This Week in Startups - Castelion Hypersonic Missiles and Crunchbase’s AI Powered Predictions | E2088
Episode Date: February 22, 2025This Week in Startups is brought to you by…Squarespace. Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWISTLinkedIn Jobs. Post your f...irst job for free at https://www.linkedin.com/twistAdQuick. Visit https://adquick.com/twist and mention TWIST to get $1000 off your first campaign.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 SuperhumanSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpCheckout Castelion:X: https://x.com/CastelionCorpWebsite: castelion.comCheckout Crunchbase:X: https://x.com/crunchbaseWebsite: https://www.crunchbase.com/Follow Bryon:X: https://x.com/hargsbLinkedIn: https://www.linkedin.com/in/cbh/Follow Jager:X: https://x.com/jagermcconnellLinkedIn: https://www.linkedin.com/in/jager/Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(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(19:38) LinkedIn Jobs. Post your first job for free at https://www.linkedin.com/twist(28:58) AdQuick. Visit https://adquick.com/twist and mention TWIST to get $1000 off your first campaign.Great TWIST interviews: Will Guidara,Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta,Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason’s suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916
Transcript
Discussion (0)
It'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!
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Hey, everybody, welcome back to this week and starters.
I was 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 Castellian is really focused on bringing back deterrence through strength.
And if you kind of subscribe to the Reagan air piece through strength,
how do you maintain peace?
You have to have actual strength
against an adversary,
and 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 a 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.
We see things come out of battleships
and submarines.
They look like they're going really fast.
But 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.
And 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,
or like a re-entering space vehicle,
they all do enter hypersonically.
So, like, typically, like,
if you're at orbital speeds
and you're re-entering the atmosphere,
you're coming in at least at Mach 25.
And so ballistic missiles, you know, space capsules,
everything, they 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 were really actually referring to a subset of that.
And so very specifically, like,
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 re-enters and comes back and it follows like the same arc that you would throw like a baseball.
Hypersonic weapons systems, 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 pure adversary such as China.
They put in tremendous investment to basically negate American capabilities regionally, close into the coast of China.
a 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. Airplanes go under Mach 1 even, right? We fly below the speed of sound in commercial
airlines, but there's boom, a new, a member of the Twist 500 and the supersonic passenger plane
and the Concord obviously would break Mach 1. But we're talking about five times the speed of the
Concord. The second note is, these things tend to fly closer to the ground. They're not interbalistic.
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, yeah.
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, you know, whoever was dropping by,
bombs on Israel, the Iron Dome wouldn't catch a hypersonic. Am 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 if it's sports cast this, many people are listening.
Absolutely. So this is some of the team. We develop a lot of the hardware in-house.
Very, 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.
We 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 is absolutely necessary that as a country, we'd be able to do that. Because 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 a few very high-end missiles.
Well, will these costs, do you think?
What do you think they're going to cost ballpark?
Like, 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 and size system
currently costs the U.S. government.
If you compare them on a capability basis,
like what could this weapon do versus 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, you know, I've been behind a desk here doing podcasts.
Why didn't the military industrial complex
make 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,
all 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 in 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 a thousand X,
you know, based on the camera and the whole set.
I'm kind of getting at why economically, politically,
politically, systems,
what's the issue here of this opportunity
suddenly emerging to take 90% out of the cost structure?
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Fundamentally, like 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.
Like, if you had a traditional prime, build your cell phone,
it'd 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.
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 expenses are paid for.
You have essentially a kind of like piece.
East time 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, you know, a handful, of course, they are going to end up being more expensive. So like you have to, 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, like the space market, which I'm very familiar with was like,
this pre-SpaceX on both launch,
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.
The 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.
And my understanding,
this paradigm shift correctly? Yes, there's absolutely a paradigm shift. And 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's going to increase the cost greatly, if 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 is now longer.
It's going to cost 3X as much.
But this is what you want it.
And 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.
They get their whatever.
strip steak, they like the 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 it to stay. 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, here'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 this space is now venture backable.
Like, 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, you can,
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
and all my friends who are SpaceX venture capital
his investors founder fund, etc.
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.
Anderl's 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 SaaS 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.
And 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 C 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. So in six months, nine months, you had money coming in from the government in the bank account. Correct. How was 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 a
defense in 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, like, you're told what you will work on.
And so I found like being part of the sales process actually helped, you know, like pick what
we are working on, what we're trying to solve.
This is like, there's two very important founder lessons here.
and we like to always point them out
when we're talking to Chris founders.
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.
So 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 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? Is 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 are, 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.
And 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 on a small business,
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Terms and conditions do apply. But this is so important because to our previous discussion about the
paradigm shifting, I think what I'm taking from this is a really important insight, which is you can
build exactly, the sales team can get in there and build exactly what the customer wants.
but 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's going to happen?
You look at the field in Ukraine
and what that has wrought,
which is basically they're not even fighting with industrial and military complex.
They're zipping drones around with grenade strapped to them.
This is a whole different warfare.
So maybe your thoughts on,
where is China right now?
How far is American manufacturing behind them
and how do we close the gap?
Well, in the munitions space,
when a lot of the defense manufacturing space, honestly,
I might, 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. But 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.
Warfare 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 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. So 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 the 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 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.
It'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.
What?
Yes.
It's pathetic.
These missiles, the missiles.
you're building, all due respect.
The complexity of building a missile and a cyber truck,
these don't seem...
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 task because you're still like
a thousand is a very large order.
Well, since we're going there and we're going to be.
be super candid here in this interview. I like having candid guests. Thank you so much for educating us.
Would, 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 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 a lot. That's a
only 3,000 missiles out of your factory a year, so I'm just picking something easy. Let's even
dump it. A hundred 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?
Most 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 process,
is 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.
So college educated, associates degree, down to even high school educated, able to think logically
and be thoughtful for an eight, ten hour shift is enough.
They'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?
Castellia.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
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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.
I 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 CrunchBased 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 exercise.
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 $500.
And 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 to see you?
So, I mean, first of all, it's been, it's been a little while.
And since, you know, we were in touch, Crunchbase has watched the AI wave explode.
And when I think about Crunchbase, this, you know, 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 Crunch Race was like,
oh, we're going to go in this direction.
Sure.
And I remember very clearly because I was using ChatT,
and I was like, oh, this was so cool.
And everyone had a sort of moment of like,
this is going to change everything.
And I was like, oh, this is going to change everything.
And 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.
I was like, yeah, kind of.
Except once our data goes into the LLM, it's going to never come out again.
Right.
And then the oil is being made somewhere else that we're not a company anymore.
So 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 a country face.
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.
So 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, 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
next in CrunchPace? So can you go and start?
So historical data is looking back. It's knowing that CrunchBase raised $106 million
thought it's history. It's everything that's kind of in the rearview mirror. But your point
is that CrunchPace 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.
If you go and look at a profile now, you'll see the history of the company.
But what you don't see is how this profile changed over the last 17 years to get to where
it is.
And then how has traffic flow changed on that profile of 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. All of that is this engagement data and historical edit data that when we looked at it
and we again said, well, the whole of this unstructured data, what do we do? We just pumped it into
chat CBT 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 to, 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.
Is that fair?
That's 100% correct.
In a way, like Chat 2BT is like this.
It took all the historical data of the public web, and it's not trying to predict the next
word that makes sense, right?
And we're doing the same sort of thing in a smaller context of CrunchFace, saying all the data
we have unstructured, can we go and figure?
out what is going to happen next in a company, that first prediction of whether it be funding
or acquisition or whatever it happens to be. So how many different things are you predicting now
with the new system you've put in place, which came out earlier this week, I believe, actually.
And frankly, Jagger, how accurate are you in these predictions thus far?
Yeah. The first question is easy. The second one is harder to answer. The first one,
we did 18 insights and predictions.
So we're shifting the focus of it's not just historical now.
It's what's happening now at the company and what's going to happen.
And that's insights and predictions by definition.
On the predictions side, you've got funny prediction, acquisition prediction.
Are they going to close?
Is the business going to close?
Are they going to do layoffs?
Are they growing?
So there's a number of these different angles.
And some of these things we're not going to put onto the website.
You're not going to go and see, like, are they going to do a layoff?
But that is an interesting prediction that we're using more on the risk side,
which is more on the API side.
So 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.
Like, wait, what does that mean exactly?
Right.
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, 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's 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.
That's correct.
That instruction 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're saying,
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. It's still a very, very small number, right?
So, you know, people that I talk to still sometimes have kind of an old crunch base 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 crunch space all the time.
But if you think of crunch space as a wiki back in the day, it's cool because everyone got to participate.
And it sounds like the new crunch space 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, surely the 80 million people using CrunchFace is an important part of the, the, the, the, like how, how Crunch Face works.
But, yeah, one of my biggest frustrations is when I go and say, you know, someone says, oh, I know exactly how much time is.
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.
But 2014 is a useful data point because you joined in 2020.
15 and took over our CEO
when it was spun out as a private company
for those folks who don't know,
emergence, Mayfield, Omeres.
And then most recently,
Jagger, you raised from,
as I scroll through my notes,
frantically,
you can build me out.
Alignment growth.
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 it's a lot of capital.
You guys have raised $106.5 million,
according to crunchbase.com.
What did that last $15 million
unlock for the company?
because that was in 2020,
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.
You might remember a lot of the data companies out there
took a beating as prospecting
became less important to the sales prospectus of the world.
So we also took that opportunity to do this pivot.
So Chat Chatsin Bita came out.
This is when we had a sort of aha moment.
And we said, let's not blow all this capital,
just going and trying to sell.
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.
And I was just kind of curious, what did Crunchbase pick as it's kind of like model paradigm?
Are you guys using, you know, MetaSlamma models or if you built somebody 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.
and some of it is our own stuff.
We use open source, like TensorFlow to go and do a lot of the ML side.
We certainly are using OpenAI to go and handle a lot of the unstructured data.
In our testing, it seemed like the best.
But we're still to the way that we can kind of move in and out,
depending on what's better and what's cheaper, honestly.
So sort of that combination.
So like when DeepSync came out, we certainly were like,
hmm, that's interesting.
They're like, maybe not.
So there's an ongoing conversation.
But the nice thing is I think every software and data company that uses the stuff needs to be thinking about how to make 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 that kind of bucket of cost?
Does that now take up a much larger?
portion of CrunchBases OPEX than like the old AWS bills back in the day did.
I'm trying to get a handle for like, what does it like to change your company towards
an AI first model?
And how does that shake up your profit and loss statement, frankly?
Yeah, it absolutely does.
There's a short answer.
Certainly, it's a huge line item that didn't exist two years ago.
And we're watching the people using our Shunch Bay Scout today just understand how much that bill
might be going up.
You know, so it's an interesting pricing time.
And how do we think about passing those prices onto our customers ultimately, right?
And so 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 sort of LLM world, that also helps us out.
So there's a lot of way to see right now in terms of not.
I mean, not first, but it's hard to sort of plan for.
Certainly.
I think that's a big challenge for CFOs.
Well, it's kind of cool because I feel 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.
Right.
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 to an AI agent that goes and builds it later.
So again, at the end of the day,
and what is the most valuable thing?
It's the day that no one can have access to.
Even if you have this circle data behind a paywall,
I think you're still vulnerable.
Because I think there's going to be AI in the feature that goes
and social engineers its way in and gets its data.
Like, we go and say, AI, go and have all the day there is in the world,
and it says at any cost, like that AI is going to go make phone costs.
finally AI is going to go and pull that data down.
It's going to create six different email addresses, rotate its IPs, use three different agents
from 40 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.
Yeah, we certainly have had some of those sorts of offers.
Like we are, we are avoiding those.
We, of course, do our best to block crawlers.
We use a lot of tools to do this.
Like Trimer X 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 Internet.
I will never put engagement on data, obviously, onto the,
to the internet.
So no one will have access to that.
But if we are using forward-looking stuff,
you can call that all day long.
Predictions change every moment.
So you'd have to be calling us constantly.
And at least today,
there's no way to like simultaneously crawl
every single page that CrunchFace has
and pull it all down simultaneously.
Like 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, the, the, the, the, the,
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 CrunchSpace 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 CrunchPace
thinks is going to happen next.
And here's kind of the state of the business.
There'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,
Jaguar, can you just tell them what that is?
Yeah.
So basically, the idea here is there's a lot going on in CrunchFace 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 home page 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
it will just pop up on your feed or a new prediction for funding, whatever it happens to be.
And you can click it and 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 it's slightly different data because, you know, private market are real-time, live.
Everyone can see the information.
But 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 CrunchSpace now with this new homepage.
Yeah, I think that's right.
Internally, what we're saying is like, what's the TikTok equivalent for crunches, you know?
Like, how can we create a sort of stream of interesting stuff?
And that's like the dream.
I don't think we're there yet.
Just 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 you can stay on beat.
There's another thing, though.
You mentioned it earlier, but I haven't gotten to touch on it in particular.
It's CrunchBee Scout, which is,
For my experience, kind of like an AI agent that I send forth to do tasks, and I presume you've stuck with the traditional crunch-based dog branding because it fetches things and brings them back.
You're 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.
It'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.
So if you want to merge those 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 crunch-based data that 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 is 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.
There'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 French Base?
I don't want people asking who is our favorite baseball team and having like strong answers
there.
So how do we scope it to Crunch Space?
How do we give it access to the countryman status?
So to merge those two things together,
and it's 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?
What 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 base dollars.
So wait, wait, not not dollars.
It's sense.
Penny, pennies and dollars.
I was like, dude, I did a lot of testing.
Should I send you a check?
But it is maybe more expensive you think it is.
So it is a, so how do we make that efficient and still keep the user experience good?
It's 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 to make it better.
And that was fine.
It's actually where the most amount of workers is going to be put in.
Going back in time.
So the round from 2022, the Series D,
you guys were talking about having, you know,
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 added like 9 million in NetanyarR 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 into black because the market's uncertain. So can you just fill me in with like,
I don't know, the last couple of 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, pretty
quickly. And because we were really pushing hard and selling the sales prospecting, like that was
really our focus at that time. In 2023, we made a hard decision to do some. I,
And what we did was you 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.
So 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.
Like if you're going to make that cut,
you can't just go and burn the cash until you build the thing.
So if slow growth, then profit and then faster growth later,
oh, okay.
That doesn't sound unreasonable.
It's not unreasonable.
So with this launch, we certainly are burning more, right?
We want to make sure there's a big splash.
We want to make sure that everyone has seen and is aware of this big change for
crunch base.
And we now are reinvesting growth again.
So what we're doing in a more measure.
way so that we can make sure that we don't get ahead of our ski.
So 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 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 yeah 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 the good news is that you know we we feel pretty
comfortable that we're to have double-digit growth.
The question is that's like which part?
When you're trying to 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.
The question is how much will people pay for predictions that they've never seen before
and that are better than they probably believe it to be with the precision of
recal numbers that we have is it's a little like it's hard to get your head around.
And it's 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
forecast or the predictions so people can understand and we'll 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 it wasn't trying to be more.
It was a very basic system that was stood up and worked for a while.
But 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's made?
And is it about time from them to go and raise funding?
Do the entrepreneurs look back at those same investors?
They both searching for each other and finding each other on the platform?
platform, like all of that is just on the funding, 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
of recall of, in the funny example, 95% 99% just it's just, it's wild to sort of see.
Like it's when we, when we got the results, we're like, no one's going to believe how good
this is.
It's too good.
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.
Exactly.
Now what are we going to do?
One last one before I like to go, Jagger, you know, we're talking a lot about M&A, a lot
about IPOs.
And CrunchPase 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 CrunchPace?
Yeah.
I mean, I go to my CrunchPage profile and I refresh the acquisition prediction.
all the time.
You sort of see what the system's like, you know,
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.
So, you know, I think I'm like, I'm going to just leave it to my presentation.
If I want to do the talking for me at this point.
Well, I looked up, I don't do it often, but I did log into my card account.
And I was like, yeah, it's still there.
So, you know, feel free to pay for my children's in private school because I learned
what that cost 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.
com.
That's the place.
All right, Jagger.
Well, I appreciate it, man.
I'll talk to you soon.
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.
Wednesday.
I think we're having Vlad from Robin Hood.
and Raoul from
Superhuman. Is that correct?
Producer Maddie?
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.
