In short
Podcast Summary: This Week in Startups - E2088
Episode Details
- Episode Title: Castelion Hypersonic Missiles and Crunchbase’s AI Powered Predictions
- Host: Jason Calacanis
- Guests:
- Bryon Hargis, CEO of Castelion
- Jager McConnell, CEO of Crunchbase
- Release Date: (Not specified in the provided transcript)
Episode Overview In this episode, Jason Calacanis interviews Bryon Hargis about the urgent need for advancements in hypersonic missile technology in the U.S. to maintain a competitive edge against China. Subsequently, Jason speaks with Jager McConnell about Crunchbase's innovative AI-driven predictive models that aim to revolutionize insights into private market dynamics.
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Key Discussions
Segment 1
Hypersonic Technology with Bryon Hargis
Introduction to Castelion
- Mission: To enhance U.S. military capabilities through affordable hypersonic munitions.
- Rationale: Emphasizes the necessity of deterrence through a demonstration of strength, referencing Historical military strategies like Reagan's.
Importance of Hypersonics
- Definition: Hypersonic weapons travel at speeds exceeding Mach 5, presenting unique challenges and strategic advantages.
- Comparison with Ballistic Missiles: Unlike traditional ballistic missiles, hypersonics can maintain low-altitude, flat trajectories, making them less predictable and harder to intercept.
Challenges in U.S. Defense Manufacturing
- Current Production Limitations: The U.S. struggles to produce hypersonic missiles in significant quantities—often only dozens per year.
- Cost and Incentive Structures: Traditional defense contracts (cost-plus) have hindered innovation and affordability in defense manufacturing.
Positioning Against China
- Concerns: While the U.S. has superior technology in many respects, China is currently leading in hypersonic development.
- Proposed Solutions: Highlighted the need for more factories and investment in automation to produce weapon systems at scale.
Segment 2
AI Predictions in Private Markets with Jager McConnell
Evolution of Crunchbase
- Shift to AI: Jager discusses how Crunchbase is pivoting from being a data repository to incorporating AI for predictive analytics.
- Historical Context: Crunchbase aims to transform from a directory of historical data into a platform that provides real-time insights and predictions.
New Features
- Predictive Insights: The introduction of algorithms that predict company funding, acquisitions, and growth trajectories based on engagement data and historical edits.
- User Customization: A personalized homepage feature allows users to track predictions and trends relevant to their interests.
Financial Strategy and Growth
- Funding and Investments: Crunchbase's recent funding rounds and the challenges in balancing growth with the cost of AI technologies.
- Market Predictions: Jager expresses a cautious optimism about future growth, indicating a focus on accuracy and relevancy of predictions.
Key Takeaways
- The U.S. faces a pressing need to advance its hypersonic technology to maintain military superiority, particularly in the face of China's advancements in this area.
- The transition to AI-based predictive models at Crunchbase signifies a broader trend in leveraging technology to enhance decision-making and strategic planning in the startup ecosystem.
- The conversation emphasizes the necessity for American defense firms to adopt innovative manufacturing processes to compete effectively against rivals with lower production costs.
Conclusion This episode sheds light on two critical areas: the urgency for the U.S. to bolster its defense capabilities through advanced technology and the evolving landscape of private market data analysis through AI. Both segments illustrate a significant shift in strategic thinking and operational methodologies, indicating how innovation is imperative in today's competitive environment.
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For further details, insights, and resources, visit [Crunchbase](https://www.crunchbase.com/) and [Castelion](http://castelion.com).
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00It's honestly sad. What quantity do you think is a large quantity of missiles to order in a year? Right now, like in the U.S., if you're talking about a reasonable size, like long-range missile, what is a large quantity? Four to five figures. Thousands to tens of thousands would be a large quantity of missiles. Way less. Hundreds? Way less. Way less. Dozens? Our highest-end systems, we're not at the capability of producing dozens per year, but that is like their ultimate eventual output when everything is working. Yes. Pathetic. This Week in Startups is brought to you by Squarespace. Turn your idea into a new website.
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1:13Hey, everybody. Welcome back to this week in starters. Very excited for our next guest. His name is Byron Hargis, and he's got a startup in the defense tech space. It's called Castellion. And welcome to the program, Brian. Hey, Jason, thanks for having me. All right. I like the American flag back there. I love defense tech. And our researchers were really excited when they found your startup to have you on the program. So we're really excited to have you here. Maybe tell the audience a little bit about what you're building. Absolutely. So Castellion is really focused on bringing back deterrence through strength.
1:54And if you kind of subscribe to the Reagan Air piece through strength, Like, how do you maintain peace? You have to have actual strength against an adversary, and an adversary has to know that. So we're focused on building very affordable long-range strike munitions, specifically hypersonic munitions, to get after kind of the current problem set that we see with having very limited options against pure adversaries, such as China. Let's take a moment here, just to level set with the audience. We hear hypersonics all the time. Now, I think we all assumed that inter-ballistic missiles were going at a very high rate of speed.
2:32Yeah. We see things come out of battleships and submarines. They look like they're going really fast. But, you know, for civilians like ourselves, I think sometimes we don't understand what hypersonic means. Let me take that piecewise because it is kind of a confusing topic. So the hypersonic itself, like the kind of like general term is usually like associated with going five times the speed of sound or greater. So Mach 5. The actual technical details of that are even more complicated. It's really that you're getting into compressible flows. You're not in equilibrium. So Navier-Stokes becomes much harder to actually compute when you're trying to figure things out.
3:14And generally what it means is that if you don't actually do testing, it's extremely hard to model a hypersonic system. And you are correct that when you look at things like ballistic missiles or like a reentering space vehicle, they all do enter hypersonically. So like typically, like if you're at orbital speeds and you're reentering the atmosphere, you're coming in at least at Mach 25. And so ballistic missiles, you know, space capsules, everything, they're all start hypersonic when they come back into the atmosphere. Now, when you hear like the Department of Defense or like a company like ours talk about hypersonics, it we're really actually referring to a subset of that.
3:54And so very specifically, like a ballistic missile follows a ballistic trajectory. In other words, it's a very predictable, controlled trajectory that usually goes through space. It launches from the surface or what have you. Goes into space and then reenters and comes back and it follows like the same arc that you would throw like a baseball. um hypersonic weapon systems uh what what the dod typically refers to is really like when looking at how it flies it typically flies a very different looking flattened trajectory and so you're not leaving the atmosphere you're flying at a very prolonged distance horizontally at very high rates of speed the reason that hypersonic systems are kind of like all talked about right now is really when you're trying to get after, say, like a peer adversary such as China, they put in tremendous investment to basically negate American capabilities regionally, close into the coast of China.
4:54A hypersonic system, fundamentally, when viewed at it from the other side, it doesn't look like a ballistic missile. And the reason that's important is traditionally ballistic missiles usually also imply that you might have a nuclear warhead on the front. And so you don't typically start launching ballistic missiles at other nuclear-armed countries for fear that they might confuse what you are doing. Oh, that's fascinating. Yeah. Okay, so just to recap here, these things go, well, five times the speed of sound. That's Mach 5. Aeroplanes go under Mach 1 even, right? We fly below the speed of sound in commercial airlines, but there's Boom, a new member of the Twist 500 and the supersonic passenger plane and the Concorde obviously would break Mach 1.
5:40But we're talking about five times the speed of the Concorde. The second note is these things tend to fly closer to the ground. They're not interballistic. They don't go into outer space or into the upper atmosphere. When you go into the upper atmosphere, you have less air, so you can go a little bit faster. So these things are fighting against wind and they're going five times as fast. And I think the reason this is important, or the introduction of this capability is so important, is that you can't defend against hypersonics, or it's incredibly hard to defend against hypersonics. In other words, the Iron Dome, if Hamas or whoever was dropping bombs on Israel, the Iron Dome wouldn't catch a hypersonic.
6:26Am I correct that that's the reason this is so important? It's not impossible. It is much more difficult. All right, and we have a video here. What are we seeing? Maybe you could sportscast this. Many people are listening. Absolutely. So this is some of the team. We develop a lot of the hardware in-house, very uniquely in aerospace. Most of aerospace, like you typically hear the primes as integrators. We do actually a lot of the manufacturing of all the systems that are inside the missile ourselves. That's actually our Marine MKR. It's a heavy-duty truck that can basically pick up a shipping container, put it on the back.
6:59We made a launcher for that to make a mobile launcher to be able to do accelerated testing. Obviously, it has applications for the Army and the Marines. But here, we're actually testing a prototype of the upper stage of a hypersonic weapon system. Got it. And so, which piece of this puzzle are you building? Are you a provider to other people building the hypersonics? Are you building the full set or TBD? What's the plan here? We're doing both. So very concretely, we are planning to provide full all up rounds, especially at the lower end of the cost scale. And I view that as absolutely necessary that as a country, we'd be able to do that.
7:43Because one of the kind of key tenets of like American defense is we make the most exquisite systems, but they're very expensive and we tend not to have a lot of them. when you're looking at an adversary like China that's put a lot of effort into manufacturing and their defensive capabilities we need to actually have sufficient quantity to actually deter them because they're not going to be scared of having like a few very high-end missiles. What will these cost do you think? What do you think they're going to cost ballpark? Like for... For our like smallest weapon system they'll probably be on the order of one third to one quarter what a much less capable but comparable in size system currently costs the u.s government if you compare them like on a capability basis like what could this weapon do versus like our weapon it's probably one tenth of the cost okay so i have a i'm sorry a very naive question because i didn't serve in the military and uh you know i've been behind a desk here uh doing podcasts why didn't the military industrial complex mate more affordable missiles, more affordable tanks, more affordable planes over the last couple of decades, where we saw in consumer and business technology a massive decrease in price.
8:58All we've seen on the other side is a massive increase in price. Now, I'm sure that these providers were adding features, but we all know, you know, you can buy a smartphone today for but$100,$200,$300, an Android phone, obviously, and you could have capabilities that are literally, quite literally, 100x what somebody had but 20 years ago. I mean, it might even be 1 ,000x, you know, based on the camera and the whole set. I'm kind of getting at why economically, politically, systems, what's the issue here of this opportunity suddenly emerging to take 90 % out of the cost structure. Squarespace makes stunning professional websites ridiculously easy.
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10:28Personalized layouts, on-brand visuals, premium content, it's all ready to go. So start your year off strong at squarespace.com slash twist for a free trial. And when you're ready to launch, go to squarespace.com slash twist to get 10 % off your first website or domain purchase. Squarespace.com slash twist. Thank you to Squarespace for making such a great product that we use year after year at an affordable price. And we really appreciate your partnership. Fundamentally, the incentive structure that the traditional primes have worked under for a very long time and has generally been accepted by the government has not driven them to those types of improvements that you've seen in commercial industry.
11:07If you had a traditional prime, build your cell phone. It would probably be over$100 ,000, maybe a million dollars. Only a select few people would have one, and that's good because that's all they would be able to build. um it really is like you got cost plus contracting that's one aspect there's basically no commercial penalty in terms of like taking a long time or it being expensive because all of the all of the expenses are paid for you have essentially a kind of like peacetime posture where because these systems take a very long time to develop and they are expensive like the government isn't buying any and of course as you know if you don't if you're never going to sell but a handful, of course, they are going to end up being more expensive.
11:50So it's not just like, I don't want to just blame the primes because it's not 100 % on them. It's really just the kind of traditional aerospace, I'd say, market has been very backwards. In fact, the space market, which I'm very familiar with, was like this pre-SpaceX on both launch vehicles, satellites, you name it. It's this exact same problems. there's just been a new entrant that fixed it. And I think that in this market, a new entrant can also fix these problems. There's literally enough margin with different techniques and processes to bring that much cost out. So if I'm summarizing you correctly, a paradigm shift has occurred.
12:33The old paradigm was this cost plus paradigm and there was very little competition. There was competition, but it was competition from a handful of players, maybe, you know, count them on one hand. And their incentive was to give the government what they wanted, how they wanted it, not to look at it and say, from first principles, what's the best thing I could make for the lowest price? Whereas in Silicon Valley, we have a rabid competition with a large customer base. There's only one customer here, the United States. Am I understanding this paradigm shift correctly? Yes, there's absolutely a paradigm shift.
13:10And I'm going to give you one more like very concrete example. Like it's just one part of a huge problem. But like even with what you said, typically, yes, the government writes the requirements and they are buying to like the requirements the system needs to do this. And, you know, the major primes are building to that. If you're under a cost plus contract, it's not like it's not like most folks working that are thinking like, just how can I pump up the price and, you know, stiff the taxpayer. But fundamentally, if a customer asks for something and it's actually very difficult, like it hurts manufacturability, it causes, it's going to increase the cost greatly.
13:45If you're planning to sell these things under a firm fixed price model or commercially, you will fight to the death that this is a bad idea. And you're going to go literally generate conflict between you and your customer, which is always like uncomfortable. But in a cost plus environment, why do that? I'll just agree to it oh look oh the schedule's now longer it's going to cost 3x as much but this is what you wanted and I I told you the consequence and you said do it but you don't fight and I think like that's just like a small example of like what has been part of the problem you know it's kind of like you know your dad or your grandpa goes into the I'm kind of the dad in this now but you know your grandpa your dad like they like to go to a certain restaurant they like to eat like this New York strip steak steak they get their whatever new york strip steak they like their martini like the side of mashed potatoes and the chef's like hey i want to do something a little more interesting here and the customer's like yeah i like my steak and potatoes and my martini thank you very much you kind of you're kind of stuck there if you are the provider because they told you what they want you kind of hinted at something maybe you want to try a seared tuna they don't want it they want the steak that's what they always knew and so you're kind of left with having to just build these things and then show them and then say, hey, we built something.
15:05Here's the capability. Here's the cost. Might this interest you? That's how the industry is kind of moving now, you think? It is. I mean, obviously, the space is now venture backable. We're venture backed. That's relatively new. Like, honestly, Andrel's success unlocked just an enormous potential in the fact that now these types of companies are venture backable. And they're standing on the shoulders, I assume you would agree, of SpaceX, which showed, you know, hey, you can have the government as a client and it will work out pretty well. And you can actually make things that kick ass that they didn't ask for, that they will eventually buy from you.
15:42And all my friends who are SpaceX venture capital, his investors, founder fund, et cetera, they're feeling pretty good about the investment now. So it's kind of a big unlock. Yeah. Yeah, totally. And so like the SpaceX thesis, right, there's still like a commercial aspect to it. Andrel is definitely more like defense only, but there was a very big software focus. We're down here, like we're making hypersonic missiles. There's not a obvious, like, you know, what's our SAS subscription software play? There isn't one. And that literally was uninvestable probably like three years ago. And so like this market is now unlocking.
16:12And the reason I say that is like, if you are, if you're in this like traditional kind of market with selling to the defense department, everything you do, like if you don't have outside capital that you can go raise, you have to find funding for it. How long will it take you to go from raising your first venture dollars, you know, outside investment, let's say not your own seed capital, but from first day for outside capital to first day revenue in from the government? What's the number of months or years, do you think? Oh, no, it was months. It was months in our case. Wow. So you picked something that they really needed.
16:49So in six months, nine months, you had money coming in from the government in the bank account. Correct. How is that even possible? I thought the government moved slow and this took years. What happened? Explain it. I started my career as an engineer working in defense and aerospace and worked my way up into doing government sales, which is extremely esoteric. And really, the reason I did that was I actually wanted to be part of driving what are we working on? Because as an engineer in aerospace, you're told what you will work on. And so I found being part of the sales process actually helped pick what we are working on, what we're trying to solve.
17:28There's two very important founder lessons here. And we like to always point them out when we're talking to Chris Sounders. If you want to be the CEO eventually, the sales team, especially in the early days of a startup, they're the closest to the customer. And they really start to understand what the problem set is, what the needs are, what the willingness to pay is, what the quantity is. And, you know, that, if you look at just that subset of tasks, sounds like the CEO's job, sounds like the founder's job. The sales job is the founder's job. Eventually, you know, you have to get a customer and that customer has to be delighted.
18:09So this is actually a really interesting lesson here, I think, is don't look down on the sales job. If you are a young person and you can get into sales, you know what? I guarantee you the CEO is going to come talk to you at some point. They're going to be like, hey, how's customer X, Y, and Z doing? Yeah. I mean, to your point, it's not, it is sales. And like, yes, you're trying to make sure that you're getting to a product that you can actually make money from. But sales fundamentally before you make your sale is really like product development. Like what are we building the right thing? Is this what the feedback is?
18:43Is this what we should be building? Are we building something no one will buy and everybody is already telling me there's no way in hell they're going to buy that? Like you're the voice to the rest of the company. And if you're doing sales correctly, you are doing product work as well. Yeah, and this changes over time. But this is such an astute point. If you look at your first couple of sales executives as product discovery and customer discovery individuals, then you can take in your mind half of their salary and comp and put it towards product development and half towards the sales process.
19:17And that will make it easier for you. Now, of course, once you have a product completed, well, then you're doing consultative sales. You're saying, hey, here's what we have. What are your needs? And you're kind of matching it up and closing the sale. And then if you really have a great product, like SpaceX does now, the third phase is you're picking up the phone and taking orders. All right, we all know if you're a founder or even if you're in a small business, You're thinking about your company 24-7, 365 days a year. That's the life of a founder. This is not clock in, clock out, nine to five gig for you as the business owner.
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21:24But then there's also room for creativity and the founder saying, I want to build something that they don't know they need. So I want to get to China. Everybody is scared about China's low-cost missiles, low-cost production, and the velocity of their production. And the thesis I hear from my friends, you know, in the deep state and who are in and around it is, we have an adversary that can manufacture stuff at a fraction of the cost and at a multiple of the speed. what do you think is going to happen you you look at the um the field in ukraine and what that has wrought which is basically they're not even fighting with industrial military complex items they're zipping drones around with grenades strapped to them this is a whole different warfare um so maybe your thoughts on where is china right now how far is american manufacturing behind them and how do we close the gap?
22:26In the munitions space, in a lot of the defense manufacturing space, honestly, they're not ahead. China's not ahead in technology in most areas. Now in hypersonics, they are actually ahead. I would view them as ahead of the U.S., which is a weird place for the U.S. to be. But in terms of manufacturing of those systems, they are generally doing quite well. It's very hard to win a fight if you are the first side to run out of munitions and weapons. And so like kind of what you're seeing in Ukraine is like, I'm sure they would like to fight further distance from each other and push the other side back.
23:02But when you run out of those type of munitions, then you engage closer. And what you use to do that changes. What's the path to winning if they're using, quite literally, slave labor in some of their factories with the Uyghurs? or absurdly low compensated wages that works six days a week, 12 hours a day. How does the United States compete with that? We don't have to compete on a dollar-per-dollar parity level. We're a very wealthy nation. We can't afford to pay more, but we do need to produce in a quantity and at a sustainable rate that allows you to, you know, basically, you know, atrophy their capabilities.
23:50Warfare is always like a back and forth. We do something, they do something to counter it. You have to do something to counter that. You need to just do that process faster than the other guys. And then you need to produce it at a quantity that overmatches anything they have. And that's where we're behind and what we are trying to fix. So we need more factories. Absolutely. It seems to me... You need more factories. They don't have to get down to the same price as a slave labor, but you do need to produce the systems that can counter Chinese capabilities and at a quantity that matters. Now, if your system is much more capable than theirs, then you don't have to maybe make as many to counter those capabilities.
24:25So there's also like that factor that has to be looked at as well. So it doesn't even have to be exactly equal numbers, but you have to counter like their potential to hold you at risk. The good news is we have slave labor coming to the United States. This is a little known fact, but we have unlimited slave labor coming in the form of robots. A figure, and I know that was like, you're like, where's he going with this one? I was like, oh, dear God. Dear God, who's he enslaving? Robots. So automation of factories, obviously that's been a trend in our lifetime, but having actual robots who can fill in what the, you know, singular arm robots that are fixed, you know, into a conveyor belt and a production line, that's going to fill in the gap where maybe we're short on humans.
25:17It's honestly sad. What quantity do you think is a large quantity of missiles to order in a year? Right now, and like in the U.S., if you're talking about a reasonable size, like long-range missile, what is a large quantity? Four to five figures. Thousands to tens of thousands would be a large quantity of missiles. Way less. Hundreds? Way less. Way less. Dozens? Our highest-end systems, we're not at the capability of producing dozens per year, but that is like their ultimate eventual output when everything is working. Yes, it's... Pathetic. These missiles, the missiles you're building, all due respect, the complexity of building a missile and a Cybertruck, these don't seem...
25:59Yeah, I mean, I didn't want to say it. It's a way less complicated problem than building a car. it's a way less complicated problem than building a satellite. So when you're talking about bringing in like a robotic workforce, we're so far away from like the scale that where that would actually pay back. Like we're talking about, let's just automate some of the tasks because you're still like a thousand is a very large order. Well, since we're going there and we're going to be super candid here in this interview, I like having candid guests. Thank you so much for educating us.
26:30Would, what is the skill level? I'm going to try to be delicate here. The skill level to put together a hypersonic missile. I'm sure you, let's say if you need, you know, X number of people per missile, you know, to build a missile or to build 10 missiles a day or whatever it is. I mean, it seems like building 10 missiles in a factory should be pretty easy task. That's only 3 ,000 missiles out of your factory a year. So I'm just picking something easy. Let's even dump it. 100 hypersonic missiles a day in a factory. That should be possible. Yeah, 30 ,000, 40 ,000 a year from a factory. How many of those people need to be engineers, college educated?
27:08Most of our manufacturing base is going to be technicians, and they do need to be highly skilled in certain areas. Like some of the things that we're doing are dangerous if they're not performed correctly, like when you're dealing with energetics. So you do have to have highly specialized training and skills. But it's something that, you know, you can teach to anyone. it doesn't have to be like they don't have to have a four-year degree to understand how to handle this process safely and what makes it unsafe like don't do this and really you need you need when you're looking at manufacturing at rate like you're really trying to control your process and quality and so those procedures and processes that's not like the technician's job to develop it but they're an integral part of giving you feedback of like hey this is working College educated, associates degree down to even high school educated, able to think logically and be thoughtful for an eight, 10 hour shift is enough.
28:07They're going to get paid 30, 40, 50 bucks an hour. What do you think? I don't like if you don't have a college degree, but you have the right attitude and the ability to learn. I don't care like that. Who cares? This makes me feel a lot better talking to you and really getting into, again, just like first principles, which is just a fancy way of basically building the model from the bottom up. Well, we wish you great success. If you were an engineer and you wanted to work at the firm, where would we send the amazing engineers, developers, smart people who want to help build the defenses of the country so that we can have more peace and prosperity?
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28:46Castellian.com. And we're also on LinkedIn under Castellian Corp. So please do find us and submit a resume. All right. Continued success. And we appreciate the effort you're doing. And we do appreciate you coming on the show. Founders, let's talk about building your brand here in the real world. We know digital ads are amazing, but if you want to stand out in 2025, maybe you need to think a little bit bigger. And a great way to do that is out of home advertising. Yes, you know, those really impressive billboards you see everywhere, or even the beautiful murals that everybody loves. This is how you build a brand.
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30:07Take your brand to the next level with AdQuick, the smarter way to do OOH. And just for Twist listeners, AdQuick is waiving their fee on your first campaign. That's an amazing offer. Get started today. AdQuick.com slash twist. That's A-D-Q-U-I-C-K dot com slash twist. Hey, everybody. We got an awesome Twist 500 interview coming up. It's with a company called Crunchbase. Now, I'm sure you've heard of Crunchbase. It's the well-known online database of all things, private markets, startups, venture capitalists, funds, all of that fun stuff. I'm adding them to the Twist 500 because they recently released a suite of AI-powered features that I think are honestly pretty awesome.
30:46I love data. I love charts. I love analytics. This is my jam, and I think it's going to help the company grow and possibly have a big exit. So it's Twist 500 material. That said, I used to work there a couple years back in the day. I helped set up the Crunchbase news team, a project that I'm still very, very proud of. But because I was an employee, I did have options, which I partially exercised. So now I actually own stock in the company. Normally, I try to avoid any sort of conflict of interest because I don't like them as a journalist. But as Jason says, no conflict, no interest. So I figured, let's just be honest, let's add them to the 2500.
31:20And so in that vein, I have Jagger McConnell, the CEO of Crunchbase, and my former boss, Jagger. Hey, how you doing? How's it going? Good to see you. Okay. So, I mean, first of all, it's been a little while. And since we were in touch, Crunchbase has watched the AI wave explode. And when I think about Crunchbase, this amazing repository of private market information and the importance in AI of having proprietary data, it seems like a match made in heaven. So can you just take us back to when Crunchbase was like, oh we're gonna go in this direction sure i and i remember very clearly because i was using chat tpt and i was like oh this is so cool and everyone had a sort of like moment of like this is going to change everything and i was like oh this is going to change everything um and the the challenge was i said well we're great we're a data company and everyone's saying oh congratulations data is the new oil, all of this.
32:17I was like, yeah, kinda, except once our data goes into the LLM, it's going to never come out again. And then the oil is being made somewhere else and we're not a company anymore. So it actually felt like an existential threat to me where I said, well, we can't just rely on historical data now. Like historical data, in fact, and this isn't just for Crunchbase, every company in the world that relies on historical data or makes a business model off of it is now completely host, in my opinion. And the reason is because once it goes in, you're done. And the insights that AI is going to do on top of the data is going to be way better than anything you're going to be able to do as a company.
32:58So what do you do about it? So that was the wait, what do we do? And I was like, well, there is data that we have that no one else has. And can we use that somehow? Those are two things. It's every edit that's ever been made in crunch space overall time, right? You can't crawl your way there and find that. And then the other piece is, um, do you have our engagement data, right? What can I do with engagement data anonymized to sort of figure out what's going to happen, um, next in crunch space? So can you go and start? So historical data is looking back. It's knowing that crunch space raised$106 million throughout its history.
33:34It's everything that's kind of in the rear view mirror, but your point is that crunchbase knows so much about how people have interacted with that data that it provides almost like meta context on top of the raw information itself that's right like if you if you go look at a profile now you'll see the history of the company but what you don't see is what how this profile changed over the last 17 years to get to where it is and then how have how's traffic flow changed on that profile over time are there more investors or less investors looking at this profile now than it was before? Or new corp dev people or recruiters, whatever happens to be, or is the entrepreneur engaging with these profiles more or not?
34:12All of that is this engagement data and historical edit data that when we looked at it and we again said, well, the whole this unstructured data, what do we do? We just pumped it into CheckGPT and sort of some of these open source ML models. Can we figure out that it can predict patterns? And the answer was a hard yes, which is great. So this really feels like a transition at the company away from we have a ton of data. You can give us some money to access it, pull it out via the API, do whatever you want to do with it, too. We are now going to, instead of offering access to the data, offer intelligence that the data gives rise to thanks to ML models put on top of it.
34:53Is that fair? That's 100 % correct. In a way, like ChatGPT is like this. it took all the historical data of the public web and it's now trying to predict the next word that makes sense right and we're doing the same sort of thing in a smaller context of crunch space saying all the data we have unstructured can we go and figure out what is going to happen next in a company that that that first prediction of whether it be funding or acquisition or whatever happens to be so how many different things are you predicting now with the new system you've put in place which came out uh earlier this week i believe actually and and frankly jacker how accurate are you in these predictions thus far yeah it's it's it's the first question is easy the second one is harder to answer uh the first one we did 18 insights and predictions um so it's it said we're shifting the focus of it's not just historical now it's what's happening now with the company and what's going to happen and that's insights and predictions by definition on the predictions side you've got funding prediction acquisition prediction um are they going to close is the business going to close uh are they going to do layoffs are they growing um so there's a number of these different angles and some of these things we're not going to put onto the website like you're not going to go and see like are they going to do a layoff but that is an interesting prediction um that that we're using more on the risk side which is more on the api side.
36:15So if you're an API customer, you might have access to like the riskiness of companies. You know, as a person who has made most of his money working for other people, I think I would love to know if a major layoff is coming as a signal. So are you not putting that one in public just in case you accidentally worry people about their employment prospects? Yeah. I mean, the reality is, it's like none of these predictions are going to be 100 % perfect. And that's when you get to the accuracy conversation in a second. Yeah. But some of them are not perfect. And we don't want to unnecessarily worry people when we say, hey, it's a 60 % chance of a layoff.
36:48Like, wait, what does that mean exactly? But for some of our customers, you know, if you're thinking about like, know your customer, that increasing risk, sort of like a credit score, it kind of says, well, maybe I should take a pause and maybe do a little bit more due diligence here to dig in deeper. And that's more the intent of it. So these are much more directional versus absolute predictions about what the company is going to do. 60 % chance of layoffs is useful if you're selling per seat SaaS and you might think, oh, they're reducing headcount, not a great place to go do a sales call. But it's not like, oh, I have an 84 % chance of being laid off in the next 74 days.
37:24Yes, that's correct. And especially when you add that time scale to any of these predictions, it gets very tricky. So our fundraising prediction, we have an incredibly high level of precision and recall on whether or not a funny round is going to occur. When you say, well, when is it going to occur? Now it's a different, that's a different question. If you're saying, well, Jagger, tomorrow, what funny rounds are going to happen? My precision and recall go very close to zero. But what's interesting is it's way closer to 100 % than you guessing on your own, because we've got more signal than you do.
37:58It's still a very, very small number, right? So, you know, people that I talk to still sometimes have kind of an old Crunchbase model in their heads. And I don't know how long it's going to take to educate people that it's been growing and changing and improving for a long time now. Thanks, by the way. I use Crunchbase all the time. But if you think of Crunchbase as a wiki back in the day, it's cool because everyone got to participate. And it sounds like the new Crunchbase with AI technologies is still predicated in a way on how people show up, access and interact with the data. so it's still in a way community Howard is my read of the situation yeah certainly the 80 million people using Crunchbase is an important part of the how Crunchbase works but yeah one of my biggest frustrations is when I go and say you know someone says oh I know exactly how Crunchbase works I'm like oh why don't you tell me they're like well it's a wiki and I'm like no well it used to be in 2014 right that's 11 years ago now that's right 2014 is a useful data point because you joined in 2015 and took over as CEO when it was spun out as a private company.
39:02For those folks who don't know, Emergence, Mayfield, Omer's, and then most recently, Jagger, you raised from, as I scroll through my notes frantically, you can build me up. Alignment growth. Yeah, there you go. I had arrangement growth in my head and I'm like, I know that's not correct. But I bring that up because that's a lot of capital. You guys have raised 106.5 million according to crunchbase.com. What did that last$50 million unlock for the company? Because that That was in 2022. So in and around the point when everyone started to talk more about AI. Yeah, that's right. Honestly, the market shifted pretty dramatically at the end of that year.
39:37You might remember a lot of the data companies out there took a beating as prospecting became less important to the sales prospectors of the world. So we also took that opportunity to do this pivot. So Chat.chap came out. This is when we had this sort of aha moment. And we said, let's not blow all this capital just going and trying to sell. oh, let's go and actually build something that is very materially different than what's in the market today. So that's why we went and started focusing on this new pivot towards predicting the future rather than just doing better historical data. A lot of people are using proprietary closed source models.
40:11And I was just kind of curious, what did Crunchbase pick as its kind of like model paradigm? Are you guys using, you know, Meta's llama models or have you built something internally? What's the underlying brain for all the new AI stuff? Yeah, I mean, it's a combination of a bunch of tech honestly um and some of it is is our own stuff we use open source like tensorflow to to to go and do a lot of the ml side we certainly are using open ai to go and and handle a lot of the unstructured data um it just in our testing it happened it seemed like the best um and and but we're we're still to the way that we can kind of move in and out depending on what's what's better and what's cheaper honestly so sort of like a combination so like when deep sync came out we're certainly They were like, hmm, that's interesting.
40:51They were like, hmm, maybe not. So there was an ongoing conversation. But the nice thing is I think every software and data company that uses this stuff needs to be thinking about how to make it interchangeable so you can sort of go where the wind blows if something becomes better. Yeah. I think the phrase is model agnostic. I'm sorry. Yeah. Okay. Does AI braining compute that whole kind of bucket of cost? cost. Does that now take up a much larger portion of Crunchbase's OPEX than the old AWS bills back in the day did? I'm trying to get a handle for what is it like to change your company towards an AI-first model, and how does that shake up your profit and loss statement, frankly?
41:35Yeah, it absolutely does, is the short answer. Certainly, it's a huge line item that didn't exist two years ago. And we're watching the people using our Crunchbase Scout today, I just sort of understand how much that bill might be going up. So it's an interesting pricing time. And how do we think about passing those prices on to our customers ultimately? Because at the end of the day, I can't just go negative and become an unprofitable company again. So it's how do we balance the costs? And obviously, as we see the prices going down in the LLM world, that also helps us out. So there's a lot of weight to see right now in terms of numbers, but it is hard to sort of plan for.
42:20Certainly, I think that's a big challenge for CFOs. Well, it's kind of cool because I feel like right now, if you build something that uses modern AI techniques that is too expensive, you should do it. Because in 12 months, it will cost 10 % as much. And if you capture that market, you can... I can see a reason for the cash burn in many circumstances. This is not 2021. People are not just taking bricks of cash and heaving them out of windows. so right um as long as it's like the challenge though again is like you can do that but then you're completely vulnerable to someone saying go make the exact same thing um to an ai agent that goes and builds it later so so again at the end of the day like and what is the most valuable thing it's the day that no one can have access to um even if you have historical data behind a paywall i think you're still vulnerable because i think there's going to be ai in the future that goes and social engineers its way in and gets its data like we go and say ai go and um have all the day there is in the world and it says that at any cost like that ai is going to go make phone calls
43:22it's going to create six different email addresses rotate its ips use three different agents from four different models and six different companies to go and it's going to get around it i wasn't going to bring up copyright but i mean i think it does play here i know crunchbase does some work to prevent scraping if memory serves but i presume that that's gone you know 100x in the AI era. So how have you guys managed to defend the fort, if you will, and have AI companies come to you and said, Jagger, we'll give you, you know, 20 million a year for the whole data set if we can just ingest it into our model?
43:54Yeah, we certainly have had some of those sorts of offers. We are avoiding those. We, of course, do our best to block crawlers. We use a lot of tools to do this, like PrimerX is probably one of the best known, where they're going in and blocking, and that's our whole core competency, but they're still not 100%. And that is why you need to be careful about what data you put out onto the internet. I will never put engagement data, obviously, onto the internet. So no one will have access to that. But if we are using forward-looking stuff, you can crawl that all day long. Predictions change every moment.
44:28So you'd have to be crawling us constantly. And at least today, there's no way to simultaneously crawl every single page that Crunchbase has and pull it all down simultaneously. Our server's going to handle that anyway. That's a DDoS attack. Yeah, so we've got plenty of protection there in the sense that it isn't technically possible. So the predictions are so dynamic and so live that we think we're safe there. Okay, so there's kind of three major things that Crunchbase just rolled out. We've talked a little bit about the predictive company profiles. Essentially, here's the company, here's their information, and then here's what Crunchbase thinks is going to happen next, and here's kind of the state of the business.
45:06There's also a private market homepage. Now I've gotten to play with this a little bit, but for folks who haven't seen it, Jagger, can you just tell them what that is? Yeah, so basically the idea here is there's a lot going on in Frenchface that you don't know about, right? Now we depend on you doing a search or looking at a specific company. You're totally missing other things that you might really care about. So let's make a homepage that essentially has a feed of all the cool stuff that's happening, whether that be predictions, insights, what's trending, all that's available now. And the part that I actually like more is the for you section where you can go and specify these are the industries i care about these are the predictions and insights that i care about so if you say hey i want to know every time a key hire gets made at a certain type of company you can go and do that and it will just pop up on your feed or a new prediction for funding whatever happens to be and you can click into it see some details and see the details that are driving that below it that feels very much like an analog to cnbc to me but with slightly different data because you know private private markets are real-time, live, everyone can see the information.
46:04But I go to CNBC to tell me what do I need to know from this massive ocean of data, and it feels like in a machine learning context, you're doing that with Crunchbase now with this new homepage. Yeah, I think that's right. Internally what we're saying is, what's the TikTok equivalent for Crunchbase? How can we create a stream of interesting stuff? And that's the dream. I don't think we're there yet, just to be clear. But maybe someday. So I'm going to see you doing a dance on my private market homepage. I see. An AI-generated version of me. That's right. So that way it can stay on beat. That's right.
46:40There's another thing, though. You mentioned it earlier, but I haven't gotten to touch on it in particular. It's Crunchbase Scout, which is, from my experience, kind of like an AI agent that I send forth to do tasks. And I presume you've stuck with the traditional Crunchbase dog branding because it fetches things and brings them back. It's your associate that can help you do things. it's going to get better and better over time. Right now, you can say things like make a chart, comparing funding of these two different companies, and they'll go and do that for you. Or the other cool thing about it, it has all the information from the public web as well.
47:11So if you want to merge those two things together, what companies may be affected by policy changes, you know, like those sorts of things can start to happen. It can go reach out, do its own searches against the news, and then integrate that with the Crunchbase data that it has access to. And I think there's a lot of opportunity hiding in there. everything you just described is kind of what i expected the words to be that came out of your mouth but to me just a black box behind the scenes in terms of how many different technologies had to be put together to make that happen did it take a long time to get the first version of it that was that felt right like i'm just curious because you're a product guy so i'm kind of curious like the process getting this from like okay we're going to do this to now it's good enough that we can begin testing it's probably one of the most complicated parts of the other stuff that we've launched to make it feel right.
47:59There's a lot of technology involved. And if you think about it, it's like, how do you scope the conversation to the stuff that is in Crunchbase? I don't want people asking, who is our favorite baseball team and having strong answers there. So how do we scope it to Crunchbase? How do we give it access to the Crunchbase data? So to merge those two things together is a very complicated problem. And how do you know when to use the public web and when not to use the public web? and you can't rely on AI just to figure that out for you. So you have to sort of put those rules in place around it. What do you give it access to?
48:32What do you not give it access to? And then even, like, there's a cost involved, right? Every time someone is asking a question, it's costing French-based dollars. Wait, wait, not dollars. It doesn't make sense. Pennies and dollars. I was like, dude, I did a lot of testing. Should I send you a check? Sorry. But it is maybe more expensive than you think it is. So it is a, so how do we make that efficient and still keep the user experience good is something that we're thinking about. And of course, now that it's live, you know, like we're learning every minute about how people are using it, what's not working right, and we're just going to make it better.
49:12And that refinement is actually where the most amount of work is going to be put in. Going back in time. So the round from 2022, the Series D, you guys were talking about having, over 60 ,000 customers, thousands of SMBs. And you had dropped some really interesting notes about how the company was performing, saying that in the first half of 2022, I believe, you'd added like 9 million in net new ARR with only$2 million in burn. Earlier in this conversation, you said you don't want to become unprofitable. So how has growth been? And it does seem quite a lot like you shot for, we're going to get in the black because the market's uncertain.
49:49So can you just fill me in with like, I don't know, the last couple years of financial progress. Yeah, sure. So again, we got hit with that sort of pain stick at the end of 2022 as well. Growth slowed down pretty quickly. And because we were really pushing hard in selling to sales prospecting, that was really our focus at the time. In 2023, we made a hard decision to do some layoffs. And what we did was we pulled back on go to market. We said, look, we need to go build AI. We need to go and build this new direction. That's going to take dollars. We don't have the money to do everything simultaneously.
50:22So we have to go and pull back and go to market. So we did that layoff in the middle of 2023. And so from there, our growth slowed down. And it was actually a business decision to do that. We said, look, growth isn't the thing that's important right now. The thing that's important is this tech. You've got to be profitable while you're in that mode. If you're going to make that cut, you can't just go and burn the cash until you build the thing so if if slow growth then profit and then faster growth later oh okay that doesn't sound unreasonable it's not unreasonable um so with this launch we certainly are are burning more right we want to make sure there's a big splash we want to make sure that everyone has seen um and is aware of this big change for crunch space um and we now are reinvesting growth again so but we're doing in a more measured way um so that we can make sure that we don't get ahead of our scheme.
51:14So we're going to try to stay as close to even a positive as we can. And as we dip down, and then later this year, we should hopefully fly right back to where we were. I'm putting you on the spot just a little bit. Coming off of some time when you were not focused on growth, how fast can you hope to reignite that for the company this year? Is that like a, we're going to go 15 % or is that like, fuck it, we're going to go 50 % this year and go hog wild. I just don't have a good vibe for like, what does a startup that's going back into growth set for expectations that will be aggressive, but possible.
51:51Yeah. And it is a fantastic, especially trying to predict that and put that in a model for 2025. It gets very, very challenging. Our prediction model isn't that good yet, unfortunately. But the good news is that, you know, we, we feel pretty comfortable that we're going to have double digit growth. The question is, is that's a, like which part of that scale you know it's a wide range 11 or 99 that's right but we're feeling pretty comfortable that we can reinvigorate growth like we've got plenty of leads um the question is is how how much will people pay for predictions that they've never seen before and that are better than they they probably believe it to be um with the precision of recall numbers that we have it's it's it's a little like it's hard to get your head around it's that how good we're at like how do we even do this you know and that's so we spend a lot of time explaining even how we do the forecasts or the predictions so people can understand and start to believe a little bit that maybe we are on to something here well it's a little bit more complicated than the old crunch based score which back in the day the algorithm was like i mean let's call it basic you know basic and that it wasn't it wasn't trying to be more it was a very basic system that was stood up and worked for a while.
53:05But I mean, it was easy because you're like, it's three things like, oh, whatever it was, versus now we're applying much more complicated AI tools to a growing data set. There's thousands of feature vectors that we're looking at across a company to go and make predictions. We're thinking about, you know, how does investor flow go to a profile, right? And how recent is that from an edit that an entrepreneur has made? And is it about time for them to go and raise funding? Do the entrepreneurs look back at those same investors? They're both searching for each other and finding each other on the platform.
53:35Like all of that is just around the funding predictions and the acquisition predictions. And there's a lot of power that's hiding here to make the accuracy or really the precision and recall of, in the funding example, 95%, 99%. It's wild to sort of see. When we got the results, we're like, no one's going to believe how good this is. I mean, that's pretty exciting. Well, it's good to have that versus the opposite, which is no one's going to believe how bad this is. Oh, my Lord. Now what are we going to do? One last one before I let you go, Jagger. You know, we're talking a lot about M &A, a lot about IPOs.
54:13And Crunchbase is, by definition, a late-stage company now. And I'm kind of curious about just how you're thinking about building versus selling versus eventually going public. Like, what's the vibe from your view on what's the next kind of like major financial step for Crunchbase? yeah i mean i i go to my country's profile and i refresh the uh acquisition prediction uh all the time to sort of see what the system's like um you know it's right now i think it says we're probable that we're going to get acquired and we're unlikely to go ipo no that's probably accurate that's probably accurate um so you know i think i like i'm gonna just leave it to my foundation if i want to do the talking for me at this point um well i i i looked up i i don't do it often, but I did log onto my Carta account and I was like, yeah, it's still there.
55:00So, you know, feel free to pay for my children's private school because I learned what that costs recently and I wanted to cry and vomit. So, literally wishing you all the best. And with my journalist hat back on, thank you very much for coming on, Jagger. I appreciate it. And for folks who want to try all this stuff out, where should they go on the great wild internet? Crunchbase.ai. Crunchbase.ai. All right, Jagger. Well, I appreciate it, man. I'll talk to you soon. Thank you. And best of luck this year. All right. Talk soon. Take care. We'll see you all next week. We had a full amazing week next week.
55:31Wednesday, I think we're having Vlad from Robin Hood and Raul from Superhuman. Is that correct? Producer Matty. Oh, wow. There it is. We got a yes, chef. We have two amazing guests on Wednesday and then news will be there on Monday and Friday. Have a great weekend, everybody. Bye bye.
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Today’s show: Jason interviews Bryon Hargis, CEO of Castelion, about the United State’s hypersonic technology gap with China, how we’re catching up and what it will take to win the hypersonic missile race. Alex interviews Jager McConnell, CEO of Crunchbase, about their newly released, scary accurate, AI powered predictive models.
Timestamps:
(0:00) Episode teaser(1:14) Introduction of Byron Hargis and Castellion's mission(2:20) Significance of hypersonic munitions(5:55) Impact and challenges of hypersonic systems in defense(7:16) Castellion's development and cost of hypersonic weapons(9:39) Squarespace. Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWIST(12:28) Shift in defense contracting and venture backing(18:25) Sales strategies and founder insights in defense startups(19:38) LinkedIn Jobs. Post your first job for free at https://www.linkedin.com/twist(21:10) China's manufacturing capabilities and defense paradigm shifts(24:37) Role of automation and robots in manufacturing(28:58) AdQuick. Visit https://adquick.com/twist and mention TWIST to get $1000 off your first campaign.(31:37) Crunchbase's transition to predictive insights(38:01) Crunchbase's technology stack and AI models(41:36) Financial implications of AI-first model for Crunchbase(48:43) AI integration challenges and financial performance(52:50) AI-driven predictions and their accuracy(54:24) Future prospects for Crunchbase: Acquisition vs. IPO(55:22) Upcoming guests: Vlad from Robinhood and Raul from Superhuman
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