Demo Day has died down as people move across the street to lunch. Good to meet you. How you doing? Nice to meet you. I'm Josh. Nice to meet you. Pleasure. Nice to meet you. How you doing? What's happening? What's happening? Big day. Keeping up.
1:34:45
Yeah, it's a big day for us. Yeah. Uh, how' the pitch go? Smooth.
1:34:49
Uh, we're gonna be in the in the afternoon today. Okay. How are the nerves? How are the nerves?
1:34:54
Uh, honestly, we are used. Yeah. Alumni Day.
1:34:59
They do a good job of kind of like getting you so many reps that it just feels like anything else.
1:35:02
Yeah, honestly, they work you up to it very easily.
1:35:05
Uh, introduce the company.
1:35:05
What are you guys building?
1:35:06
So, I'm Franchesco, the founder of Kua. Aleandro is the CEO.
1:35:10
So, we are building computer use AI agents. Okay.
1:35:13
meaning AI agents that can solve any problems like a human would do in the terms of clicking, typing, scrolling. Okay.
1:35:18
Uh what uh at what layer of the AI stack are you working at?
1:35:25
Are you sitting on top of just like a chromium in instance or are you actually sitting on top of something like a browser base or do you can keep Yeah, we we wrap an entire operating system on a um isolated environment kind of like a docker for us agents. Okay.
1:35:41
And that means that we can uh use system level events for injecting these commands like click type and really any bash or powershell commands. Yeah.
1:35:47
And then and then what's working in computer reuse right now.
1:35:51
Uh there was theory that you just read the HTML at some point.
1:35:54
Now there's more multimodal image generation like actually take a screenshot process that understand where to click. What's working? Yeah.
1:36:01
to click. What's working? Yeah. So screenshot is working uh way better than accessibility tree for uh operating system in general like you don't have any HTML dom to parts really system we just like use screenshot uh screenshot
1:36:18
and pixel based based model for that and it also been proven by research that's working way better than interacting what categories of agents are you guys seeing the most you know having the most excitement around traction I think anytime you're building agentic uh infrastructure. You got to have
1:36:33
You got to have companies that are building great products on on top of you.
1:36:36
That can that can be a challenge.
1:36:39
But I'm sure there's a lot of other companies in the batch that Yeah. Yeah.
1:36:41
So we haven't chased any verticals meaning that you haven't chased any vertical any verticals meaning that we figure out what people want. Yeah. Exactly.
1:36:49
Because like actually we first month in we were getting the most esoteric ask from the users in terms of hey I have this bunch of contractors there are simply three videos on video editing software on Mac OS. Can I use KUA for that? Sure.
1:37:00
And uh like really we couldn't converge to like very common workflows and that's why uh companies our customers are chasing those verticals for us. Okay.
1:37:10
Uh do you see the market fragmenting?
1:37:13
Do you think you will find a vertical and niche down or do you want it all?
1:37:17
Uh honestly we want it all. Okay.
1:37:19
And we're here to then then what is the uh uh what are the uh the key deliverables that you have to uh optimize against?
1:37:28
Is it speed, reliability, price, some sort of combination?
1:37:32
How are you thinking about that?
1:37:33
Like probably for computer use agents, uh we are still like six months um away from the chbt moment.
1:37:41
Maybe for browser use agent that still the moment is today.
1:37:43
So um once we get that level of intelligence for models we need to come prepared with a very good infrastructure to scale this u isolated environment because like our leap of faith is that five years from now most of the um AI agent a multi- aent system we rely on API maybe 80% of the scenarios and the other 20% are going to be based on browser and computer tools.
1:38:08
What were you guys doing before this?
1:38:08
I was working at Microsoft for over five years. Oh cool. Awesome.
1:38:12
Uh myself I was a notion and I built also a few startups in the in the past. So nice. Are you guys Italian? We are Italian. Nice.
1:38:19
When did you come to the US? Uh 3 months ago now. Three months ago for YC. Crazy.
1:38:27
How's it been living up to expectations? Yeah, definitely.
1:38:29
Uh people ask me um Ferrari or Lamborghini? Yeah.
1:38:36
People ask me how is San Francisco now? Is it better?
1:38:38
And I don't have any comparison.
1:38:40
How I was How how old were you when you just when you knew you wanted to do YC?
1:38:45
Was it uh I think it was pretty recently like 3 years ago now. Okay. Yeah.
1:38:49
For for me maybe since I was 16 and I'm 26 now.
1:38:51
So it's been like a long dream for me and no since still like I don't know if it's reality or not but uh living the dream. Living the dream.
1:39:02
Uh what's the go to market been like?
1:39:04
So the go to market right now we've been focusing mostly on start up and scale up because we wanted to prove that that we were on the right path and eventually fail also faster. Yeah.
1:39:10
Uh, but we have an open source framework over 8K stars. 8K stars. Oh, you hit that.
1:39:20
You buried the lady on us. Buried. Please go and start. Yeah. Yeah. Yeah.
1:39:28
Head over to GitHub right now. Give it another star. Yeah. Try. That's amazing. Yeah. Uh, so yeah.
1:39:34
I mean, well, what's the monetization strategy around that open source project?
1:39:38
So we um like first month in YC we were all these customer uh inbound that were basically asking us how do I even productionize on a computer agent today.
1:39:46
So we are providing a pathway for the user from the open source to bring in the same workflow that are working locally for them and scale them on on cloud.
1:39:54
So we're really charging only based on compute today.
1:39:58
Um you simply have to input an API key on our platform.
1:40:00
But what's going to happen also for us we're going to become LM inference provider for these computer UI models because maybe the the public sense is that there are only true computer using models maybe the one from OpenAI and anthropic Y and that's only because they have a better PR office sure than other models uh but honestly like even on a phase you'll find model from Bance 1.
1:40:23
5 that's also out beating openi and anthropic on on computer benchmarks on computer benchmarks like Sure.
1:40:31
Um and uh they are so hard to set up and also hard to discover and also we're going to be the go-to catalog and platform where yeah how good are the eval right now are the benchmarks for computer use it feels more abstract than just you know do some math problems. Yeah.
1:40:47
So I was actually working with the Windows team when I was at Microsoft doing about for agents on a benchmark called Windows arrina which is uh derived from OS word.
1:40:55
really like this benchmark.
1:40:58
Uh they like task are not very meaningful like for you will find task like hey uh can you go and open VC and add subtitles who's using VC anymore?
1:41:08
So that's the question even like using Libra Office instead of like office or even Google Docs. Yeah.
1:41:12
So what's going to happen?
1:41:15
U my my leap of faith here is that the next u generational benchmark will measure like real world task. Yeah.
1:41:22
Do you think there'll be a sort of like LM arena style benchmark where uh a human is watching two computer use models use computers and there's kind of like a vibe check almost? Yeah.
1:41:34
Or even like a wiki race where you have like a wiki race. Yeah. Yeah. No. Okay.
1:41:38
So wiki race is is uh like uh you know you start with Y Combinator and you have to end at Christopher Columbus and how many clicks do you have to click to get from one to the other?
1:41:51
So you might say, "Why YC has San Francisco?
1:41:53
San Francisco is America. America has Columbus."
1:41:55
And and so you you try and race through and and yeah, it's an intelligence test, but it's also Yeah. Great computer use test. That's hilarious. Yeah.
1:42:01
But also, I mean, I I imagine that there could be like a like a big model smell like a vibe check on the computer use because if it looks very jerky and it looks confused, like that's something that might not even come across in a quantitative benchmark, but a qualitative uh human might might evaluate it differently. Yeah. Interesting. Yeah. Yeah.
1:42:18
And also like there's this whole problem. Okay.
1:42:19
I have this workflow that now is working maybe 80% of the time.
1:42:23
How do I make sure that I'm able to reproduce the same kind of uh workflow all over again?
1:42:27
So, we're also working on episodic memory that will let you basically use RPA 1.
1:42:31
will let you basically use RPA 1.0, in all the old fashioned RPA and UI automation for um workflows that are very deterministic and then say that you have a deviation from from one trajectory due to noise or changing on a web page then that's when you use like
1:42:49
full computer use when it really makes sense that makes a ton of sense any other Italian YC founders we haven't met many are you guys hometown heroes back in the the Italian taxi you got to go do the local press in do the press now you're does this in Bulgarian. He's like a
1:43:05
He's like a celebrity over there and over here he's there's a wise ski WhatsApp group now they're raging like this um week on the mountains that that's reason enough alone to apply to white company group chat. Yeah.
1:43:26
Anyway, thank you so much for coming on so much. Let's bring on the next.
1:43:33
Do we have uh who do we have next?
1:43:36
Oh, Delen, we were just talking about you. What's up? How you doing?
1:43:38
Oh, you got the hat on already. Oh my gosh. Let's go, baby. Iron.
1:43:48
I can't believe you hit him with that.
1:43:50
We do that when we hear like big numbers.
1:43:52
They didn't bring the gong. Should I?
1:43:54
Um, so I was a Y comator summer uh 14 company. That's right.
1:43:56
Do you want me to go through my summer 14? Give us the page. Give us a pitch. Uh, so hi everyone.
1:44:03
Uh, my name is Delian Aspero.
1:44:04
I'm the CEO of Night and Gale.
1:44:06
Uh, we build software that helps uh, uh, autism therapists that work with uh, uh, young children to basically help them capture data on those children's behaviors.
1:44:14
Uh, put that into reports that you then send off to your insurance companies to uh, get reimbured.
1:44:17
Today, all this is done by paper and pencil, super manual.
1:44:22
Takes these therapists like 30% of their workday just doing a bunch of bureaucratic actions.
1:44:25
We cut that down, make it super fast.
1:44:27
They get reimbured more quickly.
1:44:28
Um, and they get to spend more time with the kiddos rather than on a bunch of paperwork. Cursor for autism. I was about to say curs. It's cursor for autism.
1:44:34
So, if you ever wonder where all the autism came from, it's because my first company literally all I did was spend time with autistic kids.
1:44:41
And so, you know, I had some in me already. It got amplified.
1:44:45
How did your demo day go?
1:44:45
Did you raise like what was it hard to raise back then?
1:44:48
It feels like everyone here kind of can put together a million dollar seed round.
1:44:50
What was what was like the the comp that you used?
1:44:52
A lot of a lot of YC companies obviously like to give something and roll for dog walking. Yeah.
1:44:57
like summer 14 like you have to remember like at the time it's not like there was a ton of like healthcare SAS things that had worked.
1:45:04
It's like you had like Epic as like an EMR that were obviously done well Epic the story fully. Yeah.
1:45:07
And like we weren't really an EMR.
1:45:09
So honestly I think like you know um I remember like Sam you know at the time cuz he was like the head of YC back then you know two weeks before demo day basically told me like your pitch is trash.
1:45:18
Um and then I went and you know we're going to say this on live stream but um yeah I took some psychedelics on a weekend and like you know really thought about my pitch you know for that weekend.
1:45:27
made a lot of improvements and then Sam afterward told me he was like, you know, relative to where your company's at in like performance.
1:45:32
Phenomenal presentation, but phenomenal presentation in 2014 turned into like 600k seed round.
1:45:36
turned into like 600k seed round. It was a grind to get through like still two months after demo day like you know doing individual calls and it's just like when you look at like the amount of capital that's like you know whatever like the next door building
1:45:48
there was there was like a two somebody said there was like a 2hour wait this morning if you tried to show up like right at the start there was like the line was like two blocks down summer 14 like we like filled up like a small little like area like cocktail area and like the computer history museum down in there. So it's like I if you just if you
1:46:03
So it's like I if you just if you just given 10 grand to like every batch member with you, you would have a billion dollars now, I'm guessing.
1:46:09
Yeah, I think summer 14 did have some hits.
1:46:11
I have to go back and remember who summer 2012. My batch had a ton. Coinbase, Instacart.
1:46:18
Yeah, it was a good batch.
1:46:18
There were a bunch of good ones.
1:46:20
But yeah, it's like interesting to study just like I feel like you can use Demo Day.
1:46:23
This is my first time coming to Demo Day in like I think seven years or something like that. Partially like in 2018.
1:46:27
that. Partially like in 2018. I went spent a bunch of time on it and like honestly just like didn't lead to any investments and so I was like at some point what am I you know sort of doing here then obviously co really killed it off and so um excited to be back but it's also an interesting just like marker of like the like the industries you know sort of maturity of just like
1:46:42
the amount of companies what the companies are working on now also the amount of comps that like you can like look at like in 2014 if you had said like my comp is like I would like to be a hundred billion dollar publicly traded company it's like okay there's like basically two of those in the entire history of technology now you have to come because people are doing Varta for X got there was an Indian Va. So, you
1:46:57
So, you know, got to got to track those guys down and figure out how to like acquire them.
1:47:04
So, we have like a desi va. Yeah.
1:47:07
Uh, have you have you seen any of the hard tech companies yet? Any of the pitches?
1:47:10
Gary said like 11% of the batch is hard tech. Yeah. Yeah.
1:47:13
Yeah, it's interesting to see like I mean I remember in like 2018 19 when I was doing like hard tech, industrials, defense, aerospace, it was just like so uninteresting to so many people like they would all like literally like you know we talked about this like ever at my former colleague.
1:47:26
He's just like oh like if anything is like you know negative gross margins and like highly capex intensive send he like said that as a joke and then now everybody's realizing like actually capex intensivity is like the best mode ever because like if you just build software AI slop can you know replicate it basically overnight.
1:47:40
Um so yeah definitely looked at you know handful of them.
1:47:43
I think it's cool to see that like YC's leaning into this cuz it's not something that they've they had a couple hard runs with like Pebble was a big was a really big like hard go because like they got so Sherlocked by Apple with the Apple Watch yeah what are you going to do?
1:47:56
Uh but at the same time like there's been now like Astronis and Oaklo and like a few really even harder tech companies that have made it through and like scaled.
1:48:05
So Astronis I do think is like the best like Oaklo obviously like you know you know sort of you trading but like you know hard to figure out.
1:48:11
Yeah, hard to figure out but still feels like it's like it's got some, you know, sort of real like 300 ft down.
1:48:17
I admit though, like look, I think like I mean if you look at, you know, the like YC deep tech, you know, sort of portfolio and like hit rate and outcomes relative to like the FF orelian seed deep tech industrial portfolio.
1:48:30
There's definitely one that I would want to buy in the basket of and one that I wouldn't.
1:48:33
And so, you know, I uh I mean, maybe I shouldn't be speaking.
1:48:37
Maybe Gary's going to I I I I think like the bull case is that like like it is great to have exactly what YC is, which is an incubator, an accelerator, like a pool for that type of talent to come out of.
1:48:47
And if you wind up picking over at it at some point, like that's fine and that actually part of the ecosystem.
1:48:52
And yes, like you're going to get earlier stuff, but it's nice that there's at least an ecosystem.
1:48:57
Some of the people that go through YC with hard, they might become employees at these companies.
1:48:59
They might become acquisition or aqua hires.
1:49:01
become acquisition or aqua hires. It opens the Overton window for like the average day for grad to like not just work on How many how many multi-stage VCs have pulled back from from doing de demo day investing at all and just
1:49:13
saying you know we're not going to try to go I mean I feel like in like you know sort of 2019 it was like the consensus thing like at some point like everybody was like why are we doing this it's just like way too many companies
1:49:23
that like you know sort of seed rounds you know feel like and again you know maybe Gary's going to kick me out for this but it's like the seed rounds felt like they were really overpriced and especially as a multi-stage firm it's
1:49:31
like well you can just wait for the series A and like on a risk based it's not like the companies are going to die Oh yeah, there's so many YC specific funds that would come in and just write 100K check into tons of companies. So
1:49:40
So like everyone was getting their rounds done.
1:49:43
But yeah, I mean yeah, it just speaks to like how they're playing.
1:49:47
Also, there's this weird dynamic where YC used to say like I don't know if you got this advice, but it was like don't pitch any investors until YC demo day.
1:49:54
And then everyone was like oh well like the game theory is like if I'm the only one pitching before demo day I should get all the interest I get all the interest.
1:50:00
And so and so like there's still like the I'm sure like you will you will take a pitch with a YC demo day founder a couple weeks earlier because they're inventive and creative and they got to you before. Totally. Totally.
1:50:09
You just might not find them through this.
1:50:11
I do think there's some amount of like a lot of the like you know companies have already closed their rounds by like the time this day happens which was very much so not the case in 2014.
1:50:17
2014 is like oh maybe one company in the entire batch.
1:50:21
And by the way, for what it's worth, like if you study those like early batches, there was basically like an extreme negative correlation between like the ones that like, you know, sort of raised early and that actually ended up being like the like, you know, sort of batch returning, you know, sort of outcomes.
1:50:32
I remember there was one company in YC Summer 12 that had a uh super viral video because they were in the viral video making business and so they got a ton of attention and they'd also like kind of ramped revenue by like saying like, "Yeah, well, we'll produce a video for $100,000."
1:50:45
Like that's not really like like durable, scalable revenue.
1:50:51
Clearly the company that made the $60 million round at before demo day and everyone was like what's going on?
1:50:58
Coinbase sitting there at eight and it's like did you see that? Did you see that ad?
1:51:01
It was a company called Code Tool.
1:51:03
They did like a skit based on the deal rippling thing. No way. Prank on it.
1:51:07
You got to see this video hilarious.
1:51:10
But they they're in this batch. Yeah.
1:51:11
They they they have a they have a service that will monitor Slack chats for Honeypots and create Honeypots for you and do all this different cyber security stuff. It's great.
1:51:19
I mean, it is I think back on like I just had this memory from 2017 when I was at Coastal Ventures where like um you know, Venode would basically have like the junior team go through and like crawl through the entire batch of like everybody like the week beforehand basically on the Sunday night before like the like you know sort of Tuesday demo day.
1:51:33
We would invite like 15 companies to present at KV of uh on Sunday from like noon until like literally midnight we would be there.
1:51:41
Like I remember like letting founders in at 11:30 at night to like come pitch the firm.
1:51:44
And it actually felt like we had this like really deep AR. It was alpha.
1:51:48
Nobody else was doing it etc.
1:51:50
And then literally it's like like you said now there's like these infinite Ebis YC funds where like I actually just feel like the alpha there on like doing the pre-work etc. getting into it.
1:51:57
It's not to say there might not be some good outcomes but like many many more people run that strategy.
1:52:01
And then even the fact that like something like this exists like the idea in 2014 that there'd be like a live show that anybody would give a about and actually want to tune into to talk to us like we could barely get anybody like you know pay attention to any of us let alone the idea that there's like whatever going to be like 15,000 people on Twitter.
1:52:14
So yeah this entire industry has just gotten like you know I mean like this is we we are like the new Wall Street.
1:52:18
It's like kids grow up you know in like 2008 being like I want to be like an investment banker. Yeah.
1:52:23
I just said I I knew I wanted to join YC when I was 16 and he's 26 now.
1:52:28
So he's like decade in the making.
1:52:30
I mean, we talked about this in relation to the like teal fellowship recently where it's like in 2012.
1:52:32
The like off track thing to do was to like drop out, build a company, join an accelerator, work in technology.
1:52:38
Now, this is the track and so we like need to practically find there's a high school dropout in this batch. Yeah. Yeah.
1:52:46
I mean, at this point, I mean, there's an article in Business Insider today by Julia Hornstein who wrote the article about the first article about us talking about how uh like not just not even going to college at all is the new dropping out.
1:52:58
It's like just the default versus like in my year at MIT remember there was like three of us that dropped out apply to college get accepted branding be like MIT accept but that's all you I had a whole riff on this is like yeah Delian you dropped out of MIT I knew that I would drop out if I went
1:53:15
there so I didn't even apply to college and graduate but it's just like yeah yeah you're a sucker for even having gone for a day I didn't even go to you paid the application you paid the application paid a full year of tuition Godamn want those $45,000 back. I could have put that in Nvidia
1:53:30
I could have put that in Nvidia and I'd be a billionaire. Boomer.
1:53:34
Anyway, thank you so much for stopping by. Good to see you boys. We got some big news.
1:53:39
A new investment from you coming onward tomorrow.
1:53:44
Yeah, we'll see you back days.
1:53:46
Welcome to the demo day stream 2025. Good to meet you. How are you doing? I'm John. Nice to meet you, Dave. Dave Munillo.
1:53:54
Is it Did you photograph us out there or was that somebody else?
1:53:56
Oh, I didn't photograph you. What? Who was photographing? Your buddies. Uh, someone else at GV. Han. Okay. He took a picture. Okay. Oh, yeah. We love the paparazzi.
1:54:10
Can you introduce yourself for the stream? Yeah.
1:54:11
So, uh, Dave Municello, Google Ventures.
1:54:12
I'm a managing partner there.
1:54:14
Been there about 13 years, investing in AI and enterprise software from the early days.
1:54:18
Done a ton of stuff here.
1:54:21
I was just standing in a room downstairs hanging with a bunch of folks and uh, Gary came in and said, "Hey, you got to go do this." So, amazing. Thanks for coming on. I'm here. Excited to hang. Yeah.
1:54:29
Uh, what what what trends are you following?
1:54:32
What are you seeing that you like? What's interesting?
1:54:33
Well, first break break YC into chapters for us from your point of view.
1:54:37
I'm sure you've invested in companies at this point, maybe not on right around demo day, but in every I was in Cambridge in the early days in grad school when like Paul Graham and those folks were in Cambridge doing their thing.
1:54:50
And so, at that point in time, YC was like the cool place to be connected to, right?
1:54:54
And I think you know a lot of us I met uh you know partner of mine that now runs our life sciences team and I co-lead our our digital team here at GV.
1:55:03
We met in Cambridge and we used to like get really excited about any Cambridge YC events.
1:55:09
So the place has totally evolved totally right chapters totally uh was fortunate enough to do GitLab in the early days.
1:55:17
So like new Dol from day one and like Sid has always shared his enthusiasm.
1:55:22
Patrick Collison as a portfolio founder comes in and talks to the batch and then we hear the cool stuff from him.
1:55:26
Um, how what was the perception around GitLab at the time?
1:55:32
I I I feel like I remember it and it was kind of like discounted because it was open source and GitHub was already such a such a success.
1:55:37
It was like how are they going to do anything when there's already this winner?
1:55:40
I literally just stepped out before this stepped out to do the earnings call with the you know CEO and the CFO to like do the investor call back because we're public market shareholders of course the company. Oh wow.
1:55:51
Um, so we invested just after the Series B.
1:55:53
We actually passed on the Series B. Oh, no.
1:55:55
And we had a bunch of concerns.
1:55:58
And if I look at those concerns, they were uh Hold the mic a little bit closer. Just angle it.
1:56:01
So they were one of the first companies to be remote only. WordPress and GitLab.
1:56:08
We're like this remote seems strange.
1:56:10
How the hell are they going to run a company like this?
1:56:11
Sid is extremely technical and I think remote only works really well for him because of the way that he shows up as a human, but he writes everything down.
1:56:19
And so um that works for a subset of people in in society.
1:56:27
I mean we talked constantly like like passing out a company is just like it's just like this stage isn't right for us but we want to continue to talk to you over time. Right.
1:56:34
What's your approach to demo day now?
1:56:36
You I'm assuming you don't have a lot of FOMO.
1:56:38
You guys write bigger checks.
1:56:39
We've met something like 30 companies so far.
1:56:41
You are you are writing checks even at this early stage.
1:56:45
We write checks into YC companies. We love YC companies.
1:56:47
love YC companies. So even though we're multi-stage like hundred million dollars into a public company as we were just talking about we also do seed and everything in between A is our sweet spot A's and B's great um we do a like an event a few weeks before demo day every year with all the YC founders and um and then we know all the group partners right so they like constantly
1:57:07
ping us with ideas that's great what what is the integration with Google like now we're entirely separate entire separate yeah so we raise capital from Google our sole LP it's an LP relationship Yeah, because it's such a it's such an interesting dynamic because on the one on the one hand like that could be incredible value ad if it's like hey we'll we'll introduce you can sell into Google. The incredible thing
1:57:25
The incredible thing is we have a stable LP that's there forever permanent capital essentially plenty of capital and an appetite for risk.
1:57:32
So we have a great LP that we have a half an hour conversation with every couple years. Yep.
1:57:35
And and plenty of capital. Wow.
1:57:38
We don't spend any time pontificating about where we think the market is.
1:57:41
That's why I had to call our comms people before I came on here is like we don't we don't usually do, you know, marketing or like like comms events or podcasts or stuff like this.
1:57:49
Excited to talk to you guys, of course.
1:57:50
Um, but yeah, I think we're we're unique in that we spend all of our time with founders. Yeah.
1:57:54
So, I shared the like it's such such a hack.
1:57:56
I mean, I I think you're the envy of every, no matter how successful our GP friends and the GPS on the show, having a dynamic where a hundred people could call you on a Saturday at 5:00 p. m.
1:58:08
and you kind of owe them your time to some degree and that's like that LP, you know, dynamic.
1:58:14
I mean, I talked to obviously tons of friends in uh at the GP level across different firms. It does keep them sharp.
1:58:20
Like they get a lot of pressure from LPS, constant questions, deal flow, connectivity.
1:58:24
I think that's really positive, but we don't have to deal with a lot of that stuff and so we spend time connecting with founders and other GPS. Yeah.
1:58:31
What do you think the nature of those questions usually are?
1:58:33
Is it just like trying to understand markets and trends and how the function?
1:58:36
Yeah, I I I haven't really sat on that one.
1:58:39
I've been to like one or two LPA days for big fun.
1:58:42
What's this transformer thing about?
1:58:45
I didn't want to say it, but I think that's kind of the I've seen the movie, but hilarious.
1:58:51
I I mentioned this idea of like we invested in, you know, GitLab in the early days and then now they're a public company.
1:58:56
Like hedge funds invest in the stock, they call us to ask us for our perspective on the company and they're thinking about like what happens in two weeks and I imagine LPs are like slightly farther out.
1:59:04
It's like 90 days maybe to like you know what's what's happening today? What's hot today?
1:59:08
Are you in the right deals? That sort of things.
1:59:11
Uh our LP doesn't care about any of that stuff, right?
1:59:14
So we don't have that conversation about like what what we're in, what we're not in, etc.
1:59:17
It's like do you have a second generational founders?
1:59:21
Do you have a particular understanding of how the startup landscape is interfacing with the mag seven the big tech companies right now?
1:59:29
We're in interesting time.
1:59:29
The big tech companies they all kind of like went from a 100red billion in market cap to a trillion very easily and it was kind of like it was kind of like the easiest 10x of their entire career you know in kind of some sort of unexpected way.
1:59:41
You would think that would be the hardest one but a lot of them just did it.
1:59:43
Uh at the same time um it feels like there's more opportunity for startups than ever but the big big companies have more resources than ever.
1:59:52
What are you talking to founders now?
1:59:53
I mean specifically around AI we're wondering constantly like is AI going to make incumbents stronger sustaining innovation totally and yet I'm talking to companies that are doing millions of dollars in ARR over two days. That's right. That's right.
2:00:05
And and I think the question for us is you know does each incumbent each big SAS company do they bolt on AI?
2:00:11
Do they aqua hire acquire?
2:00:14
Yeah, we're seeing this with the Windsor 49% every big tech company% investment.
2:00:21
It's a new hot structure.
2:00:21
Yeah, it's the new M&A investment.
2:00:23
I'll take 49 and all your best people.
2:00:27
Yeah, I could do this valuation or double it and you get half.
2:00:32
It's like the same number.
2:00:32
But I think having uh loads of capital right now in in a time when like the seats are shifting in tech is quite interesting.
2:00:40
The Mag 7 might be the Mag 70 in the next 10 years, right? Add a zero to it.
2:00:45
I would like I would like more big tech companies.
2:00:47
We're on the side of big tech and so we we we want there to be as much this is actually little tech.
2:00:52
The 70 little tech we're we're fans of all of it. All of it. Just tech. Yeah. Yeah. Totally.
2:00:59
Um yeah, I I I think this idea that like people want to make people want to say AI is good for big tech or it's an extending innovation, but it can be good for both, right?
2:01:09
It could be so transformative like the internet was good for some big companies that adapted well to it.
2:01:13
It was good for a bunch of completely novel ideas and so we don't have to like pick one and pick a side.
2:01:18
It can be an extending innovation and it can also enable all of this. Yeah.
2:01:22
I I think we're in this exciting place where like the most uh high agency humans in our lives that we're all connected to, they're empowered not just to have like the underlying cloud be present for them, but intelligence be present for them. Yeah.
2:01:36
And so now they're they're building, you know, I met a company out there that was like one person, no engineers, already have tons of revenue.
2:01:42
Like I think they, you know, he he told me he's going to be the first billion dollar company, right?
2:01:46
I always get I always get hung up on that because it's like if you attach if you attach a vanity metric.
2:01:54
It's a van it's a total I mean it'll be amazing when it happens, but a total vanity metric that can like guide you towards bad decisionm but it feels like it might like happen accidentally if it happens.
2:02:04
shouldn't be something that's maybe or the way to do it is extra billion and then lay off every other person but yourself. Yeah. Yeah.
2:02:12
The private equity guys are really going to be the ones that do it.
2:02:13
They're going to be like that's not how we build.
2:02:14
We bought a 1000 person company and we fired everyone except for one person.
2:02:20
There are a few VC companies right now looking at VC firms that are looking at you know the PE rollup like something that has massive distribution. Have you looked at any? We have looked at them.
2:02:28
We have passed on a lot of them.
2:02:28
It's it feels like a PE play where you're trying to like get multiple to change as a result of the industry that you're going after. question.
2:02:35
I just look at it, it's like a lot of the founders that are running that strategy, they just should change the structure and just say like we're going to run a PE playbook here and we're going to be two and 20.
2:02:45
We're going to be two and 20 because it's if you if you can if you can raise 20 million on a 100 for the strategy and keep like a lot of the economics, sure, it's great for the team, but it should probably be like the basically the the comp incentive structure should be look more like private equity. Totally. Totally fair.
2:03:01
You guys are friends with a buddy of mine, Sean Magcguire's been on here a couple times.
2:03:05
Sean introduced me to a founder on Friday night at like 9:00 over text.
2:03:08
And I respond back and the guy's like, "Do you want to meet tonight?" Nice.
2:03:13
Do you want to meet tomorrow morning?
2:03:14
Like I'll I'll come to you.
2:03:16
I live like an hour away. I'll drive to you.
2:03:17
I'm like that that kind of high agency human can be empowered by, you know, an entire set of tools, a whole software suite.
2:03:24
Uh you know, AI AI will be the thing that powers all of these incredible humans that we're sort of meeting today. For sure. Yeah.
2:03:29
Yeah, the thing I'm I I hope we get some more of these companies on.
2:03:33
We've had a lot of developer tool uh uh teams on uh I I think this idea of like business automation is being heavily explored around agents but we were talking with Dylan Patel last week and he says like the the next category besides consumer tech you know with like LLMs like you know chat GBT then you have uh you know codegen as like big revenue categories and like this third category of of of just actual like business automation.
2:04:00
And so like how do you just make the machine work?
2:04:01
And everybody's thinking about it in the concept of like agents which is like kind of a I think like almost a simplistic way to view these things and like what what is the next what is the next iteration of that where it's like actually like an autonomous system that that doesn't have to interact like a regular employee.
2:04:16
It's sort of um so we'll see. Yeah.
2:04:18
I mean we're seeing it across an organization like a Sierra or a Decagon.
2:04:22
Uh you know Harvey is a legal AI company that we're invested in.
2:04:26
There's some medical AI companies.
2:04:29
So like every vertical has AI but it looks a lot like a human.
2:04:31
It's like replacement of a human.
2:04:33
It's replacement of a human.
2:04:34
But how do you replace 20 humans at once?
2:04:36
Whole functional across across cross functionally. Yeah.
2:04:41
Um how do you worry uh when a YC deal that you're looking at gets gets hot? Do you worry?
2:04:45
Do you think it's a Oh, we don't worry at all.
2:04:48
No, you know, but I mean historically, you know, if I think if you do look at the data, a lot of these companies that some of the hotter companies at demo day don't end up, you know, always I mean, we're investing in super hot companies at the A and the B and the the most sought after companies get marked up incredibly, right?
2:05:04
So, it's a sign of the heat is a sign of enthusiasm from great people, opportunity. Totally. Totally.
2:05:12
And so like you you have to if you're if you're choosing to get exposed to that asset class, you have to be willing to pay the prices to enter that asset class and play in that asset class.
2:05:20
Um here the challenge is that you have like three months of data. Yeah.
2:05:25
And so you're talking like the company that grows revenue the fastest in two weeks or 3 months whenever they actually launch is not necessarily the company that's going to grow revenue the fastest over two years, three years.
2:05:34
We've seen that a bunch of times where we invest in a YC company and then after demo day it kind of it kind of chills out a little bit and then it reacelerates.
2:05:41
There's a founder in this batch.
2:05:44
Yeah, totally founder in this batch that raised I think like almost $8 million of uncapped convertible notes, right?
2:05:50
And so it's just like humans dog absolute dog in the incredible founders, incredible team and like I understand why people are are sort of leaning in to working with them.
2:06:02
U but that makes pretty difficult. Yeah. Yeah.
2:06:04
Yeah. you're thinking about that next that next call in a year or two with Google being like you know trying to explain like you know entering a party round on an uncapped note it's it's it's easy to literally has no visibility into but for us the thing that we care about is we want to be your lifelong partner like the thing that we think about for founders is how can we be for that them there for them over every round and into
2:06:30
the future what's your messaging around signal risk because I think there's this like if If you're truly a multi-stage fund, you could do an early round and you could say, you know, we're we're good with our ownership right now and
2:06:40
like we're going to help you raise this round, but we actually like I think this concept of of like signaling risk is like totally possible for you to want to invest in a company today and three years from now. So like just because you
2:06:50
So like just because you don't do the in between rounds or orific conversation I was having when Gary walked up and said, "Hey, talk to these guys."
2:06:56
So, I was talking to uh uh Nirage from General Catalyst. Oh, yeah.
2:06:58
And we were chatting about like do you play when the price gets to an uncomfortable place?
2:07:04
Uh what signal does that send?
2:07:06
Like you're you're essentially sending a signal to the market that your firm is excited about this company.
2:07:09
They have a separate seed program.
2:07:11
Um so they can kind of categorize this as like this is a seed bet.
2:07:15
We're going to put a million dollars in this company. We'll see how it goes.
2:07:17
We don't have a separate seed program.
2:07:18
When we do an early stage bet, we we use similar criteria to what we use in the A.
2:07:23
Obviously they don't yet have a metrics but the question is like if they had a metrics would we lead the A in this company so there is a big signal when we do it so it makes it harder for us to do like 30 or 40 companies we've talked to 30 or 40 we might do a handful. Yeah makes sense. Very cool.
2:07:39
Well thank you so much for having great take care.
2:07:42
Good to meet and uh we are ready for our next team or individual or investor or yapper. Who will it be? Who?
2:07:52
We will be surprised because we are at YC demo day 2025. Welcome to the stream. How are you doing? Good to see you.
2:07:57
You already have the hat. Hi. Hi. How you doing?
2:07:59
We're looking around for the camera. You're on live.
2:08:02
You're on a live stream here.
2:08:04
You'll need to wear this hat. Okay. You can wear your hat.
2:08:06
You don't need to wear the hat. Whatever. Whatever. Yeah. Don't wear the hat. I'm John. John, what's up? Andrew Jordy. How are you guys? Uh, introduce yourself. Hi.
2:08:13
Um, my name's Andrew Lee.
2:08:15
I'm a partner at Andre Horowitz. Fantastic.
2:08:17
Um, both working in the games fund and also at A16Z speedrun. Very cool.
2:08:20
Are there any games companies here today?
2:08:23
Uh, there are no games companies here, which is somewhat sad.
2:08:26
Suck them all into speed. This is your fault. This is your fault.
2:08:31
There's about four or five.
2:08:34
I would say for for YC, there's about four or five consumer companies, which is pretty good.
2:08:37
So, you can look at those. Oh, for sure. For sure.
2:08:38
Four or five in the whole batch.
2:08:40
I mean, there's like five or sixish.
2:08:41
Uh, but here's here's the good thing.
2:08:44
I mean, like there were a couple companies who previously in the past were like B2B companies.
2:08:47
They're like, you know what? This is really boring. I don't want to do this.
2:08:51
and a number of them like ended up in gaming and they ended up in entertainment. So, that was exciting.
2:08:55
Uh, and then also, I just generally think that like if you're going to build something that's that, you know, your mom or your your your 17-year-old DGEN friend is going to go ahead and play, then yeah, you know, it makes sense for them to go ahead and build B2B stuff as well. Yeah.
2:09:08
Uh, I want to talk about the games fund.
2:09:10
I I've been super interested in how hard it is to uh get into the hot games because they kind of blow up out of out of nowhere like Yeah.
2:09:16
You're you're like getting on a plane to Sweden and you're like it's more like investing.
2:09:22
By the time you get there, they've doubled ARR. Yeah. Yeah.
2:09:23
Like like there was this Batro game that was like a massive uh thing. There was uh Among Us. Was that the one? Yeah. Among Us.
2:09:32
I mean, that was probably one of the top ones ever played during co during co like these kind of like flash of the pan games that become very viral, but I I don't understand if they're like necessarily good businesses.
2:09:39
So like how are you thinking about finding great games or games related companies or even just consumer companies?
2:09:46
like what are you looking for?
2:09:48
Because the signal seems so much more noisy than in if there's noise around a like an enterprise dev tool company.
2:09:54
Like they're probably selling that and it's probably going to be pretty sticky.
2:09:58
Whereas like Bellatro, I don't know if it seems like local funk I think his name is.
2:10:02
Fantastic developer, but who knows if that's like a going to turn into like Activision.
2:10:06
I think fundamentally for us the way that we tend to think about it is there's there's like a couple different things that to care about.
2:10:11
One is that if there's a large audience that has a bunch of folks that are going to play, that if you do one innovation in that audience, that makes sense.
2:10:18
For example, big fans of League of Legends, if you're all out there, if you're trying to create like a MOA, that sort of makes sense.
2:10:23
But I I think that for us, honestly, the big wave we see is in the world of AI, right?
2:10:27
Whether it's like changes in 3D animation, we fundamentally think that the future of entertainment is actually going to be there's going to be an AI Pixar.
2:10:33
Mark my words, someone's going to make an AI Pixar.
2:10:36
It may not actually even be Pixar, right?
2:10:38
Because usually what happens is we tend to think that like an incumbent for example like you know Disney or something like that exactly is is gonna make like the next thing or or potentially take the next wave but I don't know if you guys seen any of these VO videos. Oh incredible.
2:10:50
I mean the Bible bros the whatever like like Stormtroopers vlogging all over the place.
2:10:56
I'm like it's astounding and it's and I don't think that's something that could ever occur.
2:11:00
There's like a sort of innovator's dilemma that's occurring with the existing folks.
2:11:03
So, even just from like a PR pressure, like I don't know if you saw that that show, The Studio, there's this whole sequence where they're very worried about the casting for this new Kool-Aid movie and then it is revealed that no one cares about the casting.
2:11:15
All they care is that they used AI a little bit and it's this really hot button issue.
2:11:18
This massive PR backlash and so that's this counterpositioning where if you come to the market, you say like, "Yeah, we're we're an AI Pixar.
2:11:24
We're just making AI stuff."
2:11:27
You you don't have the expectation.
2:11:28
People expect Pixar not to use that. That's right.
2:11:30
How how are you thinking about investing at the at the game layer versus kind of the infrastructure layer?
2:11:35
It feels like there's a bunch of feels like there's a bunch of new tooling around just creating these generative worlds that could turn into games and is the is the roadblocks of AI roadblocks or is it something you know new?
2:11:45
Yeah, it's interesting because I think the thing is what we've seen is well we go where the founders go and it seems the number one area that the founders are going is into more tooling and primarily using AI.
2:11:53
I mean, there was a bunch of stuff.
2:11:56
There's still a ton of, I think, experiments happening in the web 3 layer, potentially in the content layer, but the main problem is honestly is that distribution stuff.
2:12:03
I don't know if you guys are like invest in any consumer companies lately, but it's hard.
2:12:05
It's hard because um there's a reason why every DDC company has basically had all their margin eaten by by all the big tech companies, right?
2:12:12
Um and fundamentally, I think that's the same problem.
2:12:15
And Steam, which is like usually like the platform for folks who want to build games, is not nearly as liquid as it possibly could be.
2:12:20
Um, so as a result, I think the thing is the one thing I I think we've seen that's a very positive out there for liquid as in there's not enough demand coming from Steam itself or or really that like your ability to get more bang for buck, right?
2:12:34
Like that it's fast enough that you don't have to pay a huge amount of marketing spend.
2:12:38
It's it's gotten a lot tougher and you have to be very good at it.
2:12:41
it. So there's great teams that are able there's a lot of gaming going on on there too with like wishlisting driving early sales and so you're paying people to wishlist your product and it's like there's kind of schemes on top of schemes right and the thing is like I think we could we could do it I mean
2:12:54
like there's definitely people who do that but it just seems that if you create a 10x product that is able to grab some great cut consumers out there that seems to be something that has natural growth I mean I'm sure we're all familiar with midjourney um that was built it's built on Discord still in Discord. It's not as if it was
2:13:11
It's not as if it was something that naturally would have grown.
2:13:14
So the thing is I think the the and obviously I'm talking about VO because that's like my latest thing that I'm just doom scrolling on every single night.
2:13:21
But um when you can basically grow from zero to all of a sudden 120,000 followers with four videos over the course of like 2 days that's an astounding thing, right?
2:13:29
And if someone can is able to do that, that shows me that there's like a natural consumer poll and that's the thing that's pretty interesting. So mark my words.
2:13:35
I still think that there will be an AI Pixar.
2:13:38
also think that fundamentally the world of AI, tech, and entertainment are going to converge and we're going to basically see somebody create that 10x product that then hopefully just basically skips all the distribution problems. Sure.
2:13:49
But I don't know who am I.
2:13:52
Are you are you seeing are you seeing enough are you seeing enough weird stuff, right?
2:13:55
like there's this concept of like you know kind of uh trying to leverage AI and the sort of existing paradigm but when you think about the intersection of like tech and AI and entertainment and and sort of like uh you know I can just imagine like entirely new ways of playing games.
2:14:13
you already have kind of seen this on some of these um you know people basically creating games within games, but but are people being are people being uh like is the average pitch you know really trying to rethink things from from the ground up or is it hey we have a we think we can build the next Candy Crush?
2:14:28
Yeah, I think a lot of well for us as a fund we'd want to obviously have people who are going to be willing to build the next Unicorn company but that doesn't mean that I think great developers out there won't create amazing experiences.
2:14:38
I definitely agree with you that you have to basically aim for the weird like you have to do things that are basically in the frontier of what's possible because otherwise then what you're doing is um you're you're mo most likely just like basically doing a me too which is then hard because in a distribution channel where you have to basically pay for your c customer acquisition that's like super hard.
2:14:56
hard. I think something that that's m also pretty interesting that I was telling some folks about was that um the the one thing that's interesting about both consumer experiences and games is that if there's a limitation take for example on let's say that like you can only network 20 people on a server
2:15:10
together right well the way you do that then is you just make it so your game has 20 people playing all at the same time and there's thing called Fortnite and then 20 people have to kill each other all and then eventually ends up with only 20 that you'll be able to go network with each other. So the good
2:15:21
So the good thing is you can just basically change it's not like a bug, it's actually a feature.
2:15:25
Um that's kind of interesting.
2:15:27
Um but I I think also generally what we're seeing in AI though is when it's uh you guys are probably familiar with this which is the the sort of cycle between B2B to the to the app side which is basically you have B2B infrastructure that allows you take for example to
2:15:40
create really powerful video models that then allows you to have apps that use those video models and then create content that create new network models for example and then that leads into other things happening with the infra layer. We're seeing a lot of that
2:15:49
We're seeing a lot of that happen.
2:15:51
Unreal Engine was a B2B play birth Fortnite.
2:15:54
Uh and then there's another company in the Andre portfolio that does kind of like uh world scale sharding so that you can like basically build like a big MMO that you can walk through.
2:16:05
I forget what this company is, but they were doing like some scientific computing and some economic analysis. It was years ago.
2:16:10
Uh but there's obviously a lot of work done on the infrastructure layer.
2:16:14
And are they going to be the one to build the the the next great consumer game? Maybe, maybe not.
2:16:18
Maybe it built maybe it's built on top of their platform.
2:16:21
What what are you seeing in VR? Oh yeah. Uh in VR let's see here.
2:16:22
So um we have there is one great company that came through um before from from uh speedrun in the past and the very around the first one was this company called TR games. Okay.
2:16:33
So um you know it's it's one of those things where basically um I think just like people grew up in the mobile generation, you need to have people who grew up in the VR generation.
2:16:41
So if you talk to anybody who's under the age of like 16, most of them will be like I play a lot of VR and it's it's crazy.
2:16:48
VR team that was like a bunch of teenagers who like they won a bunch of Apple awards and then they're just like look we just spent all our time in VR.
2:16:58
So they built a a game that basically um uh is taking one of the bigger ones uh attacking one of the bigger ones which is Gorilla Tag.
2:17:05
They made a game um uh that is is astounding.
2:17:08
Uh their their their most recent game actually uh um it's called YEPS.
2:17:13
Um, Yeps actually has, you know, I I I can't describe it because I'm too old.
2:17:17
Um, but basically it's like, you know, we're all in a world together and we get to go and do stuff together.
2:17:22
Um, but then we all collect yeeps.
2:17:23
We yep at each other and it's like we'reing.
2:17:26
Yeah, we're all the all the shout out to all the ees out there.
2:17:29
We're but but they're doing great because the thing is I think ultimately it's not just a hangout spot for a lot of these kids, but it is ultimately taking advantage of you know what VR and the the general install base.
2:17:39
I think I still think that like VR still needs like a shot to the arm in terms of, you know, we all know this that it probably needs more installs.
2:17:46
It probably needs find a way there, but it it it needs like uh higher lower churn relative to the device sales. That's right. That's right.
2:17:54
Or or the device sales have to be way less expensive. Yeah.
2:17:56
Um or find a way to, you know, just get as good of sales as the Meta Rayban glasses potentially. Right.
2:18:01
We need VR games that are truly addicting, not just novel. Yeah. Yeah.
2:18:05
I was really hoping for the first you probably shouldn't.
2:18:08
I mean I I I remember I remember I like ees though and the kids love it too with uh with the original like PlayStation like Metal Gear Solid that game was like a 100 hours or like Final Fantasy 7 that was a 100 hour experience GTA 4 that was like a 100 hour experience and and I've played a lot of VR games have yet to find one that it's like okay the progression in this game is so addicting that I need to keep putting it on to play.
2:18:32
It's like it's like more like okay it's a cool demo I said a high score okay I'm done.
2:18:36
I'm not like I need to finish this.
2:18:37
I need to know where the story goes.
2:18:39
And and it's hard because it's very expensive investment.
2:18:41
I mean, I think that's why it's easier honestly if you're going to innovate in the world of entertainment to innovate on that B2B layer, right?
2:18:47
Which is where we're seeing it.
2:18:48
We're seeing a bunch of AI sort of video creation tools.
2:18:49
We had one company um Hedra who who came through who was honestly just astounding when the Studio Ghibli sort of content started exploding.
2:18:57
Um people were like, well, how can I animate the Studio Jibly content?
2:19:00
And then everyone was using Hedra as as a result. Yeah, I saw that.
2:19:04
Your partner doing that as well.
2:19:04
Can we have a can we have a studio?
2:19:06
So the magic of Studio Gibli was that it could oneshot these beautiful outputs and and are has there been are you anticipating that kind of moment for sort of ephemeral gaming where I could like take a picture of the three of us and say like make a boxing game where we can like fight and you get swords and then it's like it creates that and it's like fun and viral.
2:19:28
Uh can that happen in the near like are you expecting that at all? Well, never say never.
2:19:33
I think that ultimately um we have to get past this sort of distribution problem, but my hope is that it gets a midjourney mo moment like we've had in the past.
2:19:41
moment like we've had in the past. And the good thing is I mean I've talked to a lot of investors about this that I think a lot of folks are in that cycle right between B2B back to the sort of like app layer is a bunch of the
2:19:52
investors are pretty interested in obviously the B2B AI side and I think that will then drive a lot of innovation which then gets you to 10x here and hopefully if someone builds a good network then you have sort of like unwarranted or really sort of um uh differentiated uh customer acquisition. That makes a ton of sense. Well, thank
2:20:06
That makes a ton of sense.
2:20:06
Well, thank you so much for joining. This was fantastic.
2:20:09
You guys come on when there's big game names. Games correspondent.
2:20:11
I'm going to take this hat. Enjoy it. All right. See you guys.
2:20:15
Let's bring in the next the next person. This guy 2025. Eat data. Make chunks. Make chunks. Welcome to the stream. I'm John. Nice to meet you. Nice to meet you, John.
2:20:27
Can you introduce yourself? My name is Trey.
2:20:28
I am the co-founder of Chunky. Chunky. Chunky. Chunky.
2:20:30
That's the name of the company. Yes. What do you do?
2:20:34
We take really complex documents.
2:20:36
We split them up into meaningful pieces such that one piece is one idea and then we send your LLM only the data it needs to answer questions.
2:20:43
Give me an example of a really complicated document. Financial reports. You've got graphs.
2:20:46
You've got actual text data paragraphs. You've got tables.
2:20:50
And if you're asking are so annoying because there's like so much boiler plate.
2:20:52
You need to just skip to the right thing. Exactly. Yes. Exactly.
2:20:53
And like most of the time when you're asking questions to an LLM, you really only need one table or maybe you need a summary. That's it.
2:21:00
summary. That's it. Why don't I just throw all of that in a big context window Gemini 1 million tokens or something and then just ask it what's it'll work with like maybe one PDF but you have a whole database of PDFs you got like 100page PDFs thousands of those tous thousands of those you got
2:21:14
schematics which are really complex models get confused we actually ran this eval yesterday after the price drop on 03 which is we took relatively simple documents we took classic literature you know David Copperfield L everything like that and we gave that to 03 we asked very pointed questions 03 got a retrieval accuracy of 75%. Great. We Great.
2:21:31
We chunk the data through chunky.
2:21:34
Then we asked 03 the same thing. Always 100%. Always chunk.
2:21:40
This is my favorite name since last YC batch which was a company called Pig. Yeah.
2:21:45
You I'm setting a trend here.
2:21:45
You just like large animals.
2:21:47
I mean it's just so it's just it's going to stick.
2:21:51
We're going to we're going to be talking about this next demo day.
2:21:52
I'm talking about the pipeline.
2:21:53
I'm I have a bunch of huge PDFs on S3 or something.
2:21:55
I feed it into your uh to your system.
2:21:58
Am I getting uh a Postgress table?
2:22:01
Am I getting a MongoDB like unstructured uh am I getting embeddings waiting?
2:22:07
So it's like a vector database. Yeah.
2:22:08
So you get embeddings out there.
2:22:10
You can put it on your own vector database or we can also wrap around your vector database.
2:22:13
That's totally up to you.
2:22:14
It's really developer friendly.
2:22:16
The idea is to just make a dev tool that people just enjoy using and they can have it be two lines of code, five lines of code, whatever it is.
2:22:21
So what's actually happening with it's not open source, right? It is open source. It is open source.
2:22:25
We have an open strategy and so we are uh we are like open source first.
2:22:30
We started as a side project on the open source and we love the open source.
2:22:32
So so is this something that I should be running like in like an ingest process as I'm generating new large documents.
2:22:40
I'm chunking them and then loading them into my vector database which I'm maybe also hosting on an async chunk.
2:22:45
But if you're building a codegen tool then you want a live chunk. A live chunk. Yeah. Okay.
2:22:49
And so if you're doing like codegen on the fly or if you're like you know things if you're working with a corpus that's changing all the time then you do want to you want to do it live.
2:22:57
You come in you came into YC with this idea.
2:22:59
You're already had it as an open source project. Yes. Yes.
2:23:03
We had an open source project all set up in like February and we came into YC with this idea.
2:23:07
How many people on the scene?
2:23:09
It's just me and my friend from seventh grade just so many.
2:23:14
boys group made it out of the group chat and then we're not chunky made it out of the How many chunks have you chunked?
2:23:21
How many stars do you have on GitHub?
2:23:23
How much revenue you making?
2:23:24
What do you what do you got for us in the quantitative metric side?
2:23:25
So the metrics I really like are we've got over 180,000 downloads and we've got over 200 projects using us.
2:23:32
We're core dependency on projects like Llama Index. Oh, cool.
2:23:36
Um and we've got like 10 to 12 batch companies using us.
2:23:40
Good inbound coming in from there on. Fantastic. Brown's already done. What was that? Round is almost done.
2:23:46
We're trying to wrap it up this week. Preliminary. Yes.
2:23:50
Just just weighing our options and just like making sure by Friday it'll be done. Fantastic. Amazing.
2:23:56
Well, good luck out there. Well, thank you so much. Thank you for having me. Never stop trunking. Never stop chunking. We'll be following.
2:24:03
What's the What's the domain? C H O N K I E. ai.
2:24:06
And if you want this merch, it's shop. chy. ai. He's selling merch. He's selling merch. Let's bring in the next.
2:24:12
Great to meet you the next participant of the demo day stream if we have one.
2:24:15
Welcome to demo day 2025.
2:24:18
We are live from Y Combinator in San Francisco. Great to meet you. Nice to meet you. I'm John. Nice to meet you. Hi, I'm John. Nice to meet you. What's going on?
2:24:29
Can you introduce yourselves? Yeah, I'm Cinnamon.
2:24:30
I'm a mechanical engineer by background.
2:24:32
Uh built hardware for Apple, Google, Slack. Uh Wow.
2:24:37
Hardware hardware hardware for Slack. Yeah. What do we have? RFXway. Oh, sorry.
2:24:43
The Stanford linear accelerator center. Oh, that not SLK.
2:24:48
Okay, that makes more sense.
2:24:48
I was like, what what what hardware device did I clarify? Cool. Awesome. So, I'm Abujet.
2:24:55
Uh, I worked as a researcher at Stanford, a researcher at Harvard.
2:24:57
I was like an intern at Intel. Um, cool.
2:24:59
Built a lot of stuff, I guess.
2:25:01
Can you uh pull up on the mic a little bit more?
2:25:03
Uh, and then tell us what your company does. Yeah, so we're Godella.
2:25:06
We're building a frontier physics model for mechanical engineers. Okay.
2:25:10
So currently AI models can't handle physics accurately because a lot of them are language based. Yes, ours are different.
2:25:16
Ours are built to handle physics accurately.
2:25:17
Okay, which means it can be used as a faster cheaper replacement to simulations and physical prototypes.
2:25:23
Okay, how this is something that I think a lot of labs like to to promise, right?
2:25:27
Solving, you know, they like to bring up Yeah, they bring up this idea of of solving these problems in future. So So walk me through.
2:25:33
It sounds like you're actually training a model.
2:25:36
Is it all uh reinforcement learning with verifiable rewards or are you generating a whole bunch of training data?
2:25:42
Is there a human data labeling component like what is the pipeline to create what you're creating?
2:25:47
So at a core we extract embedded physics from data and that makes it generalizable. Okay.
2:25:52
Did you want to share more? Yeah.
2:25:54
So we don't use reinforcement learning or anything.
2:25:56
It's basically like this sort of like you know encoding framework like where we actually like take the mesh itself like we work with meshes right because we're like in simulation and stuff.
2:26:03
So we take the fluid mesh and then we like encode into like this low dimensional space and that allows to like learn the actual physics of the system. Interesting.
2:26:10
And this allows and when you do like symbolic regression on like the laten space you get like a lot of you know like you get a lot more generalizability than you would get with like regular models.
2:26:18
So yeah when did you guys start working on this?
2:26:21
Did you bring it into YC or did you pivot to this at some point? We brought it into YC.
2:26:25
So we were teeing a computational mechanics class together at Sanford which was teaching undergrads in mechanical engineering how to use the traditional simulation software kind of bred a hatred for those softwares.
2:26:36
Meanwhile Abid's doing insane research at Stanford to use ML to model the physical world in these crazy accurate ways.
2:26:42
He's like building ML models for Intel that are replacing months of trial and error in their plasma edge process.
2:26:49
And I realized like hey there's this huge opportunity to out with the old out with these old simulators.
2:26:53
Let's bring physics informed to the broader group of engineers who could really benefit from these faster, cheaper answers. Okay.
2:27:03
CFD, computational fluid dynamics.
2:27:03
I have a I have an engine and I'm trying to simulate how the air will flow over the jet that I'm building.
2:27:09
Is that an example that we could use to kind of build off of?
2:27:12
Is it just is it just faster inference than calculating everything uh deterministically? Is that the goal? Absolutely.
2:27:19
Like all of simulation, every time you start with a simulation tool, the engineer started with a question, right?
2:27:24
You've got a question in your 3D model.
2:27:25
You want to know how is what is the drag on my Yeah, exactly.
2:27:30
How's that going to change as I change thickness or angle of attack of my air foil?
2:27:33
Now, imagine instead of needing to learn a simulation software, you can ask with natural language, drop in your CAD, and get simulation quality results instantly.
2:27:41
When we say instantly, it's 4,500 times faster than a benchmarked uh GPU accelerated solver that we tested against. Wow. Wow. Wow. Okay. Very cool.
2:27:49
What's the go to market like?
2:27:51
I mean, I imagine you're selling to like very large aerospace defense companies or who else is building stuff?
2:27:57
I mean, Apple, Google, the these companies could buy this. Yeah, exactly.
2:28:00
I think the huge benefit of physics informed ML is we can tackle problems that traditional simulators cannot tackle.
2:28:07
Multi-ysics, multi scale, make it extremely feasible to tackle those problems.
2:28:10
And we can also fill in the gaps where your idealized equations don't suffice to capture the complexity of the problem.
2:28:15
So these problems that Apple, Google, maybe aerospace are throwing millions at in terms of R&D and building and testing, we can give you accurate physics models that can replace your need to physically build and test a product.
2:28:27
So and they can probably like reality check your faster results with the traditional uh system that they have in place whenever they need to. Yeah.
2:28:35
Build that confidence run that overnight instead of while while you're designing traction selling it. So far it's been great.
2:28:42
So we launched two weeks ago.
2:28:42
So we entered a 25k year contract with an engineering firm to replace ANCIS which is $30 billion incumbent.
2:28:48
is $30 billion incumbent. Um however I think our stronger pull right now is we have some exciting opportunities with enterprise customers to again tackle those highest value problems where you don't there is no solution for for modeling something like drop simulation right like there is no great simulator that gives you that fast accurate
2:29:04
answers even though it's you know governed by software gets like 70% accuracy or something yeah interesting it's also very slow though it's like 2 weeks to compute a drop simulation on a 14-inch MacBook Pro today so like these really high value problems for enterprise customers we have the opportunity to go apply our software and they'll give give them more accurate answers. Very cool. How big is the team? Very cool. How big is the team?
2:29:24
Where are you going next?
2:29:24
How's the fund raise going?
2:29:25
Yeah, it's three core, one advisor.
2:29:27
Uh the fundrais is going well.
2:29:30
We're just about Well, it's very exciting. We're just uh Yeah. Yeah. Yeah. Amazing.
2:29:34
Whoever whoever's like, you know, bidding, I'm sure they're, you know, going to watch this.
2:29:38
So, congratulations on a fantastic demo day.
2:29:41
We've been giving out hats to folks who come on the stream. Thank you so much. Great to meet you guys. Congratulations.
2:29:47
We will talk to you soon.
2:29:47
Yeah, let's bring in the next team or whoever it is.
2:29:51
And don't forget to go to vanta. com, addio. com, numeralhq. com, adquick. com, aidsleep. com, wand. Go to every website. Look at the bottom bar. What's going on, guys? Hey, how you doing? Dan, what's happening?
2:30:07
Good to have you on the stream. Nice to meet you. Welcome to the show.
2:30:10
Uh, can you introduce your yourself for the stream? Uh, I'm Linus. Linus. Pleasure. It is a pleasure.
2:30:14
Is that you want me to go into any more detail? Uh, sure. Let's get Justin's name. My name is Justin.
2:30:20
And what are you guys building? We're building Dan. Okay. What is Den?
2:30:23
Dan is cursor for knowledge workers. Break it down.
2:30:25
We're an AI native Slack replacement.
2:30:27
Um, if you if you load up the app, you'll see a bunch of AI agents and Slack replacement. Slack replacement. Okay.
2:30:34
So, I I'm not in Slack at all.
2:30:34
I'm just in Den when I'm doing knowledge work. Okay.
2:30:37
Uh, what is the typical knowledge worker like experience with Slack?
2:30:41
Because I feel like there's a lot of just like managerial overhead status updates that are going on.
2:30:44
This sounds like something a little bit more mature than that.
2:30:48
What What am I doing in Den?
2:30:50
In Slack, there's a lot of kind of lost threads, a lot of like kind of lost information um and just a lot of communication ultimately, but no actions.
2:30:58
With Den, we're all about actions and we work backwards from um you know what what you need to get the task done. So, give me an example. Yeah.
2:31:06
So, I guess in Slack, you would be asking uh you know, your coworker for how many how many users signed up last month.
2:31:12
Um that's going to be like an async process where like literally just happened in the Slack.
2:31:15
I was in one of my Slacks I'm in was like, "Are we reviewing last week's numbers or the week before or the week before was a developer on a team talking to the CEO?" Yeah, for sure.
2:31:24
Um, you know, in in Slack, that task might just get lost in the background.
2:31:28
You don't know who like what the status is in Den and AI agents just going to pick that up.
2:31:32
Um, so, you know, we're all about like that multiplayer aspect.
2:31:35
Um, your inputs are building the agents and kind of configuring your tools and configuring the tasks.
2:31:40
Um and then we kind of provide like the multiplayer environment where you might be orchestrating like thousands of AI agents.
2:31:46
Um yeah, talk about uh the path of AI agents, long running agents.
2:31:51
We have this idea of like 10-minute AGI, 20-minute AGI.
2:31:53
03 Pro seems to work for 13 minutes every time you kick something off.
2:31:57
Uh are you putting these things on cron jobs?
2:31:59
Is there is there some sort of like long running process that can run through my den installation and say, "Hey, like every single hour I want you to check on things that aren't getting done." Pretty much.
2:32:11
We break it down into three things like you've got your ad hoc tasks. You've got your Yeah.
2:32:15
Crunch job task, your scheduled tasks, and then you also have things that kind of respond to triggers.
2:32:20
It's like, "Oh, hey, run this task whenever I receive an email." Got it. Okay.
2:32:23
Uh there there was this idea I think it was in AI 2027 around the idea that like an AI would just spin up a Slack instance and use that to AI would use Slack to coordinate with each other and and I can see a world where that makes sense.
2:32:36
What was the catalyst for you guys to realize that you you needed to kind of rethink the communication stack from the ground up to serve agents over you know first and foremost over over humans.
2:32:47
I guess what we realized was that there's tools like Zapier, tool like tools like relevance AI, but they're external to your communication source.
2:32:54
Knowledge workers spend more than 80% of their time in Slack and Notion.
2:32:57
And so we wanted to bring the agents to where people actually did the work.
2:33:00
And the most important thing is now the agents can escalate tasks to like the CEO, the head of customer success, whereas they couldn't before because they were siloed.
2:33:07
So we had to build it from the ground up for agents in that way.
2:33:10
Do you think we'll still call uh ourselves knowledge workers in 10 years if knowledge is instantly accessible by all machines? Taste workers.
2:33:18
There will be taste workers and agent when agency workers cuz knowledge is commoditized now and intelligence is too cheap to meter. Like taste curators. Yeah, exactly. Taste makers.
2:33:26
That's the only job that will remain in the future maybe. Who knows?
2:33:29
How how um you guys are creating a platform that other agents can work on top of?
2:33:37
How do you rank how do you rank the quality of different agents across categories?
2:33:40
Obviously, there's like coding agents.
2:33:42
We're friends with the the cognition team um and and and the factory AI team and things like that.
2:33:47
So coding agents are great.
2:33:49
Uh I I haven't heard a lot of people saying like I love my AI BDR yet, right?
2:33:53
Maybe there's some use cases, maybe they don't want to talk about it, but like what are the categories that you guys are most excited about?
2:34:00
Yeah, deep research is obviously another another category, but um I think it's going to slowly move down like the stack.
2:34:07
I spoke with Shelto Douglas who is a researcher at an recently.
2:34:11
Um, we have great like coding agents and kind of math agents because researchers like math and coding. Interesting.
2:34:17
But, you know, it's not just a verifiable reward thing. It's that as well. It's that as well.
2:34:23
Um, I think we're kind of building in the infrastructure that's going to allow those like iterations to happen where you do actually get like a really good BDR agent.
2:34:31
Um, we're already building like customer success agents that haven't existed before.
2:34:35
Um, because we're providing like the primitives and the building blocks.
2:34:38
Um, and I think the verifiability will come. It's just interesting. How's the traction been? What's the roll out? What's the go to market?
2:34:46
Go to market is handing out 500 business cards to everyone at demo day.
2:34:51
So, so you want every company here, all the small startups, the the early stage companies.
2:34:54
That feels easier than ripping out some massive Slack installation. Right. Exactly.
2:34:57
We take a lot of inspiration.
2:34:59
Start with Den, stay with Den forever. Got it. Exactly. Okay. Seat based pricing. Yes. Interesting. Agent based pricing. Yeah.
2:35:06
Do the agents have to pay?
2:35:07
What about the thousands? Okay.
2:35:09
So, the one person company, you're you're cooked. Exactly. Good luck, though. You'll figure it out.
2:35:13
I'm sure I'm sure it'll be fine.
2:35:17
Have you shared any numbers before this? Yeah. Yeah.
2:35:19
I previously started a company when I was 19.
2:35:21
We grew like zero to 5 million AR 50 people series A. Congratulations. Thank you.
2:35:26
No, started this 3 months ago now. So, it's been awesome. Awesome. Very cool.
2:35:29
3 months right before I see. There you go. Exactly. What were you doing? Yeah.
2:35:33
I mean, Lionus is a beast.
2:35:35
He hired me actually at his previous startup.
2:35:37
So I was able to kind of go from like that 500,000 AR to 5 million.
2:35:40
Um and we just loved working together.
2:35:43
This is what we wanted to spend the next 20 years on. Yeah. Amazing. Fantastic.
2:35:46
Thanks so much for hopping on the stream. This was fantastic. Good luck, guys. See you on the next one.
2:35:53
And we are ready for our next guest coming on in to the Palace of Party Rounds to YC Demo Day 2025. Welcome to the stream. How are you doing? Nice to meet you. Very nice to meet you. I'm John. Tuchce.
2:36:05
Hey Jordan, nice to meet you. Great to John. Pleasure. What's happening?
2:36:08
I'm I'm kicking this over.
2:36:10
Uh would you mind starting with an introduction on yourselves and the company you're building today? Absolutely. This is Tu.
2:36:16
I'm the CEO of Eloquent AI. And I'm Aldo.
2:36:19
I'm the chief AI officer of Eloquent AI. Fantastic.
2:36:21
And what are you building?
2:36:22
We are basically building an AI platform for financial services. Okay.
2:36:27
To automate complex regulated operations. Okay.
2:36:30
What's an example of that?
2:36:32
For example, in a bank, if you want to unfreeze an account or handle a reg dispute, run KYC, KYB, this usually goes currently to support teams.
2:36:42
And you have a big queue, right?
2:36:45
It might take up to two weeks to open a new business account. Happens all the time.
2:36:49
So, we solve that problem.
2:36:51
Rather than that going to support team, it comes to our dedicated AI operator.
2:36:55
Our AI operator takes on the job.
2:36:58
And here's the real magic.
2:37:01
It basically navigates your existing core banking portal just like your support team does.
2:37:07
We don't need any APIs or any engineering. Exactly. Right.
2:37:13
So this is coming from Aldo's research for more than 5 years.
2:37:15
Um they developed this technology that allows us to do computer use and browser use in a reliable way for very specific tasks. Mhm.
2:37:26
How much of what you're doing is purely enabled by the advances that the foundation model labs versus fine-tuning or any sort of uh scaffolding that you're doing on top of the the state-of-the-art models.
2:37:37
That's a fantastic question.
2:37:39
Do you want to tell a little bit?
2:37:40
Yeah, of course it's a little bit of both, right?
2:37:41
Foundation model of course gives us a lot of uh synthetic data for which we can on which we can train on.
2:37:46
Uh but uh you know we leverage a multi-agentic architecture to actually perform the actions reliably. Mhm.
2:37:54
What's the response been from big regulated financial institutions?
2:37:57
They are not traditionally the earliest adopters of new technologies, but everyone's talking about AI every day, so I'm sure they're excited to at least talk to you.
2:38:06
What's the responsibility?
2:38:07
You know, things have changed.
2:38:07
We are finding it actually.
2:38:09
We reached half a million ARR in four weeks. Congratulations. I love that. Congratulations.
2:38:16
Um, and the reason is because I think all these banks now have the mandate.
2:38:20
Wait, did you say four and a half?
2:38:24
four and a half half a millionaire arrive in four weeks. There we go.
2:38:28
All right, just do that every four weeks for the rest of the year.
2:38:32
Well, at this stage, we actually have a waiting list.
2:38:34
We have more customers than we can on board because as I was saying, things changed in the financial industry.
2:38:40
They want to bring this cutting edge AI in house as quickly as possible. That's amazing. Very cool. How's how's YC been?
2:38:47
Honestly, in any metric, it massively exceeded my expectations. That's amazing, right? Amazing.
2:38:55
I'm a second time founder.
2:38:55
So, I thought, okay, do we really need to come to YC?
2:38:59
You know, we already have the investor networks.
2:39:01
But what was really beyond my expectations is the customer network, especially in financial institutions is incredible.
2:39:06
A lot of YC alumni are now running big fintech companies, banks, and they have been very welcoming.
2:39:15
We can definitely feel the love. That's amazing. Amazing. Um, how big is the team?
2:39:19
Where are you going next?
2:39:21
I'm sure you're raising money.
2:39:22
What's happening down the down the road?
2:39:24
What's in the next 12 months? Absolutely.
2:39:26
So, we raised a big seed round. We closed last week. Congratulations. Do I get another one? We're doing another one.
2:39:35
We closed the seed round, everyone. I love that. I love the spirit here. That's amazing. That's so good.
2:39:44
That still surprises me every time. It does.
2:39:48
It does still surprise me. I love it.
2:39:50
And yeah, we close the seed round at the moment.
2:39:51
It's basically heads down. We are building. We are six people.
2:39:55
Aldo is leading our technical team. Fantastic.
2:39:57
I do sales and we are hiring 10 more people. So 10 more people.
2:40:02
If anyone is watching who is looking for a new role, they are very welcome to reach out. That's amazing.
2:40:09
Well, thank you so much for stopping for soon.
2:40:12
Let's bring in the next guest.
2:40:12
We are live from YC download day 2025. Uh, book a wander. Find your happy place. Find your happy place. Bring them on in. Go to wander. com.
2:40:23
Hey guys, welcome to the stream. How you doing? Good. Good to meet you. How you doing? Good to meet you. Good to meet you.
2:40:31
Uh, why don't you kick us off with an introduction on yourselves and the company you're building? Sure. I'm Somi. Um, and I'm autarn.
2:40:40
It's an AI tutor for students. Very cool.
2:40:41
Uh, what's the go to market?
2:40:41
I I I buil I tried to build a edtech company back in 2012.
2:40:46
It was actually the first company I applied to YC for. It was a disaster. It was extremely hard.
2:40:49
Never really made a dime off of it.
2:40:51
I think I got like 500 installs on the iOS app I built. Yeah. Yeah. Yeah.
2:40:55
Not exactly one of these.
2:40:58
Uh how are you solving that?
2:41:00
Like it's notoriously hard to sell into education. We're seeing a change. Um especially with AI.
2:41:05
We have over 200,000 students active. There we go.
2:41:08
thousand more than what I got during my YC. Thank you. Thank you. You got to keep talking. Okay. $200,000. We love it. Absolutely.
2:41:23
So, so uh well, what is the channel? Is it Let me guess. You got Tik Tok. Okay.
2:41:27
Tik Toks, YouTube shirts.
2:41:32
We have I think over 500,000 followers on Instagram.
2:41:34
And how how long our Instagram build up?
2:41:37
Um, we it was a side project for a while, but I think eight months is like like for the past few eight months. Awesome.
2:41:44
And and how do you uh I'm picturing kind of like an LLM style chat interface. Is that the wrong Yeah.
2:41:50
So essentially like students upload their like learning material like textbooks and we give them like concise notes.
2:41:56
Um like you can have a conversation with an AI tutor as well like you can have quizzes, you can create exams all the study tools.
2:42:01
You create like podcasts based on Yeah.
2:42:03
So right now it's a conversational experience.
2:42:06
We want to make it like more proactive. So you can listen. Yeah, I remember.
2:42:08
And are you getting to the point where teachers and schools are are kind of asking their students to get on the platform and use it Yeah.
2:42:16
So we're talking to a bunch of school districts and stuff, but I think our main focus for now is students.
2:42:21
Um we just want to like get the product down for them and then move up.
2:42:24
And what what uh what what level are we talking? Middle school.
2:42:29
Where's the option been strong? Yeah.
2:42:29
So undergrads um are like number one right now and then it's higher than that.
2:42:34
And now we're seeing a lot of high schoolers as well.
2:42:37
How are you are you monetizing yet?
2:42:38
Are you Yeah, so we have a premium subscription.
2:42:40
Um it's free for like a limited amount of time and then 20 bucks a month.
2:42:44
Idea search based pricing exam season right before exam $200.
2:42:48
Yeah, we give a discount on exam season and it worked really well. Worked very well.
2:42:55
Even post exam like there's always a summer sale this summer. It's really good.
2:42:59
I think it just works out really well. That's amazing.
2:43:00
Wait, so how long have you actually been building this? I I missed that.
2:43:02
Um so we started 8 months ago. Eight months ago. Okay. and then YC. Okay, great.
2:43:06
So, have you been focusing on specific growth metrics during YC to kick off demo day? Um, yes. Just growing everything. Yeah.
2:43:13
So, MR is like our key metric and then retention as well.
2:43:17
We want to make sure like um like a key part in learning is like retaining. Fantastic.
2:43:20
Did you share an MR number today?
2:43:22
Can you share anything with us? Yes, we can. Um, fantastic. Let's hear it. We are at $75,000. Let's go. Congratulations.
2:43:32
Well, I mean, honestly, I got to say sorry cuz just Yeah, I know.
2:43:33
83 83 would have been 1 million. You're close. Amazing. You're close. Yeah, you're close.
2:43:40
Honestly, put another sale on.
2:43:40
Go to every person in the back.
2:43:43
Every Subscribe right now. Let's get to one mil. Let's get into one. Fantastic.
2:43:49
You actually We're not going to let you leave till you get to a million hours. Yeah.
2:43:54
You got to stay in this room. I mean, last question.
2:43:56
Obviously, tons of developments from all the foundation model labs. What's working? What's most exciting?
2:44:02
What are you taking advantage of?
2:44:04
Are you focused on cost optimization? Looking for open source?
2:44:08
Do you want to use the best?
2:44:08
Are you a beneficiary of the 03 pricing drop?
2:44:09
Are you a beneficiary of 03 Pro? 100%.
2:44:12
Every model improvement benefits us directly.
2:44:17
Um, yeah, we want to focus on accuracy the most right now.
2:44:20
We want to make sure everything that a student gets is as accurate as possible.
2:44:23
Are students uh cooked by AI?
2:44:25
Are you are you cooking them?
2:44:29
them? leveraging it more just to study smarter and that's what our vision is and also an interesting thing is they really like our voice mode so it's not just text based they can have a you know like a natural conversation is like you leave it open on your desk
2:44:44
when you're studying type of thing yeah and it can like create mind maps for you it can create like flowcharts you can create whatever you want it's very cool how are you seeing the the the competition you guys drop out um in the process in the process legally legally Not yet. School for you, but not for me.
2:44:59
School for you, but not for me.
2:45:03
Uh, how are you seeing like the obvious competition between just like using Chat GBT 20 bucks a month that's right at the pro tier or like the the plus tier?
2:45:09
Uh, there's a lot of Tyler Cowan's been writing about um I used to feed in a snippet from a book and ask ChattyPy about it.
2:45:20
Now I just say, "Hey, summarize this book."
2:45:21
And it already knows or you can just go out and find it.
2:45:23
It that feels like the logical uh competitor.
2:45:27
Um but how are you differentiating in terms of actual UI design because it seems like as we move to the application layer narrative there is a world where aggregating demand around AI tools around a specific niche works but there's a lot of secret sauce that goes into the UI.
2:45:42
What what are you doing to stay ahead?
2:45:43
doing to stay ahead? So yes, definitely a UI is a big component but the main thing is we just ask our users why do they use us or chat what's the answer and they say like we have like a feature called the quizzes and flashcards and we create that like very accurately for them and what they can do is they can
2:46:00
upload like a thousand page textbook even 2,000 page someone uploaded like the entire imagine imagine hallucinates and you just fail your exam I remember so so so I remember in in college I had a I had a textbook and I wanted a digital version I took it to a a scanning and they scanned it all and they were like, "Do you have the right to do this? This sounds illegal." I This sounds illegal."
2:46:18
I would try and download illegal PDFs. It was very sketchy.
2:46:22
How was how are college students uploading 2,000 page documents? Yeah.
2:46:25
So, if it's available digitally, they can upload it. Okay. Or anything. Yeah.
2:46:29
So, I mean, they can upload anything they want, but it's on them. Okay. Okay. Yeah.
2:46:32
They have to figure out that part of it. Okay. Got it.
2:46:35
But eventually, maybe you could do partnerships with We want to like partner with like ebook.
2:46:38
That'd be very, very cool. Amazing. Well, congratulations. Thank you so much. See you later.
2:46:46
And let's bring in the next team.
2:46:49
Let's do lightning round.
2:46:51
Let's speed these up, right? Speed these up. There's demand.
2:46:52
Is there demand out there? Okay.
2:46:54
Hey, we only have two seats.
2:46:56
One of you can take Oh my god, there's come in. Okay.
2:47:02
Realistically, only one of you or two of you can talk cuz there's only so many mics. Keep going.
2:47:09
Can you guys move the my uh the camera to show everyone for a second? Just tilt that camera. Look at this army. Yeah. Yeah. Yeah. Tilt over a little bit. Go to the wide.
2:47:17
I want to show these whole team.
2:47:19
Are you guys all Are you guys Is this a founding team or you guys all the founding team record?
2:47:24
Who's Who's the founding engineer? There's one guy. There's one guy. What are you building? Break it down for us.
2:47:33
So, uh we are building AWS for AI agents. Like, okay.
2:47:35
Imagine we are 20 years ago it was mostly infrastructure for software as a service.
2:47:40
Now AI agents are becoming like the de facto new new uh new software.
2:47:46
So we are building this infrastructure for the agent.
2:47:48
What is what is important about infrastructure that needs to be different?
2:47:52
Why wouldn't I not just deploy this on AWS or or Microsoft?
2:47:56
I mean you saw Sachin Nadella at at build.
2:47:57
He was saying like we have model router.
2:47:59
We have everything from deep seat to llama to they vend every model.
2:48:04
How are you going to stand out?
2:48:05
Yeah, we we stand out because today first people who are building agents are not cloud architect, cloud you know infrastructure experts.
2:48:13
So new generation of of software developers, software engineers.
2:48:17
The second thing is agents are going to build themsel infrastructure.
2:48:22
So they need new interfaces to interact with the infrastructure and the type of workload that are using like the the technology that are using the lifetime of the computing platform is not the same.
2:48:35
Okay, so serverless is one thing, traditional virtual machine.
2:48:37
And even going back to the YC story, Heroku was that story of like yes, you could always spin up EC2, but Heroku made it easier. Exactly.
2:48:46
And right now we are doing the same for agents.
2:48:48
So when your agent is generating code, it need it needs to have access to some resources to run this code.
2:48:54
So we provide this kind of resources called sandboxes to to help them to run this code for 15 minutes, an an hour or maybe months or years.
2:49:03
How did you when did you start the company?
2:49:05
Did you did you start it three months ago when YC started or you guys have been at it for a little bit? Yeah.
2:49:10
So, actually we both all worked in my previous company.
2:49:13
We sold to a cloud provider.
2:49:14
So, we we know the traders ate over here. It's like Intel again. What happened?
2:49:23
They can't retain any of you. You couldn't be bought. I see what happened. No, it's just six of us. That's amazing. Congratulations. You guys stick together. I love it. I love it. How's adoption been?
2:49:32
uh who are you selling to who loves this product?
2:49:34
So we launched uh we launched seven weeks ago uh and um like most of generation um uh companies from this batch even in the next batch are starting uh using us really paying customers in production right now uh the economic model I assume it's uh consumption based on top of the underlying cloud platforms that you're building on top of is that correct? Yeah, exactly.
2:49:56
We started actually to do something with a a unique subscription with monthly uh subscription just to be sure that people were serious about using us being sure that we get the right traction like we we they are using actually in production our our software. No, we want to expand.
2:50:12
So we are basically offering more just usage based model for the next uh batch.
2:50:17
Do you guys live in the office?
2:50:20
So we leave we sleep uh when we when we can sleep. Yeah.
2:50:22
But we live in the office. Yeah, it's a lot.
2:50:26
It's a lot of mouths to feed. Have you raised money? Uh, Ron's close. Yeah, Ron's close. Congratulations. Thank you.
2:50:33
Congratul I think Jordan's got some for them all with it. Spray them all with it. Fantastic. Well, congratulations. Thank you so much.
2:50:42
Thank you so much for coming. Uh, fantastic team.
2:50:45
Look forward to following your journey.
2:50:47
We got a Have a great Have a great time. We'll talk to you guys. Bye.
2:50:51
We got a good coming in next. We got Waffle coming. Let's bring in Waffle.
2:50:55
Waffle, come on in to the Palace Party rounds.
2:50:58
Oh yeah, they're a customer. That's great. Customer. Love it. Grab some seats.
2:51:02
Put the microphones as close to your face as you can because we are live from YC25.
2:51:06
You're building agents for agents.
2:51:08
We're What are you building?
2:51:11
We're building an AI operating system for small to medium businesses. Okay.
2:51:15
So, what that means is we help you build your website, set up your business email address, your phone number, your bookings, your payments, all that kind of stuff.
2:51:23
Are you guys replacing Google Workspace?
2:51:24
What are you building on top of it?
2:51:27
We're starting off replacing Wix.
2:51:29
So, we've just we've just launched our AI website builder 3 weeks ago.
2:51:31
We've had 700 projects built on there.
2:51:33
Um, and yeah, people are building websites. Okay.
2:51:37
So, you build the websites and then you also are able to instantiate all the downstream stuff.
2:51:40
But I I imagine you're not rebuilding everything.
2:51:43
So, who are you plugging into?
2:51:44
Like, you're not rebuilding Stripe, right?
2:51:46
No, we're not rebuilding Stripe.
2:51:47
It's like wrapping on top of these developer tools cuz there's so many of them now.
2:51:50
There's so many and they're so cheap, you know, like if let's take just like outbound email marketing.
2:51:55
Um, someone could use something like Mailchimp. Mailchimp. Yeah.
2:51:59
And that's that's much more expensive than how much me and Diego pay when we set up a project with Reend cuz it's a developer tool. It's super cheap. Interesting.
2:52:06
And then we can make money on the tools. Okay. Interesting. How's adoption been?
2:52:10
Adoption has been really interesting these first few weeks cuz we've done no marketing.
2:52:14
Mean we're just like full-time coding working on the product.
2:52:17
Um, so we've had people come in from the YC launch.
2:52:19
from the insist or Squarespace website and just cloning it, putting it to Waffle and then just sending it to them can do it.
2:52:33
Uh, I've seen a lot of uh Wix and Squarespace.
2:52:37
You see the web, you see the ads, the Super Bowl ads, and it's always a small business, uh, a restaurant or a pub and, uh, do you have a couple customer avatars that you really like or or want to use to fuel your go to market?
2:52:48
Yeah, right now I think what's really interesting is like the small familyun businesses like the small family run travel agents or law firms.
2:52:56
I think long-term e-commerce is really where it's at.
2:52:59
Um, they care a lot more about their website. Yeah. Yeah. Yeah.
2:53:01
How important is design in that?
2:53:03
Are agents good at design yet?
2:53:05
Uh, it doesn't seem like it's something that would come native and yet the a lot of the AI art that's being produced is beautiful. Yeah. Yeah.
2:53:12
I mean, yeah, it's interesting the default CL like if you just ask CL to generate some UI, it's actually quite good, but it's very unopenated. Unopinated. Generic.
2:53:25
Yeah, it's just like some gener generic type website.
2:53:27
I think if you start giving it examples and just really working the system from you can get it to a point which is pretty good.
2:53:33
Um what we've been doing is using 21st dev. It's a it's a tool.
2:53:39
They have a lot of UI and they're building out uh their magic chat which allows you to kind of take a UI component and like have remixes of it.
2:53:48
Um so they're they're working on that specific technology and we're we're working with them.
2:53:51
Um, so yeah, it's actually pretty good at UI, but it's making stuff which is still quite generic and we're trying to push the boundary.
2:53:59
What were you guys doing before this? Yeah.
2:54:00
So, we we've never worked full-time jobs. Yes. Me neither.
2:54:06
Let's give it up for unemployment. You guys are founders. Yeah. Yeah.
2:54:08
So, we we um we both did computer science. I was at Oxford.
2:54:12
Yogo was at Eco Poly Technique Loausan. Um met up in London.
2:54:17
I moved in with him and then we've just been working. We got you out of there. We got you to America.
2:54:20
Goodness brain said it was impossible to build a company in Europe and your testament to the fact that you got to come to America. Congratulations. Yeah, it's been insane.
2:54:32
I was listening to you guys two days ago. Oh, really?
2:54:33
And when the Cle founder was on and now we're here. Yeah.
2:54:38
Uh it's important to get attention, but there is a limit.
2:54:40
That's where's the line for you?
2:54:42
Cle has their line around what they're willing to do for attention.
2:54:46
It's pretty crazy willing to go that YC goes the other end of the spectrum where they're like just don't focus on your pitch.
2:54:51
Let the numbers speak for you and they're like just put your graph up and that's what matters. I think it's good.
2:54:57
Uh did you have a number that you shared today? Yeah. Yeah.
2:55:00
So we got uh 700 projects built in the last 3 weeks and then that's grown 14% over the last week. Congratulations.
2:55:05
Well, good luck with the rest of Demay.
2:55:07
We have one last hat here.
2:55:07
There might be more out there.
2:55:08
You guys can share that based on days. There's more hats.
2:55:11
Let's give them two hats. We're running out. Are we out of hats?
2:55:14
Yeah, we don't want to run very anyway. Congratulations. Awesome guys.
2:55:18
Let's bring in the next team and let's uh tell you about linear linear app.
2:55:25
Use it to manage your projects.
2:55:28
Half at least half the badges, I think.
2:55:30
So, welcome to the stream. How you doing? Good. Nice to meet you. My hand in water.
2:55:33
I'm going to not shake your hand. Good to meet you.
2:55:35
Uh let's start with an introduction. Uh who are you guys?
2:55:38
What are you guys building?
2:55:39
And please microphone as close to this as possible. Yeah. Uh I'm Daniel.
2:55:41
Uh and this is Musa and we're the co-founders of Vibe Grade. What do you guys do?
2:55:46
So, we help teachers save time grading papers directly in their existing learning management system.
2:55:51
What's the response been like?
2:55:53
Uh, do the teachers love it? Yeah. Yeah.
2:55:54
Actually, all of our customers are paying out of pocket, right? Really? Wow. Okay. Interesting.
2:56:00
Uh, you said in their LMS. Yes.
2:56:00
So, who are you plugging into?
2:56:02
Who's the most dominant platform providers right now?
2:56:05
So, the main one, the best integration is on Google Classroom. Oh, interesting.
2:56:09
So, a lot of is Blackboard not a thing anymore? Not that much.
2:56:14
We we got a request for it but most teachers are on Google Docs and Canvas.
2:56:18
So like most K to2 which we serve are on Google Docs in classroom.
2:56:20
We have toddle as well but it's mainly those few. Makes sense. Yeah.
2:56:25
But for universities they like Canvas is great like they can it'll go and highlight actual sections.
2:56:29
So can you add that on as like one of those like if I'm in Google Docs I can I can do an addiction. It's a Chrome extension. Okay.
2:56:37
So we realized that teachers they don't want to have to learn a new tool and go to a new platform to do that.
2:56:41
So we bu in that works directly with Google Docs and directly with Canvas.
2:56:46
So it's easy as clicking a button and then we open up a window inside Google. Yeah.
2:56:50
So walk me through the typical like workflow homework.
2:56:53
I assume it's like the student uses the the teacher Daniel to write the questions.
2:56:58
The student uses chat GBT to write the answers and then the teacher goes back and check it. You guys grade it.
2:57:04
But but what's the actual workflow in the loop at all?
2:57:08
Our students are students sending uh Google Docs links to their teachers when they're done.
2:57:12
So So Daniel was just in high school, so he really knows how this works.
2:57:18
You dropped out of high school. Get the bottle of wine. Congratulations. Yeah. High school dropout. Chad. Yeah. You front ran everybody.
2:57:31
Everybody that was like coming into demo day. Oh yeah.
2:57:33
I dropped out of college.
2:57:34
It's like that's how it played out.
2:57:34
You had to up to go further. Yeah.
2:57:36
I mean, so you're selling I think we heard about you earlier.
2:57:39
You're selling it back to your teachers now like that you at school you dropped out of sort of.
2:57:43
I mean they don't really like me that much for some reason. Yeah. Like on my final exam.
2:57:49
Well, I mean I I skipped finals to go fly to we went to this edtech conference in Orlando.
2:57:54
So I guess they don't really like me because of that.
2:57:57
But we we had to bring in more teachers.
2:57:59
Well they'll like you when you're the commencement speaker in a couple years maybe hopefully.
2:58:02
So the workflow is where teachers usually they students submit on Google classroom or like canvas they submit a Google doc or a PDF and then the teacher opens it up the doc and they grade it within by like highlighting certain sections adding comments a summary of the feedback.
2:58:16
So we do that whole process uh right in the Google doc and then we have the teacher review everything.
2:58:22
They can speak to our system to understand their tone and their style.
2:58:26
So then we add those comments.
2:58:28
How how is the actual like testing and grading and homework process changing?
2:58:32
Cuz I imagine that the like the solution to chat GBT homework is probably everyone's on a laptop typing the answers in the classroom and there's a monitor watching that you're not just AIing it and then it can be AI graded and then that's a win for everyone.
2:58:47
Is that roughly what's happening? Yeah.
2:58:50
Like the thing that we've seen is like people say all the time, you know, like students are writing with chatbt, teachers are going to grade with AI.
2:58:56
Like what's the whole point?
2:58:56
Well, the objective of the student is to learn and if you're just using like chat and mindlessly submitting something, well then you're not doing the right thing.
2:59:05
Um there's always going to be a way to get around it.
2:59:06
Um if you really don't want to learn but like for teachers the main like objective is to give students the best feedback and instruction. Yeah.
2:59:14
So what we're doing is just enabling them to do that a lot better because even in school when like our teachers would give us just like generic copypaste feedback. Yeah.
2:59:20
So we just want to give students the best feedback possible.
2:59:24
gives teachers their time back and they really get the value because they're the ones experiencing the benefits. Yeah.
2:59:30
Talk to me about the top of Why would you not at one point just give the tool to students as well? Yeah, 100%.
2:59:37
That's actually what we're working on next.
2:59:39
So, we just signed three contracts with with schools last week. Okay. Congratulations.
2:59:43
and they want to be able to give this tool to students so that while they're writing um they're going to get real time feedback on their Google doc as if the teacher were adding comments in real time.
2:59:54
So it's sort of like you know you submit a rough draft to your teacher they have to grade it and then give it back to you and then you can do a final draft.
3:00:02
Instead of that why not just have like the assistant give you feedback in real time.
3:00:06
Oh yeah that makes sense on the doc. Yeah that's great.
3:00:08
Uh talk to me about the top of funnel.
3:00:09
How are you telling teachers that this works?
3:00:11
I imagine at the price point you can't do handtohand combat sales.
3:00:16
Uh how are you getting in front of teachers these days?
3:00:20
So all of like we have 100 teachers that are paying completely out of pocket and all of that has been organic through either the Chrome web store.
3:00:25
So they find that's when they install another extension like Grammarly and then they tell their friends about it.
3:00:30
So word of mouth has been really strong.
3:00:32
We got 600,000 views on Instagram and Facebook in the past 30 days. There we go.
3:00:38
We just started posting like memes and things like that and teachers really they they share it and then they look at our page and so they find us there. That's great.
3:00:45
So that's the top of funnel up until this point and we're going to start pumping out more like UGC style content.
3:00:50
We're actually going to the biggest edtech conference in the US at the end of this month. The Super Bowl of Ed.
3:00:55
Yeah, there's going to be 20,000 teachers there and we got a really big we bought a 400 foot booth there and we're going all out for it trying to reach as many teachers as possible. Congratulations.
3:01:05
You guys make your first uh money on the internet. Thank you.
3:01:08
How did we first make back?
3:01:08
I I used to make I used to make websites for like random people.
3:01:14
I charged like this pastor in New Jersey like $3,000 to make his church a website. Wow. Yeah.
3:01:19
That was back when I was maybe 16.
3:01:21
I made like a a mental health chat app in like grade 10 and like a couple of people like one person in Japan found it and they installed it and paid for it. They paid for it. That's amazing. Congratulations. Have a great demo day. Great to meet you.
3:01:36
Yeah, you really rooting for high school's cooked.
3:01:39
Call us when you meet the first. Yeah, we're good.
3:01:43
We got middle school dropout middle school dropout.
3:01:45
That's how I was going with that. Welcome to the stream.
3:01:48
We are live from YC Demo Day 2025. Good to meet you. I'm John. Nice to meet you. Welcome to the stream. How you doing?
3:01:55
We're going to have you sit down here.
3:01:56
We're going to have you pull this microphone as close as you can. Talk directly into it. Introduce your company. What do you do?
3:02:00
We are building AI agents for insurance claims operations. Okay. How's that going?
3:02:03
Are you is business ripping?
3:02:06
Yeah, we're at 200k AR now. Let's go. Let's go.
3:02:08
Let's go where the money is.
3:02:11
That's why people rob banks cuz that's where the money is.
3:02:15
Go to the insurance industry. It's expensive.
3:02:17
Who Who are you selling to?
3:02:18
Are there is it as I I assume that the insurance industry is very igopolistic?
3:02:24
There's a few big players, but is that not right?
3:02:26
We're selling to third party administrators, which are these like claims outsourcing companies, of which there is a surprising number.
3:02:31
Yeah, it's like 42,000 across Europe.
3:02:33
Did you realize that you guys loved insurance? 6 years old.
3:02:39
I wanted to process claims.
3:02:42
No, I'd seen it in my job before like sort of had some exposure.
3:02:45
My roommate is an insurance adjuster.
3:02:46
So, I was like, look over his shoulder.
3:02:47
I want to put you at a job so I can hang out and go to more movies on the weekends. You're working late.
3:02:53
I want to play get video games with you. That's the best. Awesome.
3:02:57
Uh, so yeah, walk me through what you're actually building, what the product experience is like, how it plugs in.
3:03:03
I assume this is some sort of like co-pilot experience right now or is it fully agentic?
3:03:07
It's a it's a full fully agentic experience.
3:03:09
So the goal is to replace like autonomously parts of the workflow for the adjuster.
3:03:15
So the thing we're live with with our customers is like a claim intake agent.
3:03:18
So when you crash a car and you call in, you basically ask you a set of structured questions and then creates structured data and writes it into the system of record. Got it. Okay.
3:03:24
And and previously that was handled with someone on the phone talking and typing everything in. Your room. There you Yeah.
3:03:32
Did you get him as a customer yet? No, not yet.
3:03:34
He he worked for a very big carrier, so that's going to be a long game with that one.
3:03:38
So, and what were you doing before?
3:03:41
Um, I was doing product consulting and then worked as a software engineer at Agentive, which is another YC startup. Oh, very cool.
3:03:46
Uh, how's the round coming together? What's yesterday? Close to yesterday. Congratulations.
3:03:54
Uh, well, thank you so much, Robin. Good luck.
3:03:56
With everything we're moving into lightning rounds, I'm going to give you one of these.
3:04:00
Let's bring in the next team.
3:04:02
We're moving through these quicker.
3:04:04
Thank you so much for hopping on.
3:04:06
We are live from YC Demay 2025. Welcome to the stream. Come on, sit down. What do we got? Text AI. Text AI. That's a good domain.
3:04:15
Are we supposed to suit up for this?
3:04:17
No, you can wear whatever you want.
3:04:19
We don't have the right gear. Pleasure. Pleasure. Nice to meet you. Pleasure. Nice to meet you. Nice to meet you. How you doing?
3:04:24
Sorry, we don't have an extra chair.
3:04:26
I I I brief I caught like uh 30 seconds of your two-minute pitch.
3:04:30
But but give it to us again. What's the pitch today?
3:04:33
Yeah, we're AI agent right in your group chats. Okay. In the group chats. Yes, sir. How are you plugging in?
3:04:38
Because I feel like iMessage, they really don't like when other companies plug in. 100%. We're carrier based.
3:04:43
So, as long as you have a number that you can just add to a group chat instantly, right then and there.
3:04:48
Are you a beneficiary of the RCS update? Yes, we are. Explain how.
3:04:50
Yeah, we're working through a couple of providers that give us a number.
3:04:54
So all working with all the carriers like Verizon, T-Mobile, AT&T, and then we're applying for the RCS is still in the beta stages even though it's rolled out.
3:05:03
But SMS infrastructure is one of the best infrastructure in the world. So uh that's working. Whoa, hot take.
3:05:06
I feel like everyone's annoyed by it.
3:05:08
That's why Twilio exists, but you know, is it is it good now?
3:05:12
It feels like it was terrible for a long time.
3:05:13
I feel like the big question around adding an AI to your group chat is security.
3:05:17
Things that happen in you know, yeah, signal group chats, you don't you want to be very careful about who you are, journalists, How are you handling security? Yeah.
3:05:25
No, great question, guys.
3:05:27
It's we don't sell your data.
3:05:29
You can kick out the AI whenever you don't want it, right?
3:05:31
You bring it in, bring it out.
3:05:32
Nothing compared to like met AI where it's always living in there ambiently.
3:05:35
It's completely under your control.
3:05:37
So, we don't sell any of that data either.
3:05:40
What's the What's the most obvious use case like the family group chat, creating a grocery list or something like like give me some examples of how people are using this.
3:05:48
It's it's actually a lot of friends using this to get a restaurant recommendation, roasting each other.
3:05:53
when do we need to actually all meet up? Have reminders in there.
3:05:57
That's our first agentic flow. Yeah.
3:05:59
Cuz in and when you're planning trips and trying to go out, there's always that one person.
3:06:02
It's like, "No, I'm too busy or this doesn't work for me."
3:06:06
And someone has to put in the screenshots.
3:06:07
Someone's always taking the lead.
3:06:08
The idea of adding agents to group things.
3:06:12
It feels like like I saw this meme that was like, "I joined a Zoom call and it was seven AI agents." You see this one? Everyone. Yeah. Everyone knows.
3:06:19
And it was like the one poor girl and then like this person's noteaker and fireflies and Lou and this one and this one this one.
3:06:25
How are you thinking about building the agents yourselves versus letting people build on top of text AI? I think two things.
3:06:31
Number one is like the quality control that has to come in along the things like you said on the data piece.
3:06:36
We're a consumer company. We're like text. ai.
3:06:39
People interacting with us.
3:06:40
We want to be very careful of allowing third parties to come in here and see what they do with the data that's prevalent.
3:06:45
And second is like we build it ourselves so we can really figure out specific use cases like calendaring for example working with other people's calendars giving you a exact answer like hey between all five of us when's the best time where we can actually grab coffee later this evening and it can actually find it done and dusted right then and there.
3:07:02
How much of the go to market is just pure viral growth because someone gets added you realize that it's text AI and you add it to the next group chat and it just kind of goes from there and you add a studio Giblly machine to the group chat.
3:07:11
That is a great question.
3:07:13
We have Gibly images working.
3:07:15
I wish I can put it on live stream right now, but we actually have collaborative AI where we can actually start doing images. People can edit it.
3:07:21
I love I mean that was the beauty of MidJourney is that they use Discord, right?
3:07:24
And then so if Jordy writes a great prompt, I can kind of spin off that makes sense that would happen in iMessage.
3:07:29
There's so many fun and I'm I'm already thinking like anytime somebody shares any photo, just immediately make it like a SAR trooper version of that.
3:07:36
That's like half of our group chat is like somebody just me sending Giblies of all the other guys in the chat. It's like great.
3:07:41
Isn't it Isn't it exhausting that everyone like cuts and past? Yeah. Yeah.
3:07:43
You go back and forth, back and forth, back and forth.
3:07:45
Make it so that everyone is accessing it equally as they need to. Yeah. Yeah.
3:07:49
And the beauty is you can create an image, he can edit it, and someone else can edit it on top of it. Yeah.
3:07:56
So, it's much more collaborative.
3:07:57
There is no need to really copy paste images.
3:08:00
Is it a fun use case that we saw just develop?
3:08:02
This is the best part of being consumer, right?
3:08:03
Is that you get to put this out there and you get to see what people do it. Hinge dates.
3:08:06
No, someone goes in, brings them into a text thread, says, "Hey, by the way, um, I have my AI staff here, digital staff.
3:08:12
Do you have any restrictions?
3:08:15
Do you have any favorite restaurants?"
3:08:19
Imagine like this is well above beyond use cases you could have imagined and it's it's going to places where people are being really thoughtful about how do you bring it in to make it more easy for us to have a human connection.
3:08:28
What were you guys doing before this?
3:08:29
So, I was at Tesla for four years leading there.
3:08:31
Can you explain what Tesla is? No idea.
3:08:37
Your guess as best as mine.
3:08:37
Um, no, I was leading the digital supercharging team there and the vehicle subscriptions team. That's great.
3:08:44
And then for Yeah, I was I was leading an engineering team at Walmart.
3:08:47
And then before that, I used Let's give it up for big Let's give it up for big retail.
3:08:54
I wonder what Walmart is. Huh.
3:08:54
But before that, I was at Eventbrite and Open Table doing a lot of consumer personalization.
3:09:01
Some of the same workflow.
3:09:02
So that's why I think one of the main reasons we founded texti was our rich sort of consumer background. So yeah, yeah.
3:09:07
No, I've had a blast of being in media for a long time.
3:09:10
Most recently I uh was the CEO of a B2B media company down in Los Angeles.
3:09:14
We exited I sold it over in October.
3:09:17
Um I've known these guys for eight years.
3:09:19
So Rushi's first job was at a crypto startup my wife was at.
3:09:24
She hired him and then he wouldn't she wouldn't leave he wouldn't leave our house. He just like showed up.
3:09:28
And so I've seen him do everything.
3:09:28
And then Parar of course these guys went to school together.
3:09:32
And so um the opportunity after going in and doing a lot of executive jobs at like publicly traded companies and whatnot.
3:09:37
I think if you want to know what's happening, you got to get hands on keyboard.
3:09:41
There's no talk the executive talk and pretend like you understand it. You got to get back on.
3:09:46
And so for me, this was a great opportunity to go work with these two guys and start from scratch and just get to know what's happening because this is going to be the platform for the next 15 years. That's amazing. Well, congrats. Thank you very much. Quick question.
3:09:57
How's how's the watch game at uh in your guys' batch?
3:09:59
I see I see you guys each the Texas time.
3:10:01
He has a better g he's leading the way.
3:10:07
I might be the oldest founder ever to go through YC and so yeah. No. What are you like 32? Oh yes.
3:10:12
I'm going to stay with that. Yeah.
3:10:15
Closer to 50 than I am to 32. Okay.
3:10:17
Well pleas coming into studio. Welcome. Great to see you. Great. Come on. Welcome to YC Demay. I see two sweatshirts. Pull the mic up. Hey. What is that? Why? Preliminary. Preliminary.
3:10:36
You just assume that they're blowing out their metric.
3:10:40
Assume that you're doing good to meet you. What's up?
3:10:42
Can you kick us off with an introduction on you and the company that you're building today?
3:10:45
Hey guys, we're uh we're building value mate.
3:10:49
We're automating real estate appraisals. Okay. With AI.
3:10:50
When did you realize you wanted to evaluate real estate appraisal? Yeah.
3:10:55
Um, so a little bit, you know, family background like things of the sort.
3:10:58
Um, we kind of discovered this pinpoint. We both study AI at CMU.
3:11:02
Um, so we have family's had a background in it and, you know, seen appraisals and things of the sort.
3:11:07
Super inefficient process.
3:11:09
Um, and we were like, it's one of those industries just perfect like just ready, you know, to, you know, to to become a lot more efficient.
3:11:16
Um, and that's kind of how we how we got into the space.
3:11:18
What is the what is the structure of the legacy market today?
3:11:22
There's you guys are are providing a tool for people that do appraising. Yeah, exactly.
3:11:27
So like the current like the current competition has literally existed for 40 years, right?
3:11:33
And it's just like like appraisal reports is like a snapshot of like a property value.
3:11:36
Human goes in and looks at things, takes some pictures and writes down trim and floorboards and mold.
3:11:44
So we bring this entire thing down in just a scan. Okay. Right.
3:11:46
So you scan it, we build a 3D model, 2D floor plan, our computer vision takes notes. Sure.
3:11:51
And then we pull data from all these various sources. Got it. Right.
3:11:52
And then you know we use AI obviously fill out this kind of report.
3:11:56
So so it's a you know it's a pretty timeconuming process that we're about to that that we're able to bring down.
3:12:02
Is it a partnership with Zillow to do a better estimate or or truly augmentation co-pilot for the existing true appraisal reports that are used in underwriting?
3:12:13
for the true appraisal reports that are using underut because the issue with Zillow um and and every appraiser will kind of tell you this.
3:12:20
This is like super inaccurate like the estimate is like you know like people are like ah like it's mostly based on like recent sales in the area.
3:12:26
It's not actually the quality of the building. Exactly. Right.
3:12:27
Um so what we're able to do doesn't even take into account remodels. Exactly.
3:12:30
Cuz they don't know, right? They don't know.
3:12:32
They don't have the data.
3:12:34
Um and what we're able to do is have this digital twin go of a property.
3:12:37
Um so it's actually along the way as we're you know we're building this and selling you know software presenting sort um we also have the most valuable property data set um that anybody's going to kind of have um to build future models cuz super accurate.
3:12:51
What were you guys doing before this?
3:12:54
Before this um we were students at Carnegie Melon University. We dropped out years. Yeah. Yeah. I'm sorry.
3:13:00
There's a a couple guys dropped out of high school.
3:13:02
It's not really special anymore but not cool. you didn't form here.
3:13:08
Uh, talk to us about traction. How are things going?
3:13:11
Things have been going super well.
3:13:12
Um, we started selling 20 days ago.
3:13:15
20 days and we're at $124,000 in Congratulations. You were correct. The confetti.
3:13:22
Did you guys get um Did you guys get the round done already? We are.
3:13:28
We are still filling out a round stage talks with some with some leads. Um, good luck.
3:13:32
But it's looking like we're going to we're going to graduate.
3:13:35
When did you uh last When did you when did you first discover YC? Oh, yeah. That's a good question. Discover YC.
3:13:39
So, my freshman year roommate from Carnegie Melon was actually YCF24. Oh, there you go. Told you about it.
3:13:46
In my mind since then, I was like, "Okay, I have to do this.
3:13:49
You got to And then, you know, we did it." So, welcome. You're in the league.
3:13:52
You're in the league now. You're in the league. Welcome to the league.
3:13:56
Welcome to Silicon Valley.
3:13:56
Uh, and welcome to Demo Day.
3:13:57
Thank you for stopping by. We'll talk to you later.
3:14:01
Let's bring in the next crew. Thank you so much. We got a line.
3:14:03
We got a line out the door.
3:14:05
We're going to bang through these.
3:14:06
We got These guys got QR codes on their sleeves. Bloom. Yes. Bloom. Bloom.
3:14:10
Are you building Bloom filters? No. No.
3:14:12
What do you So, the easiest way to nope. Okay. Bring it down. No.
3:14:16
So, lovable but for native mobile apps.
3:14:18
The easiest way to We'd love to just like show you. Please. Okay.
3:14:23
So, have you guys tried to build mobile apps? Touches. What is that?
3:14:25
I've never seen that interaction before.
3:14:27
He's got UI from the future.
3:14:29
So, have you guys ever tried to build?
3:14:31
Yes, I wrote Objective C. It was terrible. I wrote X code. It was awful. Sucks.
3:14:34
We love Apple, but you know, we were very excited about the anthropic partnership. Yeah.
3:14:42
So, typically you'll have to write code.
3:14:44
You'll have to build the app in Xcode or something.
3:14:46
You'll have to submit for apps to review.
3:14:47
You have to get your users to download it on Tesla, enter an invite code. Okay.
3:14:51
So with us, I can literally just like talk into my phone, build a native app, and then I can send it to you via literally bumping phones. Do you have an iPhone? Yeah, I do. I do. I see this.
3:15:00
It'll just load the app right onto the home screen. Okay. Malware installed.
3:15:09
All personal information extracted. Here we go. I don't know. I got I got one. Let me see. Uh we got half.
3:15:13
I mean, this is just using airrop.
3:15:17
I think do you need to turn it on again? No. Oh no. live demo set up.
3:15:22
Airrop like maybe we need another Are you on the same Wi-Fi? You want to try? Yeah, I'll try. Let's see. Airrop. Airrop is on. Oh, contacts only. Now it's on everyone. Okay, I got it. I got it. Cool. Let's try it now. There we go. Skill issue. Skill issue maybe. Okay. Oh, Jesus. Is it going? I got the wave. You saw the wave, right? Yeah. Yeah. Yeah.
3:15:42
I only have RAM, public, adquate, sleep, wander, and test installed right now.
3:15:47
Those are going to be absolutely Let's give it one more shot. Uh, you can take it.
3:15:50
Otherwise, we'll have to maybe retry on your phone. Yeah, it's okay.
3:15:55
It's not like this is live or anything. Okay, you you try. You try. We'll give it a try. Anyways, keep keep Yeah.
3:16:01
So, so when someone like tries to build an app with Bloom, right?
3:16:08
It's doing, but it's not doing that.
3:16:09
I think the internet just sucks.
3:16:09
I think the internet is not the internet.
3:16:13
Anyway, so what you would see is you'd be able to open this app on your phones like instantly, right?
3:16:17
And it uses app clips under the hood. Oh yeah. Okay.
3:16:19
So that's how you're getting the app on without me actually installing. Exactly.
3:16:25
Oh, they're really hacking the app. That's awesome. Okay.
3:16:27
And so the other thing is like when you prompt to build an app with us, we also automatically deploy a back end for you that real time syncs data between devices.
3:16:34
I as I understand app clips, it's like it's like uh there's there's like one app like the Uber app exists and then there's an app clip that ties to to Uber.
3:16:43
Are you creating like custom app clips?
3:16:45
It's all It's all around one iOS. Oh wow.
3:16:48
It's one Bloom app whatever.
3:16:51
So it's like an app store with an app store. Yeah. Kind of like that.
3:16:58
We've talked on the on our show before about this idea of like ephemeral apps like memes.
3:17:02
Like there's a lot of things that should exist but only for like a day.
3:17:06
We've had so many ideas for like funny apps but we don't want to actually go pay.
3:17:09
go pay. Oh, it used to be there's so many people like people people have an idea for an app and you're like well you realize it'll cost like a million to build that it's not actually like with us we built an app for for demo day in 5 minutes that everyone in the audience could just scan to like vote on our
3:17:25
valuation in 5 years and it like had a graph that updated in real time for everyone cuz it has a back end connected to it and so what we want to enable is a creator economy but for software okay under the hood what are the best uh code generation LLMs that you're using what do you like what's exciting And how how is that market developing? Yeah. So I Yeah.
3:17:41
So I mean right now we're we're obviously for the smartest models we're using cloud for sonet.
3:17:46
Um but we're also experimenting with you know a smart mode smart mode and a fast mode because sometimes people just want to make like a quick edit to their app and like literally you can just speak into our phones right you just go into like this like edit mode and then you can just type hey add this feature or whatever.
3:18:02
Um and so sometimes you just want those changes fast.
3:18:04
Um, and what's cool is like if you had this app open, it would also hot reload on your device, right? So, very cool.
3:18:11
What uh what use cases are you most excited about? What are you seeing? What categories broadly?
3:18:15
Yeah, I mean, so right now we're seeing people that already think as software as a creative outlet use this.
3:18:20
So, developers, designers, and entrepreneurs.
3:18:23
So, especially for designers and nontechnical entrepreneurs, it's great because they can just like be their creativity gets unlocked with this.
3:18:29
Um, and so we're seeing people build all kinds of things like personal apps, but also apps that I wouldn't have imagined before, like someone in Africa building like a wild life tracking app for their conservation.
3:18:41
Um, and then people building like funny apps for find the most delicious animals to go after to conserve animals for for my own hunting for my next hunting expedition. I'm kidding.
3:18:54
But um but yeah, what I'm really excited about is like the apps that I can't even imagine, right?
3:18:59
When the YouTube founders put out YouTube, I'm sure they weren't imagining vlogging or MKHD just like you know you put out images in Chet.
3:19:05
They didn't really imagine studio exactly happening.
3:19:09
And for us, I mean, it's software, so you can literally do anything. Congratulations. Thank you so much. How's your round going? Oh, round is closed. Let's go. All right. Good stuff.
3:19:22
Well, bring in the next team. Welcome to the demo.
3:19:24
I'm breathing in the microplastics. Really?
3:19:27
This is violating everything I know about you.
3:19:31
Put your life on the line. How's it going? What's happening? Hi. Nice to meet you. I'm John. Pleasure. Wait, I don't have long. Yeah, no worries. No worries.
3:19:39
Uh, can you introduce yourselves? What are you building? Sure. So, we're Morpho AI.
3:19:44
We're building a software tool for engineers that are building new robots and new machines. Oh, interesting. Yeah.
3:19:48
So, I came came from the manufacturing tech world.
3:19:50
Um, we both met at Harvard. I was an MBA. He was a posttock.
3:19:52
And you know, you should talk about yourself too. Yeah, absolutely.
3:19:56
And yeah, I met her when I was at Harvard.
3:19:57
Like she said, we got a introduction from a mutual mentor.
3:20:00
Um, I did my PhD at MIT focused on automating the design of robots.
3:20:04
So, it seemed like uh, you know, wanted to bring that into some sort of product.
3:20:08
Show people in the world how useful it was and how it could change the way people design and she was super excited about changing all the pain points in manufacturing. So, we're doing this.
3:20:15
What is exciting in terms of robotics in manufacturing?
3:20:17
There's a lot of noise about humanoids, but we talked to a lot of people who are just saying robotics and manufacturing or is it a tool to accelerate the manufacturing of robots? Second one.
3:20:26
The second one, but but the main beach head market is really in industrial robots. Okay. Yeah.
3:20:30
So, so what those look like? Yeah.
3:20:33
So, the crazy stat that we found is, you know, if you're actually buying a robot off the shelf, you can't actually just like put it in the factory floor, like 90 plus% go through a customization process.
3:20:42
So, that's like 6 months of lead time and, you know, it takes up a lot of engineering hours.
3:20:46
So, one of our customers, they were trying to build a full new industrial robot arm.
3:20:50
Um, 6 months gone in, you know, arms not lifting.
3:20:54
They came to us and in two days we basically redid their entire hardware design. Interesting.
3:20:57
So, quite literally, we're allowing engineers to build new robots overnight is the hope and in the future in a matter of minutes.
3:21:03
How how concentrated is the robotic arm market?
3:21:05
Are there just a few companies that you really need to integrate with deeply or do you need to create something more generalizable out of the gate?
3:21:11
Um, so we're starting out with a little bit more of the OEM side of things, but also these integrators that are buying these arms and saying, "I now need a new hand."
3:21:18
So out of like the what 50,000 robots that get deployed in a given year, most of them have a new hand that's made.
3:21:25
And so now you have a journalist engineer trying to make a new hand for four to six weeks in a new design.
3:21:31
Uh, so really plugging in in that early stage of what do I build uh before we even get to the programming part. Yeah.
3:21:36
The whole idea is you just have to input the task specifications that you needed to solve and then as much as possible we're automating of the mechanical and somewhat the control design side of things.
3:21:44
Is there is there a lot of data that you need to feed in?
3:21:48
Is there a lot of data that you need to pull from the manufacturer before you can we work with parts that manufacturers have and that they like to work with?
3:21:54
Um and aside from that it's task specifications but we unlike a lot of the uh Genai companies out there we do employ some Genai solutions but they're all trained from simulation and not from data set.
3:22:04
That's really important because the data for how do you go from design to something how well it's going to work that that doesn't really exist.
3:22:11
Nobody takes logs and curates data sets of things they've built and how well they worked. Sure. Sure. Sure. Uh talk about traction.
3:22:16
Uh sounds like you guys already are are in market. Yeah.
3:22:20
So uh we actually just got a grant from the UK government 2 and a half million British pounds.
3:22:24
Um fantastic last couple months. Non-dilutive. Fully non-dilutive. Congratulations. We love it for that. Jordy. Oh my god. My ears going to happen.
3:22:35
Not in here than out there.
3:22:35
Not related to funding from I mean Europe just shooting themselves in the foot they're going to be like why didn't we get at least like quarter point or something. Anyway, congratulations. Thank you.
3:22:50
None of us are British but they basically Well, we're setting up an office in London.
3:22:54
Like we're really excited about about working with them and setting up an office.
3:22:57
Of course, there's benefits to the research community.
3:23:00
We have a lot of collaborators there as well. That's fantastic. That's great.
3:23:03
be an amazing outcome for them.
3:23:05
Last thing, bull bull bear on humanoids. Yes, humanoids. What's your take?
3:23:10
I'm bear, but um like medium bear. I don't know.
3:23:13
It was was like, okay, if you're going to build a humanoid, which humanoid like people come in all sorts of sizes and shapes.
3:23:17
A construction worker is not the same as like a like a toddler or something.
3:23:22
Okay, not toddler, but like ballerina. Exactly.
3:23:24
Line backer looks different than So, you're going to need custom designs regardless of what you do.
3:23:27
But I mean the other side of things is just like what is the application right now of the humanoids that isn't solved better by re-engineering the things around the humanoid and that's that's there's a there's a long tail there.
3:23:38
So we we hope we can help people to design the humanoids of the future.
3:23:42
Just don't think it's here yet. Yeah. Yeah. Yeah.
3:23:43
I think I think there's Yeah.
3:23:45
You're not saying embarrassing a 100redyear timeline or maybe a 10ear timeline.
3:23:48
I just think it's a little I completely agree. Very reasonable stance. Anyway, congratulations. Congratulations.
3:23:53
I'm going to give you a salute so we don't have to deal with the whole sheriff fist like Okay, perfect.
3:23:59
Anyway, let's bring in the next team. Thank you so much.
3:24:01
The table is now covered with confetti.
3:24:04
We predicted this happen millions of dollars.
3:24:09
Head over across the pond.
3:24:09
Uh this could be the greatest capital extraction event, the greatest wealth creation event in history.
3:24:15
In history since the Boston Tea Party.
3:24:16
Anyway, good to meet you. Welcome to the stream. My name's John. How are you doing?
3:24:22
Can you introduce yourself and the company? Yeah, absolutely. Yeah, so um I'm Rajith. We're Prism.
3:24:27
Uh Prism is an agentic observability company.
3:24:29
So we let developers configure agents to watch their production systems.
3:24:33
So read logs for them, watch videos of their customers using software and then enable them to take certain actions.
3:24:39
So like create issues on linear, GitHub, sponsor the stream, let's Yeah. Yeah.
3:24:43
I did that on purpose and uh and send reports to Slack. So that's great. That's great.
3:24:47
Um well, how's adoption been? How are you selling in?
3:24:52
Are you going uh mediumsiz scaleups, other startups, YC companies, enterprise? What are you thinking? Bottom up.
3:24:57
So, this is a tool that every developer needs and every developer can use.
3:25:01
So, we're starting with the YC community.
3:25:02
We're completely self-s served.
3:25:04
So, there's 23 people on the platform and counting.
3:25:05
More people sign up and start using it every time.
3:25:07
Were you guys were you guys iterating through the the batch? We were. Oh, yeah. Yeah, we were.
3:25:12
So, the first version of the product, so it's like we watch videos of people using software, right?
3:25:16
So the first version of the product was these two watching everyone's videos and just giving them issues and like sending them Slack messages and stuff like, "Guys, this is broken. You need to fix this."
3:25:26
So that we were basically like a services business, but we didn't tell everyone.
3:25:28
We told them it was AI and it was just these two.
3:25:31
So that was the first version of the business. Got to start somewhere. That's awesome.
3:25:33
Uh what uh how's how's fundraising going?
3:25:36
You guys in the midst of it? Great. It's going great.
3:25:39
We're in the midst of it.
3:25:40
Still, you know, still trying to finish up the round.
3:25:41
Um but yeah, we're excited. Excited. That's fantastic. Awesome.
3:25:45
Uh, what were you doing before?
3:25:47
I was at Gretile, which is a code review company. I think you guys Yeah.
3:25:53
Dragon with eating the bug. Amazing. Great website. Yeah. You too?
3:25:54
Uh, I was a software engineer at Pounder. Oh, cool.
3:25:59
And I worked in product at Johnson and Johnson. Oh, very cool. Alex big pharma. Yeah. Yeah.
3:26:05
So, Land and I met in high school and then all three of us were at Georgia Tech together. Cool.
3:26:09
Alex actually had a post on LinkedIn this morning about how he left 850k a year behind at Palunteer to come work with us. So there we go.
3:26:16
I think you'll make it all back. Just burn the boats.
3:26:20
Anyway, good luck with the rest of de we are ready for the next guest on the YC demo day stream. Tyler 10 minutes left.
3:26:29
10 minutes left and then we got to go. Yeah. Yeah.
3:26:31
We can speed through this as much as we can.
3:26:33
Um we got 10 minutes until we got to go to the airport. Is that right? or start 10 minutes. We got 10 minutes more. Come on in.
3:26:42
Don't even bother introducing yourself.
3:26:44
Just tell us what you do.
3:26:44
What company are you building? How you doing? We are Clarm.
3:26:48
We are Perplexity on Internal Documents.
3:26:51
So, search is being heavily disrupted by AI at the moment.
3:26:56
As you know, Google is being disrupted by perplexity and uh we're doing that for internal enterprise search. Okay. Competition with Glean.
3:27:03
They just raised a bunch of money.
3:27:04
How are you thinking about that?
3:27:05
We're going to replace them.
3:27:06
You're going to replace them.
3:27:08
They're just getting started.
3:27:08
You're not replacing Google. We're replacing clean. Okay. Okay. So, how do you do it? What's different?
3:27:14
How do you actually integrate?
3:27:15
Are you building a bunch of integrations?
3:27:16
Are you building on top of an integrator?
3:27:18
We are we have our own integrations.
3:27:20
Uh we found that the the only way to do this to actually build AI agentic search is to build it from the ground up and that's why all these legacy players have to do that as well.
3:27:31
What's more important in integration with Google Docs for example or integration with uh like the data lake that's maybe that maybe somebody has a snowflake installation? What's more important?
3:27:41
I mean it's important to have both of them so that you can connect integrate both and you connect.
3:27:44
We have about 45 connections. 45 connections. Okay. Uh how about customers?
3:27:47
How many of those you got? Uh we have eight.
3:27:49
We only launched two weeks ago. Congratulations. Congratulations.
3:27:52
Uh what's the biggest challenge? Is permissioning hard?
3:27:55
Maybe at smaller companies it's it's it's not as much of an issue but as you go kind of up market it's dealing with all the different types of data and this is why B2C companies don't play in enterprise space because when you have to look at Salesforce data alongside Messiac Excel sheets then it becomes uh harder to to connect them together but that's the value in it.
3:28:16
Where can companies go to get started? They can go to clam. com.
3:28:20
They can try our live demo.
3:28:20
Fiveletter domain already. Five letter domain.
3:28:25
Congratulations on demo day.
3:28:27
They can talk to us directly.
3:28:28
A fantastic JLC reversal. It's a fantastic watch. We'll see you soon.
3:28:33
Thanks so much for hopping on.
3:28:33
Let's bring in the next team.
3:28:35
We're doing lightning round. Lightning round. Lightning round.
3:28:37
Lightning round at YC Demo Day 2025. Welcome to the stream. What do you do? What are you building?
3:28:42
AI co-pilot for solopreneurs. Exactly. Okay. Get out of here. Good job. No, how's it going?
3:28:47
Uh, how many customers do you have?
3:28:51
What what data are you sharing today at YC? Who's more cracked?
3:28:54
He's definitely the most cracked engineer we have we have ever seen.
3:28:58
He's the most absolutely most.
3:28:58
So, we've gone from 0 to 300K in the last 9 weeks. Oh, congratulations. Yes.
3:29:04
So, that's that's what we're doing. Absolute.
3:29:07
And yeah, we're seeing this future where solopreneurs are going to completely wipe code and run their entire business on cactus, right?
3:29:12
So, that's what we're building. Great name. Great name. Thank you.
3:29:16
What were you guys doing before this?
3:29:17
We built a previous YC company.
3:29:19
He was a founding engineer. We scaled it up to 2. 5. That's it. I'm crack.
3:29:24
He's a crack sales guy and the crack engineer and together we are the crackers. So crack sales guy.
3:29:31
Uh how are you actually selling this thing?
3:29:32
Is it hand to hand combat with these solarreneurs or are you doing like viral marketing?
3:29:35
We've seen levels get a lot of attention for solarreneur stuff.
3:29:39
How are you actually attracting people? Absolutely.
3:29:41
So it's mainly through word of mouth that's been spreading.
3:29:42
What we also do is outbound where we call them.
3:29:46
Think about them saying, "Hey, you just missed an opportunity, guys."
3:29:55
So, yeah, they get back and then they set up characters.
3:29:59
They get incremental 10 to 15k in a month revenue.
3:30:01
And the biggest thing is the headache for them is gone, right?
3:30:05
They don't have to answer the phone. Yep. That's the best thing. That's amazing.
3:30:08
Uh 300k ARR, how's the fundrais going? It's going great.
3:30:12
We just got completely oversubscribed. Subscribe. Well, congratulations.
3:30:17
Thanks for coming on the stream.
3:30:19
We're bringing in the next team.
3:30:21
Have a great rest of your demo day. Come on down.
3:30:23
We're live from YC Demo Day 2025.
3:30:27
And we have our next team in the building. Hello. Nice to meet you. I'm John. Nice to meet you. Good to meet you guys.
3:30:33
Would you mind introducing your company? What are you building? Yeah, for sure.
3:30:36
So we are building Lumari which is essentially helping go to market teams build tools internally instead of having to buy super expensive SAS.
3:30:44
What what what tools do go to market teams need like yeah golf club buying machine on subscription and state dinner booking. That would be nice. That would be nice. I wish we did that.
3:30:56
But we are helping them like from anything from deal scoring, qualifying leads, making contracts like anything down like the sales pipeline. Got it. Got it. Okay. Yeah.
3:31:05
What what what does the future of the stack look like?
3:31:07
Are you guys going to basic are you trying to verticalize effectively and allow people to build custom software at every point? Every point. Yeah.
3:31:15
I really think we're going to look back to this era of of SAS of like having all these generic tools that you're using and think that was really silly because why wouldn't you have software that's customuilt for your company, for your process?
3:31:26
Um, and so I think exactly that we're gonna start with replacing some of these really point solutions software, but I think in the future, every company's gonna have their own CRM.
3:31:35
What were you guys doing before this? What were we doing? Yeah, I was at Stripe. Sam was at Google. Amazing.
3:31:41
Um, yeah, we were sort of a non-traditional background. Yeah. Yeah.
3:31:46
Who who who's the key uh person actually using the tool?
3:31:49
Is this for a nontechnical person?
3:31:50
It's a nontechnical person within these go to market teams.
3:31:53
Often like a revenue operation, sales operations.
3:31:56
That makes a ton of sense. Awesome. How's traction? Uh, it's been great.
3:31:59
We're at 90K ARR in streaming. Congratulations. Yes.
3:32:02
Uh, obviously we're out of the confetti. Yes. Yeah, we are.
3:32:06
We're pretty much Yeah, we got we got a couple left.
3:32:08
Okay, I'll let you kind of bust it. Yay.
3:32:10
Anyway, thanks so much for coming on this.
3:32:16
Let's bring in the next team.
3:32:16
We have five more minutes, right? Something like that. Let's go. Five more minutes. Let's go. I'm losing my voice. Welcome. Welcome to the stream. Introduce yourself. introduce the company. Good to meet you guys. All over your shirt. Um I'm Yooav. Um and this is Shuria.
3:32:30
We're second time exited YC founders. Congratulations. Thank you. Addicted to startups. Addicted to startups.
3:32:38
We're building third share.
3:32:40
It's agents for in-house legal teams.
3:32:42
And we're starting with media and entertainment companies. Oh, interesting. Very niched down.
3:32:45
Not just like legal AI, but you've actually got You want to dominate a small market? Um, no.
3:32:50
It's a massive market, but we're but we're starting by dominating media and entertainment. Yes. Yes.
3:32:55
So, we're starting by helping media and entertainment companies um find IP infringements. Oh, interesting.
3:33:01
And we collect evidence around it and then that's revenue driving immediately, right? Exactly.
3:33:05
It's a revenue generating workflow.
3:33:06
Is that the is that the business model?
3:33:08
You take a cut of whatever you get or is it more seat based?
3:33:10
We have a software model but we also take a cut of what we get.
3:33:12
So, it's kind of amazing of the apple. I like that.
3:33:16
And we're exploring a little bit.
3:33:17
uh how's track full stack.
3:33:17
You're finding the IP uh infringements and then you're actually sending letter demand letters.
3:33:24
Someday we're going to be a vertical AI law firm and uh yeah there's a lot of we we're handling the entire workflow right now and a lot of it is being done through agents but our customers just think of us as people who get things done and they don't care about how the other like the black box is working. That makes sense. Yeah.
3:33:39
Uh uh what metrics have you been sharing? How's demo day going?
3:33:43
Is wait is this your third demo day then?
3:33:44
Uh it is second demo day. Second demo day. Second demo day. Second coound last time.
3:33:48
Were you co-founders together last time or?
3:33:53
No, we had separate startups.
3:33:53
Different companies finance company for this uh social media analytics. Now we're in legal.
3:33:58
So YC alumni network is strong.
3:34:01
You know, we we teamed up and um yeah, traction's going great.
3:34:03
We just crossed 100,000 AR.
3:34:05
We're working with Congratulations.
3:34:06
We're working with the biggest media entertainment companies in the world now expanding to brands uh doing stuff like marketing compliance. So yeah, that's great.
3:34:13
Well, congratulations on all progress.
3:34:14
Thank you for stopping by the stream.
3:34:16
We will talk to you soon.
3:34:18
Let's bring in the next team. How are you doing, Q?
3:34:19
I like this capital here. TC, introduce yourself. How you doing? I think Solo founder.
3:34:27
We got to give him a hat. A TVPN hat. Oh, yeah. Definitely.
3:34:32
I'll I'll introduce yourself. Introduce here. Perfect. Let's swap. Yeah. So, hi guys. I'm an CEO of QEX. Cool.
3:34:39
We're making a 24/7 uh 24/7 stock exchange. Okay.
3:34:43
So, we're going to let institutions and retail trade traditional assets like US equities and commodities uh real time 24/7 uh without brokers with loads of leverage.
3:34:52
Uh just like you load a lot of leverage, right? How's the traction been?
3:34:58
It feels like it's really hard to underlying uh is this a a sneaky blockchain company?
3:35:03
There's no there's no blockchain.
3:35:05
Um there's no blockchain.
3:35:08
It's completely offchain.
3:35:08
Uh it's basically uh it's like a it's like a crypto exchange but without the blockchain parts.
3:35:13
We've taken those improvements and moved them over to the traditional assets world. Okay.
3:35:16
And the traction is good.
3:35:18
Uh we've been running it oh well uh we've not been running it uh to the YC batch cuz we're not licensed yet. Sure.
3:35:23
But uh uh we been running some internal experiments. Yeah.
3:35:28
Some internal experiments the current YC batch.
3:35:29
And uh due to those experiments we're launching in a couple of months with the with the license.
3:35:33
And uh launching offshore or you offshore offshore in Bermuda. We'll get you Bermuda. Bermuda is a nice place.
3:35:39
You guys have a lot of trips there. Yeah, exactly.
3:35:45
Free rum if you come visit our office. There you go. Fantastic. There you go.
3:35:48
How How do you get into this? Uh I was a quan. Yeah. Tower research before.
3:35:50
Um and my co-founders at Citadel. Well, you're our now. Yeah, exactly. Well, congratulations. Congratulations.
3:35:58
Excited to follow the progress. Great to meet you guys. Cheers. We'll talk to you soon. Come on down. Loads of leverage. Loads of leverage. We love to see it.
3:36:05
Uh, welcome to the stream.
3:36:05
Tell us what you're building.
3:36:08
Wait, were you here last? You were here last time. Were you not? No. Okay. No. Sorry. Sorry.
3:36:11
I thought I recognized another guy. Yeah.
3:36:17
Anyway, introduce yourself.
3:36:17
What do you What are you building? Uh, yeah.
3:36:19
I'm building an AI accounting for small businesses. Okay, cool. Um, h how's it going?
3:36:25
Do you have small businesses on the platform already? Yeah.
3:36:27
Yeah, we have a few small businesses.
3:36:28
Um, we're just trying to automate all of their bookkeeping.
3:36:32
go, you know, chase people down for uh receipts, uh make calls.
3:36:34
I feel like there's so much that's already built into the accounting suites.
3:36:40
Like, do you have to sit on top of QuickBooks or do you actually pitch people, hey, let's rip out what your existing accounting solution?
3:36:46
No, we're sitting on top of QuickBooks.
3:36:48
There's no point replacing the software.
3:36:49
Yeah, we're just replacing the service side of things.
3:36:53
So, consolidating all the scattered data makes sense.
3:36:55
Uh, you know, um, so it's in all different kinds of places, your WhatsApp, your email, your Stripe, everything. doing before this? Sorry.
3:37:03
What were you doing before YC?
3:37:03
Uh, I was building a health tech business.
3:37:06
Uh, we're selling uh AI patient triage software uh to clinics. Awesome. Cool. How's traction been? How's the raise going? How's demo day been?
3:37:15
Yeah, demo day has been great.
3:37:17
Uh, we are raising uh $2 million and uh roughly like three quarters finished.
3:37:22
So, just trying to wrap it up. Congratulations. Classic two on 20. That's funny. Love it. Well, congratulations.
3:37:28
Hope you have a great rest of your demo day. Last one. Bringing it in.
3:37:32
Closing it out strong with What's going on? Sim studio.
3:37:34
Are you simulating things? Yes, we are. I'm simulating. How are you? Nice to meet you. Okay. How you doing? Great. I'm I'm doing great. How are you? I'm great.
3:37:43
Uh, break it down for us. What are you building?
3:37:46
It's a open source platform to build AI agents. Okay. Yeah.
3:37:48
So, it's developer focused.
3:37:50
It's like a Figma-like canvas to build agents. Interesting.
3:37:53
Uh, how many GitHub stars you got? We got to ask.
3:37:55
50 to 4,000 in the last two months. Wow. Wait, wait.
3:37:59
You you and now you have 4,000. Wow. Congratulations. Thank you. I appreciate that. Thanks. Yeah. 4,000 GitHub stars. You love to see it. Congratulations. We got two more.
3:38:13
We got I can't believe Gary let us bring these in. Oh yeah.
3:38:15
He let us clean up after is going to be interesting.
3:38:19
Anyway, uh how's how's traction been in on the sales side?
3:38:21
I I imagine you have a you have a product that you actually sell on top of it, not a nonprofit. Yeah. Yeah.
3:38:26
So yeah, we can't disclose revenue numbers, but we have a lot of great customers.
3:38:29
Um, so yeah, Department of Defense, Lumber, Epic Global, a bunch of names.
3:38:34
So the round's definitely done. Okay. Yeah.
3:38:45
What were you doing before this?
3:38:47
Um, so I was at Berkeley and my girlfriend Let's go.
3:38:52
Let's hear from Berkeley, baby. Right across.
3:38:54
Right across the Go right across the bag. We love it. We love Berkeley.
3:39:02
Yeah, I'm completely covered here. It's everywhere. Well, congratulations. I appreciate it. Yeah, thank you. Yeah, that's great.
3:39:08
What What's next for you guys?
3:39:08
Uh next is just making our customers happy after the the Department of Defense.
3:39:12
Where do you even go from there?
3:39:14
Yeah, I mean just making developers happy, like building the product out more and more.
3:39:18
Um you know, and I think uh you know, developers love us uh and and big customers love us.
3:39:22
So we're just like keeping that energy going, keep launching new products, building the team.
3:39:26
We have a really great like killer engineering team from friends at Berkeley.
3:39:29
So yeah, we're excited to keep growing and keep building.
3:39:31
What's the what's the key value prop for for uh a uh for building platform for AI agents?
3:39:37
Is it like interoperability between different models?
3:39:39
Is it the ability to scale?
3:39:41
Is it just price and cost?
3:39:41
I think the question I have is like uh even last YC batch there was a bunch there was companies with this pitch and I think the challenge is everybody wants to build infrastructure and fixing travels for agents but then it feels like you can build good software but it's it's maybe even harder to get the kind of companies that can build highquality agents that actually have value.
3:40:02
What's what's the secret to like finding even customers that are not just going to sign up but actually get value out of the product?
3:40:08
Yeah, that's definitely true.
3:40:09
I think a lot of people especially right now it's very invogue to adopt AI and so there's a lot of push like top down push from companies to adopt these AI implementations but I think the biggest thing for us is that we're focused on not creating easy abstractions to make it easy to use and I think that's where a lot of people fell short.
3:40:24
It's like you're creating these abstractions that make your platform easy to use but it's actually not powerful enough to to really um put AI into into your production system.
3:40:32
Uh and so for us we're really focused on actually might be a little more like might might be harder to use um but because we remove the abstractions you can actually power relatively complex applications like real world simulations, deep research, data transformations um because a lot of companies are sort of going after the sales and marketing um you know use case and for us we're more focused on the developers and actually production systems. Interesting. Awesome.
3:40:55
How how much is real world simulation like scaling right now?
3:40:59
We've talked to some of these companies and it seems like it's almost like video generation. It feels like very nent.
3:41:04
We really haven't had like this breakout studio Giblly moment for real world simulation.
3:41:08
Like h how is adoption going there?
3:41:10
Yeah, it's actually going quite well. I think um at Yeah.
3:41:16
What are the applications? Yeah.
3:41:17
So the applications of that are essentially simulating like I I guess like one that would be interesting would be like international affairs.
3:41:24
So like understanding how like global events are going to play out using agents. Yeah.
3:41:33
So that's like you know a broad uh topic that we're heard about that with like economic modeling even and like housing prices.
3:41:39
You can actually have agents running and it was always like just like Grand Theft Auto level but now it's like oh what if each of them has like an internal reasoning engine powered by an LLM and has like 130 IQ instead of like turn left I'm running AAR like it's much better. Yeah.
3:41:52
I think the thing that really our our platform unlocked was being able to run thousands of agents in parallel at the same time.
3:42:00
And I think that was one of our grounding the like thesis was that um you know we wanted to create this environment like Sim Studio comes from building simulations of things.
3:42:08
Um so launching you know 10,000 agents at a time and perhaps some of them are going to come back and give you an accurate result or some of them you know might inform you in an interesting way and so you take those aggregated results and you go do something with it. Very cool. Yeah.
3:42:20
Thank you so much for it was a pleasure. Thank you for having me. Great. Fantastic.
3:42:23
And that is the end of our demo day stream. Tune in tomorrow.
3:42:30
We will be back in Los Angeles tomorrow live from Ultra. Yeah.
3:42:33
Thank you to Combinator team. Fantastic.
3:42:36
We're San Francisco's back. Gary Tam's back. He He never left. YC never left.
3:42:42
But the Rosewood is back.
3:42:44
It's It's just a fantastic time in San Francisco.
3:42:47
Fantastic time to be here at YC Demo Day. Thank you for watching. We will see