This Week in Startups - Neurosymbolic AI outperforms chatbots and product search | E2327

Starting point is 00:00:00 LLMs are not good at this. They regress to the mean and they find the most probable thing and that's often not what you need personally. When you need to remove hallucination and you need trust, you need to be able to see inside the model, that's where neuro symbolic models can really shine. You really have built something between Howes and Pinterest that is more powerful than both of them. The performance of it is already 2.5x greater than some of the largest search companies in the world. It learns that new information. So you don't have to go do another training run.

Starting point is 00:00:27 It's literally updating in real time. It's one-one thousandth the cost of an average Frontier Model Training run in the U.S. This week in startups is brought to you by YSECurity, the on-demand security team for startups. Need enterprise-grade security without hiring a $400,000 CISO. Security gives you 40-plus expert engineers matched to exactly what you need by the hour,

Starting point is 00:00:46 with your first six hours completely free. Go to yissecurity.io-slash-twist. Agree.com. Stop chasing invoices and automate your entire contract to cash stack. Go to agree.com and tell them Jason sent you to get 50% off for life. And Vanta. Compliance and security shouldn't be a deal breaker for startups to win new business. Vanta makes it easy for companies to get a SOC2 report fast. Get $1,000 off for a limited time at www.v.vante.com slash twist. We got Zach Hudson joining us. He's the CEO of Onton. They're a search

Starting point is 00:01:16 and discovery engine for e-commerce. It's power, Jason, by a neurosymbolic AI model. What does that mean? You can see it for yourself at onton.com. We're going to find out right now. Zach, thank you so much for joining us. Thanks for having me. Yeah, and you can give us a demo, so let's, you know, show, don't tell. Oh, yeah, yeah, yeah. And what have you built, yeah. We can dive right in. Let's do it.

Starting point is 00:01:37 Oh, and we're investors in the company, just as a full disclosure here, yeah. I'll give your audience a chance to go and do some basic searches for themselves, but why don't I jump in and do some more of the mind-blowing searches? And a little bit of background about Anton. We have these things called surfaces within our product. If you've ever, you have, Lon or Jason, have either of you used, notion before. I'm sure you have. Plenty of times.

Starting point is 00:02:01 More than once. So they have these things called blocks there. They let you organize information in different ways. People do this quite often in shopping journeys, too, where they create lists. They create mood boards, these types of things. These are surfaces within Anton. And so what I've prepared for you was I put together some of your favorite things, Jason, or at least some of the hotels that you've mentioned.

Starting point is 00:02:21 Some of the things you mentioned were... We sent him some cheat codes, Jason. Monicle magazine, a few hotels we know you like. We helped Zach build this for you. I went back through some of the podcasts. I grabbed a few others. But we put this into a canvas. But what we've realized recently is it wasn't possible to search these without this model.

Starting point is 00:02:41 And so I want to use this to demonstrate what ontology one can do in this, the amount of context these models can take. So I'm just going to go search with it. I'm going to use this just to go, hey, try to find some stuff. Okay. So you put images on a mood board of. hotels I've stayed in and the design of those hotels. So I saw one of them there look like the room at the artisan in Singapore, yeah? And I put even more than that. I put actual products in here. I put some text and other contexts in here. And ontology is able to suck all of that up. So it's good,

Starting point is 00:03:15 it's, it is a lot like a mood board. But ontology one will look at that whole thing and it will try to understand it. The thing that I want to call out here is that it's learning in real time. We don't have any tags for these things. We don't have any, this wasn't like human labeled. It is going off and learning them, but more importantly, it's storing that understanding in the model. So every next search that's happening with Anton is getting a tiny bit smarter and a little bit faster, which is incredible. We don't have to go back and do another training run with this model to get better accuracy. So it's learning about things like organic, burlwood, brass, floral, all the things that it thinks goes into this.

Starting point is 00:03:52 And in my opinion, these look pretty accurate or it look like they could belong in some of these hotels. I can almost one shot the room that I'm going for, which is a lot more like how e-commerce search actually works, right? You have a chair and you want that chair to match the lamp or you have the lamp and you want it to match the other parts of your room. Ontology can do multi-category multi-object searches. But more importantly, it can be honest with you. It can tell you exactly why these results came back. Definitively, I can look down into the model. It's not a black box, like a typical LLM, and see why these results came back. So it can be honest and explain these things. But I could take this, and I could throw this product back into this mood board, and I can

Starting point is 00:04:34 use this to recursively search. So I've plopped it in here. I could see how it looks. So you put a Cambridge love seat here in the 1930s Hollywood style. Only 16,000 lawn, so this might be right in your zone. It's out of my budget, but maybe in y'all's budget. But I can recursively search with this. So I've now updated ontology's understanding.

Starting point is 00:04:57 I could go do another search. But just to show you what else this could do, I can, I prepared one more for you. I've taken one of your friends, Jason. She's a lot on a sweater. Throwing, maybe this meme is already dead. I know new cycles are pretty fast these days. But I can take this one and I could also search with it.

Starting point is 00:05:15 And let's just drag it into the search bar. And let's see what comes back. But actually, let's augment it. Let's say couches fit this vibe of these AI generated. And the vibe being Chimots oversized white. Chimots huge. Oversized, creamy, off white, oversized, chunky knit. It's learning these concepts in real time, which is incredible.

Starting point is 00:05:36 So I think this is what ontology can do. This is what ontology can do. And it's getting smarter with every search. So it's literally learning these concepts. So we're really excited about it. And the performance. of it is already 2.5x greater than some of the largest search companies in the world. We have a smaller index size. So I can only imagine where it, or excuse me, yeah, I can only

Starting point is 00:06:01 imagine where it goes once we start adding some new categories. Who's your customer for this? Obviously, designers, consumers, everybody wants to find that perfect object to put in their room, et cetera. And then also people want to build a new product. So I was looking at this thinking, hey, what if I want to get custom furniture made or I'm a manufacturer? And I say, here's the Blade Runner apartment that I love. I'm a big fan of Deckard's apartment. So can you get a picture of Deckard's apartment and the Blade Runner set and then make me a blade runner, find me Blade Runner-esque, you're not an aesthetic?

Starting point is 00:06:45 You can definitely do this, Jay's. I'm going to share my screen. I did this just to play around with Anton with Twin Peas. And it's been, it, so you can see, I just put in a bunch of images from the TV show Twin Peaks. And when you search, it can find anything like rustic, it knows about rustic decor. It knows about, you know, like, oh, you're looking for surreal or weird things. Like, it's actually pretty good. So if I just put, like, items for a Twin Peaks living room.

Starting point is 00:07:14 Or a bar, you know, you could make, like, a restaurant that looks like Twin Peaks. It's really cool how it's sort of understanding. like it's like vibe search or aesthetic search beyond just like items or words you're putting in. This is a problem. Like taste is so beyond what, and you've talked about this endlessly long, just like, can't make jokes. It doesn't have taste. Right. Zach, have you cracked essentially taste here? I think a lot of people bundle a shopping journey into two categories or into one thing. And I think it's actually a lot more nuanced than that. I think there are wants and needs. Needs are like toothpaste, deodorant, the things.

Starting point is 00:07:50 that you order very quickly. They're often commoditized products. But there are a lot of other products, broadly speaking, they're above $50. And they're driven by totally different things. Taste is one of them, self-expression, emotion, imagery. LLMs are not good at this. They regress to the mean and they find the most probable thing and that's often not what you need personally. So what this model is capable of doing is it's capable of learning about you too. While it's learning from searches today, it can start to update itself to where the search index reflects the things that you really enjoy in a very different way. So it's not like there's just one output that is the most likely. It is, it's creating its own separate understanding for, for every search.

Starting point is 00:08:34 It's learning that new information. I've got a question. Check this out at onton.com. O-N-T-O-N-T-O-N-com. We invested back in 21, 22 during COVID. And this was a search engine. This is pre-chat GPT. The world caught up with you in some ways in terms of AI, and you've now got millions of people doing searches, yeah? That's right. Yeah, we're on track for hundreds of millions of searches over the next year, and that's only in one category. So as we move into others, I would expect that to multiply pretty quickly. What's the revenue model now for the business? Five years in here, six years in? Yeah. So we do make some money from affiliate commission, but I think our largest revenue opportunities are in front of us.

Starting point is 00:09:13 We're releasing an API of ontology to be plugged into all these stores. And I think there's the reason why there's an API instead of, say, a Shopify plugin is because we found this model to be generalizable. It can be applied to use cases beyond just e-commerce too. But obviously, that's where we're starting. That's our bread and butter. So that's how we're making money, but we have been really focused on user growth. Everything is moving a lot faster in the age of AI. But moving fast often means taking on more risks. Every time your company adds a new tool or a vendor launches a shiny new integration, that's one more opportunity for something catastrophic to go wrong. No one wants to get left behind, but you still need to worry about security. It's kind of job one. That's why

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Starting point is 00:10:46 and you just charge them based on consumption, yeah? That's right. Yeah. Interesting. Is another product category coming? Apparel is coming next. We see tons of searches for apparel right now that we're not fulfilling. Electronics is probably the next category after that, which should be surprised.

Starting point is 00:11:02 I think what is fascinating about ontology is that as it learns about one category, it makes the next category smarter, right? So as we learn what polyester is in, say, home decor and furniture, the search engine gets better at understanding what polyester means for. something like apparel. And so it makes it a little bit easier for us to move into categories than what's historically been the case with e-commerce where you have to set up the whole, you have to set up everything.

Starting point is 00:11:28 You have to go through, you have to relabel all the products. You basically have to build your understanding of that category before you move into it. I was going to say on this week in AI, this week we had ISO-Contin from pool side. And he was talking about how they're pursuing coding models as the root to AGI, like teaching. If you make a model perfect at coding, event. eventually it'll become super intelligent and self-aware. I'm curious, do you feel like neurosymbolic models could one day get there to? Because you are kind of teaching the model about our world and sensory experience in ways that a coding model is not. That's a really great

Starting point is 00:12:03 question, Lon. I think there's a lot of use cases for large language models. I'm not saying they're not useless. But they are great at certain categories of things at a certain scale. They're, in my opinion, they're great at verifiable domains. Coding is one of of those. Mathematics, you're starting to see them break into mathematics because they have verifiable, you can use things externally to verify the output of those large language models. But when you need, when you need to remove hallucination and you need trust, you need to be able to see inside the model, that's where neuro-symbolic models can really shine. So I'd say the other three benefits are, it's less expensive. The cost of this model to outperform those search companies that I mentioned

Starting point is 00:12:42 was one, it's one-one-thousand-the-cost of an average frontier model training run in the U.S. which is incredible. It learns that new information. So you don't have to go do another training run. It's literally updating in real time. And then the final thing is probably trust. So I think at a certain scale, this model could replace some of those things. It can do things.

Starting point is 00:13:01 Like I think at a certain scale, all models can actually be pretty great at a lot of tasks. But the question is, is it the most efficient model for the job? And neuro-symbolic models are quite a lot more efficient at certain tasks like the e-commerce. Law and I just put in like, I got the actual image of the In it. I think it's the Innis house in L.A. That was a Franklin Lloyd Wright. Yeah.

Starting point is 00:13:26 And I almost bought this house, by the way. My wife stopped. Well, it was only going for like $4 million. I feel like if you own a Frank Lloyd Wright house, you have to like let people in it to look around, right? Like you kind of, well, that was one in. You own a piece of art now.

Starting point is 00:13:41 Well, and it was, so there's that. Then you also, Zach, had to restore it and all these tiles that he made, you would have to go source. And it turns out Ron Burkle, also a fan of a headrunner and real estate, the billionaire, bought it.

Starting point is 00:13:58 I think he spent like $15 million renovating in. And then I don't think he sold it. I think it's now part of like some sort of... Wait, is it trust? Yeah. I think I think you're right. I'll look at it. Yeah.

Starting point is 00:14:16 If I remember the history correctly, so when I was like starting to look at it, it was like, yeah, this is not going to work, son. You're going to need to spend $10 million for a two-bedroom house that is totally the opposite of kid-friendly. It's totally dysfunctional house, but it was,

Starting point is 00:14:31 this is like a really powerful solution that you've come to. Is this now a small, like a small language model that you own and is proprietary? Or is it like more like a harness when we think about it? as a business and the IP here. What is it that you actually own here? Yeah. This is a fundamentally different type of model. So the way that you can think of a large language model, or actually to oversimplify the brain, you have like two halves of the brain, right? Maybe an intuitive side and a logical side. LLMs are kind of like the intuitive side of the brain, but it's when you apply a logical side to the brain

Starting point is 00:15:06 that you really start to unlock the intelligence of it. Some people, psychologists sometimes talk about this. It's like systems one versus systems two thinking. LLMs are great at Systems 1. So this is literally a completely different model. It's a union of a couple of different things, but we do have a lot of things we've built in the house to make this work, including a graph database that stores a lot of this information, and it stores information in a very different way. So yeah, it's a, it's a completely new approach. I wouldn't even call it a small language model. You could scale this thing up a lot. Really super fascinating. And it's great. It's one of the amazing things, Lon, about when you invest in smart people, you know, especially when you're like, we're super early stage. I'm not sure exactly. You went through the accelerator. Then we put a little extra money in. I mean, this was years ago. And I've been like, wow, I wonder what's going on with Anton. And like, you guys just grind it and grind it and grind it and figured it out. But you, if my investment philosophy is passionate founders who are gritty and figure things out and are passionate about that space. So they're not going to give up. And here we are.

Starting point is 00:16:11 This is an incredible product. What's the future of the company, do you think? Yeah, I think we're launching that API for a lot of reasons. Like, there's this great quote from Sam Martin, quoting Paul Graham, that says, you should always create an API no matter what good things will happen. And we can largely think the Cambrian explosion of AI products that happened from that. It was around GPD3 that they launched their API, and you see all the opportunities that develop.

Starting point is 00:16:41 So we see a very similar path for this model for our company. Yes, we do still want to be the starting point of every shopping journey. Actually, let me kind of reframe this differently because I think the shape of companies are changing right now. Previously, you would be a product company and you would have a technology that would really, you have a technology that would help you reinforce that strength. I think companies are kind of becoming a little bit different now, especially with the AI labs. You have a model that is good at certain tasks, and your product is a reflection of what the model is good at. In our case, we have a neuro-symbolic model that is great at e-commerce and all these trustworthy searches where you need accuracy.

Starting point is 00:17:19 All the other AI companies that are using large language models. We could take OpenAI, for example. They have a model that was great at conversation, so they launched ChatGBT, BT, and now they're starting to see the ability to do code, so they launch Codex. So I think the structure of companies is changing, and Anton is no different. Amazing. I'm just like now I'm totally distracted, putting in Tyrell Corporation. It's fun to play with. Notably, the Ennis House, it is featured in Blade Runner.

Starting point is 00:17:50 It's neo-Mayan architecture. It's in Los Felis. It was memorably in the 1959 horror classic House on Haunted Hill, Jason. That's the other most iconic movie. And that's one of the reasons it fell into disrepair. that movie came out in the late 50s. It was a sensation. And kids would then go find that house and scream and carry on outside because it was in this big horror movie. And so people, nobody wanted to live there. And so in the 60s, it fell into abandoned disrepair. Isn't that interesting?

Starting point is 00:18:18 Well, and to show you the, to show you the depth of this and how crazy it is, I was watching this incredible show on, I don't know if it's HBO or if it was Apple TV, but I'm watching Seth Rogan's show The Studio. It's Apple TV. Apple TV, thank you. And it turns out, and I was like, I said to my office, that the Ennis House that we wanted to buy. And the production team behind the studio looked to, writes, Mayan Revival designs for the

Starting point is 00:18:47 company's headquarters. And so look at this. In this image, you see the Mayan tiles. They're not exactly the same, but you're like, why is this so iconic? And there it is. That's the Ennis House. That's the studio conference room. And it's just super fascinating to me.

Starting point is 00:19:09 And this is the interior of the NS House. That's the walkway. And here is, you know, this, like, famous scene with Ron Howard and Seth Rogen. And they did this. Now, if they had Anton, my Lord. They could be gone even deeper on this. So I think for Agree is the number one fastest way to go from contract to cash. And right now, they're offering an exclusive deal just for Twist listeners.

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Starting point is 00:20:05 to get around to paying you. And that's if everything goes right the first time. Agree moves all of these tasks into a single platform. So you can get everything signed, sealed, delivered, start billing, and finally get paid. If you want to stop chasing invoices all day, go to agree.com. And then if you tell them J-Cal sent you? They're going to give you 50% off for life. Do you have like an outreach program to designers to kind of get in here? And I think saving the mood boards, you know, you call them something else, but I'll call the mood boards to the audience. Sure. That's easier. The canvases, the mood board canvases, like this feels like it could have a Pinterest-like workflow where you could get designers, Kelly Wersler, a friend of mine, or any. And, you know,

Starting point is 00:20:53 any of these folks to start making canvases here? In fact, Ron, can you make sure we get this to Kelly? Sure. And do an intro with Zach and Kelly, because she's gone crazy on AI. Yeah. You know Kelly Worcler, I'm sure, Zach. I know someone who knows her very well. Let me put it that way.

Starting point is 00:21:07 That's how you know that person is please in. I know Gallis. Anyway, you know, she has her own studio and, you know, like this whole warehouse and everything. And she's just obsessed with AI. I think you should get some of these, like, iconic folks as advisors to the company have them start making their own mood boards. And I think taking the next step,

Starting point is 00:21:28 which is I want to make this product in the world, that's like another interesting angle. Like, what can't I find that I could manufacture? So there are all these interesting people who like to manufacture products. So what this could do for furniture for decor is just unlimited. You really have built something between house and Pinterest that is more powerful than both of them.

Starting point is 00:21:57 And that would create a sharing. Like if I could share, can you share the canvases? You can. Yeah, they're starting to be public. We're going down that exact same line of thinking. What I like about that one, Zach, by the way, is it creates a viral loop. And, you know, this is when you go to market law, and one of the tactical and practical things that founders sometimes forget, which is,

Starting point is 00:22:21 what if one person who uses my service introduces it to 1.5 people or 2.6 people and then gets in a search engine, oh my lord, then the site starts growing while you're asleep. I think one other thing I would say about that, though, is while it does help with a viral loop, the LLMs and these AI companies are cannibalizing the data that they rely on for training. Like you see think about how many bloggers, wirecutters, these types of posts that used to exist in the world are disappearing because there's no incentive to write them anymore. They're just going to get sucked up immediately. If you don't build content into your product, if you don't build user generated content into your product, you have nothing to train on or give these recommendations. Super important for e-commerce. That's why we started doing it now, but it's also super important to think about for a lot of other categories of searches. Yeah, I just am thinking about the number of pages. that Google has for Anton that are, yeah, I wonder like how many pages you actually have in there and this is super interesting. Do you get a lot of search traffic anymore or is that game over? You know, I don't think that, I know people are talking about AEO a lot. We invested a lot into

Starting point is 00:23:39 SEO and it still continues to drive users over to Onton. Wait, what was the term you used? AEO. AEO, Answer Engine Optimization. Other people call this GEO is the other one, generative engine optimization. People go back. In my opinion, it's largely the same thing. They're using existing search indexes and they're putting LLMs on top of it. So the things that worked for SEO kind of still work for AEO and GEO, it's almost more of a wild west than it used to be.

Starting point is 00:24:06 But you do have to think about how people query these things differently. Like the queries aren't just keywords anymore. They're much more long form. So that's the only difference between SEO and AEO, in my opinion, on how you're creating content. It's still all about Wikipedia and Reddit, it turns out. If you rank well in those sites, you do well no matter what. Exactly. It does create some signal. I did see somebody create a fake product. Somebody created a fake brand, a fake deodorant brand. And then they got the LLMs to think it was real. And within like three weeks, they had chat GPT singing the praises.

Starting point is 00:24:48 of a fake deodorant brand. So AI slop and what is that term they use, Lon, for like the moment the web went from human to... No, in shittification. Insidification is one. It's true. Right. That's like with products deprecating. But there's another one, like the human created web then giving way to this non-human web

Starting point is 00:25:10 where there's a major problem on Reddit right now with AI slop going in there. And this is where we're going to just have to make a decision of the human web versus AI slop. Do you have thoughts on this, Zach? And what we need to do? This is why we built Ontology 1. Like, we put LOMs on top of e-commerce data, and it would hallucinate all the time and come back with products that were completely irrelevant. E-commerce data is so bad because it's been gamed for so long.

Starting point is 00:25:39 And just imagine how that's going to compound. So that's why we built ontology. I really don't envy the position of a lot of. the social companies right now. I know Reddit is dealing with bot attacks constantly. We're dealing with bot attacks and AI agents that are going after Anton regularly. It's a big pain point. Jason, I think you may be thinking of the dead internet theory, the idea that over time bots will take over and there won't be any human created content left to find. I think we already hit it, but it's the, yeah, when automated accounts and AI slop

Starting point is 00:26:16 outnumber the traffic and our content. I think you already see this most prominently in comment, threads, and replies, where once there used to be robust conversations, after almost every piece of content you could find, and now it's almost always a bunch of bots talking to each other, overwhelming human participation. This is why I charge $1 a month to reply to most of my tweets. I have 2,200 people out of my 1.5 million followers, so 1% would have been... I'm one of them. 15,000.

Starting point is 00:26:47 So I think I have 10 basis points on my follower account who pay a dollar a month. I give it to charity. And I'm increasingly thinking I'm just going to give it back to people randomly. Like I'll just pick one of the, I may just pick one of the followers, 10 of the followers. Now for X money, you could just easily do that. That's right. And then it's just like, okay, you're, I mean, I might get then maybe one of these organizations is going to come to me and say I'm creating a gambling multi-level marketing scheme. Because if you put a dollar in, you have a chance at $2,200 every month.

Starting point is 00:27:19 You're going to be the Bernie made-off of X money, yeah. Of the people that pay, are there still bots? No. Do you see? No. There are MAGA lunatics who think I'm a Libtard, and there are libtards who think I'm a MAGA lunatic. And I told them, you can insult me, you can flame me. If you give the dollar to charity, I'm all with it.

Starting point is 00:27:45 It's totally fine. Zach, continued success. Everybody check out ontof.com. Thank you. A very cool product. Today we're going back to space, my absolute favorite place to build. There are so many startups

Starting point is 00:27:58 that are doing interesting things in our local orbit and in our solar system. I love talking to all of them, especially right now. In the wake of the SpaceX IPO, I feel like a lot more people are paying attention to space.

Starting point is 00:28:08 So it's a great time to sit down with the founder building something I think we're really going to need and not many people know about. So please join me in welcoming Ashi Desanaika to the show. She's the CEO and co-founder over at Spacium. Ashi, how you doing?

Starting point is 00:28:20 I'm really good. Thank you so much for having me here. I'm so glad because we get to talk about a pet topic of mine that I really love, which is in orbit or in space refueling, which I think is really cool and really matters, but I think a lot of folks don't know what it is and why it does matter. So could you start by just giving people kind of the basics as to why this is a problem that needs to be solved now?

Starting point is 00:28:42 Yeah. Okay. So space industry, growing rapidly. And we see so many space companies coming up with like OTVs, moon missions, launch vehicles, and all these missions and all these spacecrafts are currently limited by the amount of fuel they can carry. So which compromises on the payload, how much payload they can carry, how much further they can go in space, they can't do crazy manuals, they can't change orbits. So that's what we are solving because it's like, just think of us like a service station here on Earth,

Starting point is 00:29:12 but in space because when the highways were built and like on earth you need fuel to go from one corner to the other side of the city right like oh from l.A to New York you need you need fuel but that's exactly what we need in space as well so to go from place to place you need fill and right now all these spacecrafts are launched by the exact amount of fuel they need for the mission and to replace with fill you need to compromise on the payload or you need to to compromise on the range they can travel. So that's where we come in and we basically give them more options. So now they can travel further, carry more pay loan. Here's a nightmare scenario for any unprepared founder. You're about to close a huge enterprise deal and suddenly the legal team

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Starting point is 00:30:42 It needs to close big wins without sacrificing your runway. Head to yosecurity.io slash twist. The first six hours of consulting are free. That's y-security.io slash TWI-S-T. The flexibility point is very interesting. I hadn't thought about how the fuel load would be exactly tied to the target mission. But if something goes wrong and they need more fuel, what do spacecraft do today to compensate for that crisis? Right now, they just have to scrap that.

Starting point is 00:31:09 whole mission and send an A1. So, yeah, it's, and it's not just about missions going wrong. Even the missions that do go well, they're currently being compromised. So what types of fuels do we need to have in these future orbital gas stations that we're going to have? Because I know there's a variety of propellants used in space. And I'm curious, which ones you think are the most important and the ones you're going to target first?

Starting point is 00:31:31 That's a really good question. So I'm going to give a bit of background. So we are doing two types of fuels. So we are doing storables as well as scratchy fields. So storables are xenon, krypton, hydrozine, and chiroginics are the ones that have to be stored at really cold temperatures, like minus 190 Celsius or minus 310 Fahrenheit. So that's really cold. So that's liquid oxygen. Yeah, that's, for an example, liquid oxygen.

Starting point is 00:31:55 So if you don't store these fuels at these really cold temperatures, what happens is the temperature increases and you basically have to boil off, like, which means it's like water. Like, it boils off and then you have to vent it out. Otherwise, we are going to see an explosion. So you paid all that money to get it up there, and then you have to slowly release it if you can't keep it at the proper temperatures. That's terrible. Exactly. Exactly. So that's something we cracked. During YC, we went through summer of 1024.

Starting point is 00:32:21 We went through YC, so me and my co-founder, we cracked that problem. We built zero boil off technology, fuel tanks. So our first idea was before we even got more customer demand, we were solving for crashing. We were solving to store and France's a crazni fuel. because that's what the initial demand we got from our customers. So that's why we saw the zero bylaw of technology. And then we got reached out by other customers who were wanting like water or xenon. And so then we decided, okay, now we had to be more fuel agnostic.

Starting point is 00:32:52 So we are going to do as tourables as well as Krijinik fuel. So our initial customers or initial stations will have Xenot. And then those customers are also moving into Krijin's in the long term. So, yeah, we are fuel agnostic. So you're going kind of both ways then, both the fuel you have to keep cold than the fuel you don't, simply because customers want both. Do cryogenic, do fuels that need to be kept cold have a different use than fuels that are less temperature sensitive?

Starting point is 00:33:18 Are they used for longer flights or shorter bursts? How does that break down? Yeah. So it also depends on what our customers, the other space draft, their mission is, right? So with cryosophiles, you get more energy. So that's the basic idea. So for an example, if you want to go to the moon, they mostly use garage. fuel. So we have customers who's asking for like 10 metric tons of

Starting point is 00:33:41 hydrogen fuel because of their moon mission. Yeah. So because of their moon missions. Just to be clear, Ashley, we're talking about bringing all this up from the planet surface to orbit and then you're going to provide it, but we're not manufacturing anything in in space yet at that quantity. No. No. Wow.

Starting point is 00:33:57 That's a lot of weight. That is a lot of weight. That is a lot of weight. Yes. Okay. Before we get too far into the weight point, I want to ask about electronic propulsion. Because I think probably folks listening to this, I've heard about the use of electronic propulsion to do some in orbit maneuvers. So why does that fail to meet the needs of customers that are coming to you for cooled or just kind of gaseous liquids?

Starting point is 00:34:18 Yeah. So electric proportion, like, we think electric proportion can also really benefit from refueling. So it's not like, oh, electric proportion is not going to work. It definitely works, but they will benefit from refilling. So electric chemical, even nuclear proportion, you benefit from refueling. Because now they're building nuclear proportion. and he has spoken to some companies and who thinks they will need refueling

Starting point is 00:34:42 even for their nuclear propulsion systems as well. So it's not just one type of proportion system won't work. It's because they can get more benefit from being able to refill. Let's talk about launch costs because I was talking to the folks over at StarCloud, a very cool company. They want to build in orbit data centers. And the CEO was like, look, our entire company is a bet on launch costs coming down. If Starship and New Glenn don't work, then we don't work because the economics don't pencil out.

Starting point is 00:35:10 I'm curious about what needs to happen to make it feasible to bring up those 10 metric tons that you mentioned earlier of fuel. Because I think right now, if we did it all with Falcon Nines, it would take a while just to get that one set of material up to orbit. So do you guys also depend as much as other companies on heavier launch vehicles coming to market? No, not really, because our initial customers are simply like two metric tons, five metric. metric tons. So we have that capability currently to actually send the amount of fuel we need. But yes, when we have to scale up more, like 10 to 30 metric tons of fuel, yes, then we will have to depend on heavier launch vehicles where we can send more payload to space. But we are not depending on Starship or New Glenn for our business planet work because right

Starting point is 00:35:58 now everybody launches and where we actually give value to our customers, how much they can do once they go to space, once they are in it. So that's when we actually give them value. They can go from Leo to Geo. I watched your session with Tom Mueller, where he mentioned, like, for their helios, they could, if there was a refueling station, they could get more value out of their helios from Leo to geo. That's exactly what we are providing. So we don't really depend on the launch vehicles, like launch vehicle cost. Well, but it does improve your economics. I presume that if we had lower launch costs, then it's a tailwind, not a glass wall. Exactly.

Starting point is 00:36:38 Because at the moment, like, we all pay the same amount for the launch. And also our technology allows us to store for longer periods of, to store fuel in space for long periods of time. So that actually benefits. And that's your zero boil off. Zero point off. Yeah. Exactly.

Starting point is 00:36:57 And also we can store like for xenon as well, we can store for longer periods as well. That's fantastic. Okay, so quickly, before we get into what you've built and how it's performing up in space, to me, this sounds like a piece of work that will apply equally to both commercial and defense applications. One, is that correct? And two, where are you seeing the most early demand? You mentioned customers earlier.

Starting point is 00:37:20 I'm curious where they kind of fall on the commercial defense continuum. Yeah. So we see demand from both sides. So we don't just see the demand from the, defense side. We have like all our customers right now are commercial customers. Oh, interesting. Yeah, because like YSysi says, build something people want. So we actually wanted to make sure we have people who's going to buy our product. So we iterated so much with what our customers want. So we would build something and then we would always get feedback. And then if they don't like it, we would change it.

Starting point is 00:37:55 So so we got like over the last two years, we got so much feedback in terms of hard. in terms of type of fuel in terms of how hardware should dock their spacecraft or how much risk they're going to take. I'm blown away by how faster a company has moved. You went through YC and, oh, I forget, was it 2024? Yeah, summer.

Starting point is 00:38:17 Yeah. So summer of 2004. And you've already put some of media into space. You've already done reiterations, a bit of technology. But when I was growing up, space was slow and hard. And it took forever to do anything. And you're thinking about, you know, like multi-decade NASA contracts.

Starting point is 00:38:30 and, you know, cool stuff. Like, everyone loves the James Webb Space Telescope, but like, oh God, did that take a while? So what's changed that allows, and I say this with respect, a scrappy startup like Spacium to do so much so quickly? Yeah.

Starting point is 00:38:44 So me and my co-founder, we love space. We are like, we, that's what we leave for, to Spacium, to send pillows to space and to build this rooffilling station. So we built our first pillow

Starting point is 00:39:00 in fine, months, just the 12th class in five months. And it was the most accurate robotic actuator ever tested in space. The way we did that was obviously obsession was big part of it, like, because we never felt like we are working. It was just every day doing something we love. And also we brought all the testing in-house. So our iteration cycle was really quick compared to how space industry usually works. So we brought all the testing in house. We do 98% of the testing in-house. We do 98% of the testing in-house. So we build something, we test, and if we test it until it breaks, and then we improve on it. So that's why we were able to, like, do so much with so little time.

Starting point is 00:39:40 When it comes to, you know, the fast iteration of building something testing, improving it, building it again, we're going to talk about your robotic actuator in a second, but this is a piece of physical technology. So do you guys also have, like, in-house milling machines and all the necessary tools to quickly prototype and iterate? Yeah, we do. We have T-R-R-R-R-Ring. We have vibration beds. We have like... And you can do all that with two people.

Starting point is 00:40:04 We did that with two people for the first mission, but then for our next missions coming up, we are growing. Now we are a growing team. So it's not two people anymore. I was going to say, like, I mean, someone has to like,

Starting point is 00:40:14 into the trash cans, do the payroll. Like, I mean, there's a lot of work to do just to keep the business from falling off a cliff. Yeah, yeah.

Starting point is 00:40:20 Let alone do it all that. Yeah. It's not anymore. So we, it was, we had like, we have so many fun stories about what happened during our first mission because it was just the two of us and it was like crazy.

Starting point is 00:40:32 We have one of our advice since he was one of the early employees as SpaceX. And at one point, because we went quiet, like we did not reply to him. And then he was so worried something happened to us because it was the two of us building pillows. And he was like, where is she? And res are like, we don't know where you guys are.

Starting point is 00:40:49 And we were fine, obviously. And we were fine. But then after the first mission, we started hiring now. We have amazing engineers who are. also equally obsessed. How big is the team now? We are seven people. We also like to keep the team lean because it helps us move faster because then we don't have a lot of bureaucracy and we don't have like everybody owns their piece in the fossil and then moves forward. Yeah. No, I've heard that from software entrepreneurs, robotics entrepreneurs, space entrepreneurs. Every single person is like we want

Starting point is 00:41:23 to have the minimum viable team accelerated with as much technology as we can. So that makes good sense. Let's talk about your mission, though. So you were on a rocket last December, and then this February you announced that you, quote, flew the most precise robotic actuator ever tested in orbit. So what does that mean? And why does it matter for in-space refueling? So robotic actuator is what goes into our robotic arm. So with that precision of the actuator and exactly end of the robotic arm will be, we'll have a precision within 0.5 millimeters. So with that type of precision, we can dock to the incoming spacecraft so precisely, and it reduces

Starting point is 00:42:03 the risk for all our customers. And then we start the refueling process. So that's why that type of precision is so important, because if we can't dock to the incoming spacecraft precisely, it's going to be a huge disaster, basically. Are the tolerances that fine for docking onto a spacecraft? Okay. Oh, yes. Okay, why?

Starting point is 00:42:24 And this is just pure ignorance leaking through here. But it doesn't make sense to me that it has to be that precise, given that we're talking about a thing and then, you know, like, why can it just like fit once it's like attached? What do you mean? Why can it fit? Well, you know, like go back to Apollo 13, the movie, right? When they're trying to like put the thing into the Connectureport,

Starting point is 00:42:45 like it kind of like missed and kind of like hit and it could slit in. Why isn't there a little more tolerance to the linking of your future space station refueling facility and the spacecraft? What drives that lack of tolerance? Yeah. So if you can't dock precisely, it really increases the risk for our customer. And that's not a risk our customers are going to take. So this is another feedback that we got from our customers.

Starting point is 00:43:10 So are our spacecraft just less tough and durable that I'm imagining? And therefore, you have to treat them very, very carefully. And therefore, the tolerance is also fine. That's also a funny part because we, build cars to be really robust, right? But we build space props. They're like little babies that we can't even like do anything. Like if something goes wrong. And also in space, we don't have humans on board. So if something goes wrong, we don't have, usually we don't get a second chance to fix that. And so that's why we want to make sure everything goes smoothly. The first time,

Starting point is 00:43:47 very less risk. Because with risk, like, it's like a chain of events. Like more things can go wrong. Okay, so you got your actuator up in space. You showed that it works. What is next for the company as you work towards building your first actual facility that can accept fuel and disperse it? So we have a Xenon fuel transfer. This is the first time I'm saying this out loud. So, yeah, you guys are the first to know. Thank you.

Starting point is 00:44:14 We appreciate that. Yeah, of course. We have a mission coming up really soon within the next year also. So we'll be transving Zon in Obed. And then we have another mission coming up within the next one and a half to two years where we have a free-flying spacecraft and we will be docking into another spacecraft

Starting point is 00:44:32 and we also crossing Xenon in orbit. So those two missions are coming up and we are fully funded for those as of right now. Fantastic. Now, demand for in-space refueling is not a hypothetical, it sounds like. It sounds like this is a very acute need now, essentially. Okay, cool. Because sometimes you build ahead of the market,

Starting point is 00:44:52 sometimes you chase, you know, what's needed. But it sounds like the moment you can get this up and running, you're going to have business. Exactly. I have heard from like bigger companies. They're waiting until someone actually put their stations up there. And then they will start building their technology around refueling. But so it's just kind of like chicken and egg problem. And also we do have customers who spring and take that risk and actually get, you know.

Starting point is 00:45:20 I'm really excited once we have this technology. think it's going to make everything so much easier and less unfault tolerant. And then hopefully you can go more robust things and do more stuff and get back to the moon. And then I can go to space too. It's going to be fantastic. So I did talk to a company called orbit fab a while back. And they were talking about their kind of like standardized enterprise refueling interface, which I think is kind of the connector port.

Starting point is 00:45:43 So I'm curious, what's the space seem approach to connectivity to other spacecraft? Is that a difficult thing? Or am I over-indexing on a bit of news that I just happened to remember before we jumped on the chat. No, that's a really good question. So that's something I would love to talk, but there will be some really groundbreaking news coming up about standization really soon. So just keep an eye out and yeah, give me a hint about really soon. Like should I have my eyes peeled in the next couple of weeks or is this like a Q4 thing? Oh, no, like within the next month or two. Okay, okay, cool. But we'll have to have you back on to talk about that because I'm really curious.

Starting point is 00:46:20 Because I mean, like, I hope that there's eventually a USBC equivalent for in-space refueling. So that way it's super simple, super quick. And everyone can use the same thing to avoid, I mean, just an unnecessary plethora of dongles in space to do the connections that we need. It seems simpler to have one standard. So I'm hopeful on that front. Yeah. Standization is really important. And also it's not just about standization.

Starting point is 00:46:44 It's about how that standization works and adopts to the current and current space. or future spacecraft side. So, yeah, keep your eyes out for it. We were talking at the top of the show about how once we have the ability to refill spacecraft, they can do more, they can, you know, make more adjustments to their course or change their mission or just be more flexible. And right now, if you have to send up a spacecraft with all the fuel it's ever going to have, that impacts design choices.

Starting point is 00:47:14 Once you take away that requirement, how quickly will we see spacecraft design change to take advantage of what you guys are building and also just to have more, I don't know, longevity per space spacecraft? Oh yeah, we'll see that change coming in the middle within the next three to five years because when we started a space and we had to tell space companies, okay, if you refill, this is what you get.

Starting point is 00:47:38 But now I don't have to explain to them anymore. Like they already know, and people are already trying to build their space drafts around refilling, thinking that, okay, there will be refilling in the future, okay, because it's such a constraint. And with all that mass, you want to put into space, and with all these things that we want to do in space,

Starting point is 00:48:00 without refueling is such a bottleneet. So people had actually started developing their space missions around refueling. Okay. Now, you mentioned that your next couple of missions already fully funded. I know you guys raised, I think it was a $6.3 million round of last year in, in quote, four weeks. That's impressive. Are you guys going to need to access more capital to finish those missions?

Starting point is 00:48:21 And have you already kind of have a portion of that, or does that initial round take you all the way through your next few missions? Yeah, we actually raised more money after that third round. So we have raised close like $12, $30 million so far. So that covers all our three missions, the one that we already flew and the next two missions as well. Other than we are planning to like come into like more profitability soon because we do have commercial contracts. close $100 million and we have $2 plus billion in LOI. So all those ones, all those commercial contracts convert, we'll be able to be profitable.

Starting point is 00:48:59 Yeah, it's kind of rare that a company comes and says, yeah, we have $2 billion in LOIs for our technology that we're still building. I think that is the definition of building something people want. Now, thinking about the broader venture ecosystem, if you look around technology today, it's kind of all AI. and that's absorbing a whole bunch of capital. Is there still enough investors out there focused on space to keep the space startup industry healthy in the near term?

Starting point is 00:49:27 Yeah, I think so, because space is really hard right now. I have been reached out by multiple investors wanting to talk and better understand our technology. So I think investors are really still interested in space industry as a whole. And then last question is just, you know, pretty simple. SpaceX, when public recently mentioned this at the top. I'm curious if that has changed the level of excitement and enthusiasm around investing in space-focused companies

Starting point is 00:49:55 because I think a lot of people that weren't paying much attention and kind of forgotten the fast-launch cadence of Falcon 9s and all that are now once again paying more attention and I wonder if that's creating positive momentum for the space industry. It definitely does, yes, I would say that. How does that manifest? Because I think a lot of people started giving more attention to the space industry after SpaceX IPO.

Starting point is 00:50:19 They're like, oh, space industry. And then they became so interested, okay, there's actually, there's an industry that we should pay more attention to because it wasn't space industry was there, but people weren't really paying attention until SpaceX IPO. And now people are like, okay, space industry is something we should actually talk about. There's so many cool things happening. There's all these new technologies coming up. And end of the day, space industry will benefit.

Starting point is 00:50:46 life on earth. So once people understand that, people will pay more attention, but I have I have been reached out by a lot of people wanting to talk about space industry. That makes me so happy here. I feel like it's always good when an IPO can kind of shine light on an entire industry and help everyone at once. Oh, actually, Ashley, before I let you go, you are building this company in San Francisco. And I tend to hear about companies building things that fly and zip around building in Southern California. So can you just tell me why SF or the Bay Area kind of writ large is the right place to build Spacium?

Starting point is 00:51:22 It's because after YC, we realize SF is where we want to be because the energy is crazy. Everybody wants to build something huge. And that's the, and at Spacium, we are weird. So we want to be in a place where there's a lot of people who wants to. to be like really crazy things. And that really, and so we really felt like SF is where we belong.

Starting point is 00:51:53 So, so yeah, we made that decision. You want to be in SF. I love San Francisco. I miss my city. But what about, what about you guys is,

Starting point is 00:52:00 is quote, quote, weird because I feel like everything we've talked about is within the normal envelope of like technology. So are you weird in a space startup sense? Or are you guys a different type of company

Starting point is 00:52:10 in startups as a whole? I think it's a little bit of both. It's just how we test things, how fast we move. And even like when we interview people, we are not, we are never looking for technical knowledge. We are looking for some type of technical knowledge, but we're always looking for that mindset. Who wants to, who are obsessed, who wants to just work from 5 a.m. to like 8 p.m. So that's when we actually start working like every morning. we started like 5 to 6 a and then and then everybody just grinding but it's such a fun working

Starting point is 00:52:49 environment that that's that's a cool part like sometimes i had to tell people like please go home they're like oh no i want to finish this i'll go home after i'm like no please go home so so it's not like i'm forcing anybody to stay like everybody wants to stay like so so weird in the sense it's like how everything we build is we always find a way to we always find a hack to make it cheaper or how to move faster. I really appreciate that. I think the hours you work sound incredible. I just, I have tiny babies, and so I cannot do that.

Starting point is 00:53:28 But I'm always very jealous to people that can devote that much of their time to their core projects. I feel like I get 60% as much done each day as I need to. And it compounds over time. So now I'm about eight years behind. Anyways, Ashley, thank you so much for coming on. What's the URL so people can go find out about the company? And are there any roles you're hiring for that you would love to shout out to our audience? Yeah, we are looking for software engineers.

Starting point is 00:53:52 So if anybody who's obsessed and want to build really cool stuff that can send a space, yes, please reach out. And it's spaceem.com, S-P-A-C-E-I-U-M dot com. So check it out, everybody. All right, and when you announced your next mission or two, we'd love to have you back on, A-S-Hie. But in the meantime, go forth, kick ass, and let's go to the stars. All right. Thank you so much, Alex. It was really nice talking to you.

Starting point is 00:54:17 Thank you so much for having me.

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