Predicting Fundraises, Acquisitions, and Emerging Markets with AI Data

Hey, welcome to the Next Wave podcast. I'm Matt Wolf. I'm here with Nathan Lans and today we're talking about the future of investing. We're going to be talking about how you can leverage AI using tools built on top of CrunchBase to figure out what to invest in. Uh what your sales team should go and focus on. All sorts of really cool strategies to leverage data and AI around the world of investing. Nathan in this episode had one of the most brilliant ideas I've ever heard for a salesperson. If you're actually out there trying to sell your product to companies, like you need to stick around cuz this idea I think could totally change the game for your business. But this is an amazing episode. It's with Jaggery McConnell, the CEO of Crunchb. And uh I'm not going to say anymore. Let's just go ahead and jump in and talk to Jagger. We're going to jump into what Crunchb is doing with AI, how you can leverage Crunch Base. We're going to get a little tour, a demo of what Crunchbased AI is capable of and then we're going to talk about the future of AI and investing. So, thank you so much for joining us, Jagger. It's great to have you on the show. Great to be here. Yeah. Awesome. Well, let's just dive straight into it and and talk a little bit about Crunchb. I know that Crunchb over the last uh I don't know, however long, maybe the last year or so, has really really gone deep into the AI world and sort of shifted what Crunchb is into like an AI first platform. So, let's let's talk about that. Like what what is the sort of grand vision with Crunchb? Who is it for? You know, what's what's the plans with it? Let's just get right into it. Look, like we we've been for the last 14 15 forever years. Um this sort of historical record of what's happened with a company and we realized with AI happening and like all this sort of it's yes, it's structured data, but but huge amounts of structured data. Were there insights that maybe were more interesting than what's happened in the past with a company? Can we use AI to figure out what's going to happen next with a company? How accurate would it be if we go and try to figure out, you know, what's what next funding round is going to happen with what company or what company's going to get acquired next or who's going to go public. So, we took all of this data, all of our historical data um and combined it with data that no one else has access to. Things like our usage data anonymize of course sort of looking at trends of investor flow or corporates flows and said what can we learn from all this and that's where we launched this sort of prediction engine that now is it just wasn't possible a couple years ago just because given the pabytes of data that we have sort of behind the scenes here so it's it's pretty exciting times yeah I'm curious is so is are the models that you're using are are they like external models or is this stuff that Crunchb is sort of developing internally. Yeah, it's sort of a combination. Obviously, like we don't have the billions, tens of billions of dollars to go and and and build our own stuff, but we so we certainly are leveraging the latest and greatest tech. Um, as you might imagine, Open AI as part of that equation, TensorFlow as part of that equation. So, there's a lot of these the sort of latest and greatest tech, but we're building our own stuff on top of it, right? So we're going and and and taking a lot of the proprietary stuff that no one else would build because they're not crudbased and we're leveraging the pieces that we need to to pull the right spaces. So in other words, how do you go and generate the content of what how we present to the user? Sure, we're going to use Open AI for that, but the end of the day, there's still a massive machine learning problem that that's hiding in the Crunchbased side that it takes more than just uploading it up to to chat GBT to sort of answer for us. It it's really fascinating to me like what what sort of like data points would you even look at to sort of predict the future because that's kind of what Crunchbase is trying to do, right? It's kind of trying to predict what companies are going to IPO next, which ones are sort of acquisition targets. Like what are we looking at? People already kind of use Crunchb that way, right? like in the past. That's I think it's like a genius evolution of the platform cuz you know for context I lived in San Francisco for 13 years did some tech startups know a bunch of VCs and people always check crunch base and they look at who's in the round or when did they raise around or what's recent news. You're absolutely right though the use case before was are they going to raise money soon? So they would go and look at a profile and say well it's been about 18 months is they're probably about time for fundraising and that would be the one data point that they're using. To answer the question, we're we're using thousands of feature vectors to go and figure this out. So like an easy to understand example would be is a company going to go and fund raise soon? So we'll go and say sure, is it about time for them to fund raise? Then we'll go and look at the entire industry and we'll say okay well like how long does it usually take for a company to fund raise in this space for this size? But then we'll go a little deeper and we'll go and say well has anyone updated that company profile recently? And if the answer is yes, that gives us a little signal that maybe there's something going on at the company. And then another signal might be has investor flow to this profile changed significantly compared to the past. So if there's more investors looking at the profile, well, what would drive them to go and look at this profile? And then how are they looking at it? Are they searching for it? They just organically came upon it or was it a link or did they come from a Gmail account, you know? So you have this sort of like two-way sort of conversation happening on our profile. Then is the investor or the entrepreneur looking at those same investors who were looking at them? Well, that's another little signal, right? So each each one of these steps along the way gets us more and more confident that a funding round is maybe happening behind the scenes and if it is can we can sort of signal at least some level of confidence out to our end users. And now that's just one again of thousands of these things. What's happening in the news? just how how is traffic to the site in general? Like there's a lot of signals um that we can go and combine together to sort of find the right pattern to say this is a company that's going to fundra soon as an example. Yeah, that makes a lot of sense. I mean just thinking about it. Yeah, if a company's in there going and updating their Crunchb profile and adding new information, they're probably doing that because they're expecting, you know, investors or people to be going and looking at that page. It can't be it can't be the only signal, but it certainly is one of more signals, right? and and and when we the nice thing about AI is we don't really need to figure out exactly the right combination that means it it's just like it can look at every company that's ever raised funding and historically look at all the data we had collected at that moment to say well here's the 16 different paths of a company that might lead to a funding round um that's and that that gets me excited right because this is this is stuff that no one else can do it doesn't matter which competitor we're talking about they don't have that 80 million people using our our site um to go and drive and inform those predictions decisions since you've actually pivoted to more of like the the sort of AI based analytics of like you know figuring out where the you know when there's going to be an IPO or who's going to raise or those kinds of things. Have you sort of like figured out the accuracy level of it? Like how how accurate has it been so far? Yeah. And this is maybe the biggest challenge is that when anyone ever tells you, hey, I I've got a prediction engine, you're like that's garbage because every prediction engine ever is garbage. So this is very different. Um and the the the so we do do a lot of analysis. We can do a lot of back back testing and sort of figure out how would we have done. So you take sort of twothirds of all of our data and you build the models on that and then the remaining third you use to sort of test to see would it have done it correctly had this model existed. Um and by using that that that framework and looking at the kind of companies that we're trying to make these predictions against uh we've got some there's there's uh precision precision and recall and we have a 95% precision on fund raise and 99% recall. So in other words when we make a prediction about a fund raise it's 95% correct and we make predictions against 99% of the companies that match the criteria we're looking for. So, it's a it's ridiculously high how accurate we are. Now, now you can get you can that's that's the easy answer. The more complicated answer is um as you add time scale to it, it gets much harder. So, who's going to fund raise tomorrow is a very implausible question to answer. Crunch base will do a better job than you guessing, but it's still going to be fundamentally a guess. This is actually what I was going to say. So, before we got on here, I checked a few companies I know when they're fundraising. super you were super accurate on they were going to be fundraising. Uh a bit off on the timelines, right? So So that's and so we put that in there. So we say, look, like here's what we think, but we're never going to be 100% confident. Oh, in the next 6 months it's going to happen, but we might say in the next 80 like 80% chance it's going to happen in the next 6 months because that timing scale, uh there's so many factors that are impossible for us to know unless we're inside the brain of the founder to know if they're going to fund raise. But that signal, getting back to a question you asked earlier, helps the use case of, well, I'm an I'm an investor. I'm not looking at this company, but maybe I should be because it looks like Current Space thinks they're going to be fundraising soon. Or I'm a a large public company. I want to acquire this company. They might be going to fund raise soon and I want to get them before they raise that money or or or or increase their valuation. Um, there's a lot of different uses for even just that one fundraising prediction among the the now almost dozen different insights and predictions that we have. I mean, I think we'd be great to just jump in and and sort of get a little demo, a little tour of of what it's capable of and and you know, this is like a kind of a YouTube first podcast. We we like to be really visual and show what we can. So, love to jump in and and just sort of get a sneak peek and give people a little demo of what it can do. Um, so this is the new homepage. That's very different than the old homepage of yester year. Um, and you'll notice that we're right up front saying sort of the the new data that's coming in. I think we've got um the latest predictions in just the last 30 days. So just this thing is this engine is constantly running, constantly updating, trying to find not just the next funding round, but also you know what is the next acquisition, what is next IPO, which companies do we predict to grow. So, we're really looking at like a lot of different aspects of what a company is. We we've got this new sort of AI agent that can help you get sort of navigate Crunch Base, but you can just type in, you know, Blue Sky as an example. And now we're looking at the Blue Sky profile, and you're going to see right up front, and this didn't used to be there. Now, up front, we put some of the biggest predictions up at the top. So, in Blue Skye's case, we think it's probable they're going to raise another round of funding. We think that there is likely that they're going to get acquired at some point, which not a lot of people are talking about. and we don't think blue sky is going to go public. Certainly there's no signals that they are. And then as we scroll down, uh we sort of took this approach to the profile page of you know what is the stock ticker equivalent of a profile. So there's there's no way we can put valuation day by day over time, which is what a stock ticker does. Um but what is the private company equivalent of that? Um, so we've got these things called heat score and growth score and and and you know there's a little definition of what these things are, but like looking at how the company is interplaying with the the public web, how it's interacting with us, how is the um how does it rank among all the other companies within our our corpus of companies that we track. Um, that gives us these axes of data like this heat score and growth score. Um and that again drives other pieces of the application and even some of our predictions. So we understand what's happening and what's going to happen next to the company. You can play around with this, you know, and sort of make it do different different whisbang things. So if you're a data nerd, you can kind of get into this. And all the the raw data is available in the API, of course. And then as I scroll down, you're going to find predictions and insights. So here's where I can see um we predict they're going to be growing. We don't just say it's going to be growing. We actually explain in with our own words why we think that that this company is currently growing and and if there's a a growth prediction, why we think it's going to grow in the future. And then here's some of these predictions like we were talking about. Like here's we think there's a 37% chance that they're going to go and fund raise in the next 6 to 18 months. There's a good chance they don't fund raise, right? So we're kind of transparent that not these numbers don't necessarily lead up to 100%. Because there's still some percent chance that they're not going to raise at all. So we'll go and put that in there. Are they going to get acquired? We give reasons as to why. And the API we give all of the detailed reasons, right? So we actually give percentages and we go and say here are the drivers that that that that we believe lead up to this thing. So, as an API user, you can discount things that we think are true that that maybe you don't want to sort of incorporate into the prediction. Um, or you can just use a prediction score on top of your own prediction algorithms, which is what a lot of VCs do. They sort of use as an input into their own proprietary algorithms. So, this is some of the stuff that we're doing nowadays. Um, there's a lot around um like we gro all the the news that is happening on a company and sort of summarize it for you. So, you don't have to read 30 news articles to figure it out. We sort of bring it all together. So there's just a lot of different pieces that help you understand. And of course, we still have the funding data, but that's all sort of just drivers now into these sort of bigger meteor questions that we're trying to answer. there's a lot around even on that homepage um you know sort of seeing what's important what's trending what's happening in the in in the the the the all the data that we're tracking and you can decide I want to look at these particular predictions for these types of industries and sort of get a daily feed of all the stuff that's happening um and what we think is going to happen next uh in these companies which is pretty exciting as well. So, lots of interesting use cases. Um, and again, you could always go and have a conversation with Scout. Um, which is our little sort of dog fetching thing. Uh, that would go and sort of do the sort of some of the logic stuff that you couldn't do in in Crunchb before, right? You before you couldn't figure out sort of what's the business model of this company or um how does this compare to another company or how do public events affect these particular private companies. Um, now you have a way to have that conversation with Crunchb um programmatically, which is kind of cool. Everyone everywhere is talking about AI agents right now, but here's the thing. Most companies are going about it all wrong. This guide cuts through the hype and shows you what's actually working right now. HubSpot has gathered insights from top industry leaders who are implementing AI agents the right way. You'll discover which agent setups actually deliver ROI and how businesses are automating their marketing, sales, and operations without replacing their teams. get it right now by scanning the code or clicking the link in the description. Now, let's get back to the show. Any questions have been that have been like really really valuable? Like any any sort of like best practice questions where you're like if you ask this, you're going to get some, you know, some some really good stuff out of it. Yeah, I mean there's there's meaty like policy questions, right? Like so we see whenever some something happens in the government you know people come to Christ they go type in how are tariffs going to affect this company and uh and it and it will do a pretty good job of sort of speculating and sort of figuring out what what's going to happen next. I think those are those are some of the interesting ones. And then just the the analysis, right? it's it can be hard like if we go over to AI search builder. So now like you can just natural language in your your query and it's going to go and build sort of these very complex searches cuz you know you think about multi-join searches and how to build those. It's always been sort of cumbersome. Now you can say show me all the CEOs at companies where they used to work at Salesforce and then they uh went to Stanford. you know, like you could type that all in in a huge uh run-on sentence and it will go and and show you exactly who which companies do it because it builds the join for you. And just that alone is a huge timesaver for our our users. I wonder what this is going to do to like startups. Uh like it feels like it's going to like really increase like the velocity of rounds like how how fast rounds will you know close because you know you guys are kind of creating like the ultimate like FOMO machine right where like people are like oh my god look it's a hot company they crunch base just told me it's hot. I I I got to get in. Yeah. I mean, anecdotally, there's it's hard for us to have data on this, but but anecdotally, we've heard that when we go and signal that is very imminent that a company is fundraising um that they get a lot of inbound interest from investors, it's because there's now awareness that it's happening. Oh, you notify people or we don't, but people set up their own alerts, right? I can just say, you know, um show me biotech companies uh that are very likely to fund raise, right? I can just make that search. It's gonna go and this is a live demo. We'll see what happens. Um um but there you go. So it did it said industry is biotechnology funding predictions here is very likely. So these are all the companies are very likely to fund raise soon. Um and we can go and and and create an alert off of this. Right? So you've got investors who are subscribers of ours say when a new company shows up on this list, shoot me an email, right? Go and let me know that that's happened. Um and so we don't need to set them send them emails. They'll get their emails themselves because they've set up the alerts the right way. Yeah, that's awesome. So, I could do like AI coding or something like that and I could just like as soon as some you guys have a new prediction in that category, you guys will email me or something. That's amazing. Yeah, and that's and that's just one one of the predictions. Like another very common one is I'm looking for these sorts of companies to acquire. Let me know when a company of this size, no bigger than series C, I don't want them who's raised more than $100 million, whatever it is. When a new one shows up is very likely to get acquired. let me know because I I'm in the space of acquiring those companies. So, a lot of corp dev departments get excited about that. Now, are all the companies that are in here are they all are they all like self added or is it is all the data sort of pulled by crunch base? In the 2014 it was 100% from our users. Um today it's about 5%. So, we've sort of transitioned but the brand belief is that still like if you ask our users how where do we get our data from? They're mostly will say it's user generated content. Um, but really that's only for the smallest companies, ones that haven't had a news article yet. They no one knows they exist. They go and put themselves in. They sort of announce themselves on Crunch Base. Um, but the reality is we have we invest tens of millions of dollars now every year into getting data from a lot of different ways. Uh, a lot different sources. We have 5,000 partnerships of data coming in. Um, we of course go look at government filings. Uh, we've got lots of data partnerships that go and give us uh seed data. And then we have our own AI systems that go out and find the data. So if we don't if we hear about a company that that we don't isn't in our in our data set. Uh we very actively go and fill out the profile as best as we can assuming it fits a certain set of criteria. Uh and and that plus the engagement data plus the generated data, right? like the the biggest source of data now is Crunchb generating its own data on the data that we have. That is uh that huge huge huge data set that we've collected over the years now. But not to not to devalue the usage the the user data editor the user generated data. That's still very important stuff, right? Yeah. Because I was it just seems like it could be such a a really good discovery engine for very, you know, small new startups, right? You you want to make sure you're in crunch base because then you're sort of in that algorithm. You're in that system where now people might discover you if they're looking for um you know, small startups in X niche, right? So that that's why I was curious like can companies just go and sort of input their data in there to make sure that they get discovered when people are making those sort of queries. Yeah, they absolutely can. And and it's and we do a bad job of this like giving reasons why you should uh because they ask you get discovered by VCs who wouldn't normally have found you. And if you're like well I don't need I'm a bootstrap company. I never want venture funding. I don't need to be in Crunchb. Job seekers is is like a good solid 10% of our users are going and researching your company to see if it's a company you want to work they want to work at. um if you're not in there and it's not up to date, they're like, "This this this isn't something I want to go and participate in because they couldn't gro your website or they couldn't find your website or whatever the case happens to be, there's a good chance that Crunch Prec's profile comes up higher than the website of the smaller company." So, it's usually a good idea to have uh that data correct in Crunch Base. It used to be traditionally like VC backed companies that were mostly on Crunchb, right? Is it is that still the case? Like, you know, are there companies that are private companies that are nonVC? like you just said that you suggested that they should do that, but also like I could see this working for even like public companies like just like a general tool to help me guide my investments in companies in general. Um yes, I actually it's it's a it's a minority part of our users are actually VCs who have funding that that that want to go invest. So so that is an important use case to us but it's certainly not the biggest. You know you'll see use cases across sales. Um let me go and find the companies that are going to have money soon. I'm going to go and start a sales cycle with them is a good time and and and it's better than waiting for the fundra to happen too right because everyone knows when the fundra happens. If you can know it 6 months a year in advance maybe you can sort of get entrenched earlier than that. So that's uh a pretty big use case for us. I mentioned corp dev, right? Anyone who's buying companies, that's important. Um we do have a on the on the self-service side, we do have job seekers who go and are are are paying us to say, I want to find hot level companies in my area because I want to be there to at their early stage, right? So you've got that use case pretty heavy. um a lot of researchers and analysts um and that and that from the largest consulting firms all the way down to students who are trying to figure out sort of some interesting trends. So you've got a lot of that sort of use case uh lurking in crunch space. You know it's really exciting to sort of see how many different people have different uses for that private company data. Right. Right. I know there's crunch fund which has no connection. Right. like my you know I still get confused techrunch crunch fun you know I chatted with Michael Arington back in the day I have a crazy story where I was raising money for a startup and we had a call and uh he's like I'll be right back I I got to go give milk to uh my baby goat or something like that I'm like okay cool we kind of like became like Twitter friends after that and occasionally chat but uh so my mind still connects all that but but it feels like you guys you know you guys have all this data you know which companies are going to raise Some somebody should be like piggybacking off of that like making a lot of money off this like you guys have all the data. Find out the right companies get into them even like small allocations. Yeah. I mean we we've we've toyed with the idea of doing ourselves honestly like one of the ideas that we have lurking out there. Uh it's it's on the road map for not this year but maybe some future year. Um is so you just saw I I I showed you a profile that has sort of our equivalent of a stock ticker right which is this growth in heat score. Um what if we aggregate those right? What if we do that across entire industries? So now you've got the AI heat score and growth score over time. We're using all our stuff. We're predicting is this moving up or down in the right direction. What if we worked with maybe a secondary provider and created a little index for those companies so you could invest in some subset, right? U the retail investor maybe start playing around with this. It's still an idea. Uh we've sort of had some early chats about it. Um, but you sort of stumble into a lot of regulatory issues pretty quickly and the ROI is way out there, right? So, like, yeah we could start a fund. It's a 10-year thing. We're a little bit more focused on the present than than than that far out. Yeah. I'm kind of curious about like what the sort of future of investing looks like. And I don't necessarily know the exact question to ask because I don't don't know what I don't know when it comes to like AI and investing. Um, but I'm I'm I'm trying to figure out like if if the the general population has access to the information and like what's likely to sell next and you know this this information is, for lack of a better term, democratized, right? The the common folk could have access to the data. I'm curious about what the world looks like as we move closer and closer to that reality. And I'm just curious if you have thoughts on that. Yeah, I I mean I I think there's a lot of potential disruption a lot across a lot of different industries. data is included in that and that's honestly why we moved the way we did like I would argue funding data is already commoditized right so like yes we I we think we have the best yes there's a lot but if we just kept rusting on those laurels like that that that company goes out of business when all of the data gets absorbed into our LLM masters right like they're going to like there's going to be uh you know what else is there once it goes in it's not going to come back out so so facts are a dangerous business to be in So speculation and predictions is at least dynamic and changing. And I think I think a lot of data companies are going to be thinking like that. If you deal even in if it's hard to get facts or you've got what once it if if you lose it all if someone takes it all and uploads it, is your business in trouble or not? um that's the that's the question I think everyone should be asking. Now to to the broader question um you know of of how does this affect the entire industry? generic tools that do not have proprietary pieces of the story are going to be very very hard. First mover manage isn't going to be a thing. um it's always gonna be a challenge. So how do you go and and and build a thing that is uniquely yours? um I don't know of how to do that unless you are be building the foundational models, right? like you are the open AI and everyone's building top of you or you've got something that truly changes all the time and is only available to you and it's critical to people's business workflows. Um I don't know how else you survive. It's a it's a you know I go to a lot of these AI conferences and I see a lot of people like building AI on top of their product but I really think there's a day not in the I mean replet is almost there where you can just describe the thing and it's going to build as good as the thing that you have as long as you've got a good product manager with a good set of ideas um that tech is is not that far away and you just fast forward five years it's going to do it's going to suggest things to do to beat the competition right it's it's going to code it for you and build the features. So all of that becomes um commoditized essentially. So there is now it's just like companies are going to go back to building their own internal tools because they're customs bespoke for what they need rather than trying to fit into someone else's uh package. So in those scenarios, you've got to bring some other value other than that into the equation. And that's why uh being a being a data data company that has some stuff that no one else has feels pretty good for that long-term vision. But I'm biased. Yeah. You also mentioned that uh that Crunchbase has an API as well. So I mean that that API can sort of work into your own sort of proprietary stuff. I'm sure there will be people out there that figure out some like really good prompts and really good data points to look at to sort of make their own predictions and then not want to share them with the world because you know that that's their sort of little secret sauce that they figured out you know. Yeah. Almost every major VC now has our own data science team. um and and we have conversations with them and saying, "Hey, how would that API feel feed into your team? We don't want to replace that team. We're just going to supplement them." It's really exciting to sort of see the innovation and um like seeing how people incorporate our data into their own tools to make them successful. Another angle we're thinking about is how do we take what's happening in public markets and interlock it with private market data. So for instance, if you know a certain set of companies uh let's say biotech companies are suddenly their stock market is tanking and they're doing really poorly, how does that affect the VC market? How does that affect our predictions? Right? like there's these external influences and then can we report on that and say look based on what we're seeing in these sort of external sort of public markets we think we predict there's a cooling happening on this side of the house and that and those dollars are going to get redirected to you know whatever whatever the other hot trend is at the time like we can start making more of a commentary on what's happening in the world um than just leave it to um others to to interpret. I do think you know out of the use cases you mentioned like for me uh the sales one is super interesting like like if I could talk with AI and like okay I've got a marketing agency and maybe uh you know you could even get really detailed like I went to Stanford maybe like look up startups that they went to Stanford so I can like bond over that like if you could get like really detailed like that right and then reach out like hey we both went to Stanford we both went wherever uh and then start conversation I think that could be like super powerful for a lot of people. yet that sort of that we're trying to change the definition of what an ICP is, right? Because because they're they're look here's exactly why I always sell too successfully and maybe it is I and we also went to school together. Those are still historical facts. So the thing we're trying to change in people's minds are is um is it the right time for you to talk to? Cool. Here's this list of companies. Which is the right one to talk to right now um for this particular accounting executive. Right? So this accounting executive historically has been great at selling these sorts of deals. here's companies that match the the kind of companies that they would successfully sell to, but here's ones that we are predicting are going to grow growing quickly. They're probably fundraising in the next 18 months. They're not going public and they're not getting acquired because that would distract the sales cycle. So, you can kind of like sort of tee up this is the right time for this this ICP is the one you want to talk to right now. Yeah, that's that's worth a lot. Hope so. We'll find out. Now, can you use Crunchb to to sort of discover emerging markets as a whole? Like obviously you can look at in a specific market and find the the the companies that are sort of uh you know making moves in those industries. But can you find like you know you mentioned biotech and you know had had you known like what AI was going to do over the last you know six or seven years if like is there are there any ways to sort of see that stuff coming a little bit sooner? Yeah, it's it is one of the um one of the the harder to find features in Crunch Base, honestly. So, so it's really possible to do. Um there's things called hubs and not many people know what even the hub is, but we basically took every major piece of metadata that has uh data. So, for instance, like industries. So, we have every industry. Um, that's one access. GEO is another access. um you know there's gender, there's u a founder, uh there's stage of company, how much they raised and we basically intermix that. So we made these pages. So somewhere on Crespace there is a um sort of female founder in crypto uh in Europe. There's a page for that and we originally did it just for SEO reasons. Um, but what that also did is it collects all the data. So it's like here are all the latest funding rounds, here are all the people, here are the companies. Um, and they're all ranked by which ones are trending the most in Crunchbace. Um, so you take that um, and then you say, well, if so every single thing in Crunch Base has a rank. So hubs have ranks. So which is the hottest one right now today based on what's happening in Crunchb's first, second, third, fourth, all the way down for every single combination of the I don't even know 10 uh 100 thousand of these different hub pages that we've created. Then you can go and say, well, which ones are trending? Um, so if you start looking at which ones are trending, um, and which ones had the low rank that are trending upwards quickly, that's where you get to see which of those combinations is the hottest. So you'll find some really just fascinating things lurking in there. Some of it's going to be weird, you know, but um like I'm just I'm just playing around with it right now, but like like Taiwan artificial intelligence companies are like a hot thing right now, you know, like like very I love that. I used to live in Taiwan. That's great. Okay. Yeah. Uh so there's so there's these little pieces of that you wouldn't normally otherwise know and I think if you were a savvy investor who was really um trying to figure out what is an emerging trend um or even just again an analyst or even a journalist who al they also use crash base you can find some interesting things lurking in hub pages I think just it's it's a a sleeper feature that we have very cool well this has been an absolutely fascinating conversation like I you know I I don't want to be like a saleserson for you but I'm actually a subscriber of Crunch Base. I actually do have a subscription and I get in there and I play around with the data from time to time. But no, this this has been a great conversation and I really appreciate you taking the time to hang out and give us the demo and everything like that. Um, you know, obviously Crunchb is is the place to go. Crunchbass.com if anybody listening wants to go check it out. Um, is there anything else that they they should know? Any other, you know, places they can maybe follow along with you? Anything like that that you want to shout out before we wrap it up? Uh, yeah. I mean, follow follow Crunch Base on LinkedIn. I think that's probably our our our top channel of sort of sharing stuff out. Um and uh you can follow me on LinkedIn as well because I I usually leak road mapap stuff. So if you want to see what's coming uh before it does my product team hat but I usually will post stuff about what's coming soon. Awesome Jagger. This has been this has been great. Thank you so much for uh hanging out with us today. And uh for anybody listening, if you like content like this, make sure you like this video and subscribe wherever you listen to podcasts. And thank you so much for tuning in. Hopefully we'll see you in the next one. [Music]