He worked out of a police department for free for a year—then built a $6.8B company. | with Ben Rudolph, Co-Founder of Peregrine

0:00We're interested in learning more about how you solve these cases. Could you take us along as a partner? We'd love to learn more. And he said yes. He invited us to the police department. He gave us a bunch of background checks, basically handed us this book. And he's like, all right, let's see what you can do. And we got to work and basically worked out of that department every day for 18 months. I always tell founders kind of the same thing as go sit with your customer. Prove value. That is the thing. If you're in an apartment or things like that, get out of that apartment, go to the customer, try and find a situation where you can build alongside the customer.

0:34That's product market fit. Product market fit. Product market fit. I called it the product market fit question. Product market fit. Product market fit. Product market fit. Product market fit. I mean, the name of the show is product market fit. Do you think the Product Market Fit Show has Product Market Fit? Because if you do, then there's something you just have to do. You have to take out your phone. You have to leave the show five stars. It lets us reach more founders and it lets us get better guests. Thank you. Ben, welcome to the show, man. Thank you, Pablo. Happy to be here. So you started Peregrine like just over eight years ago.

1:08You just raised a$250 million round at a$6.8 billion valuation. So clearly things are working. And I would say in your case, more than that, you know, every founder, at least that I mean, you know, typically they want to like add value, change the world, however you want to like, you know, make that sound bigger. But in your case, the impact you're having is very clear. I mean, you're helping law enforcement solve crimes. You're helping fight wildfires. Like these are pretty meaningful things. So we're going to get into all that, like what Peregrine is, what it does. But, you know, we start always because this is ultimately about product market fit and how you found product market fit.

1:42So let's start with that. Like, what is the moment for you when you felt like things were really working, when you felt like, okay, we have product market fit or something like it, at least? Yeah. So the story of Peregrine is long. And, you know, we got started by embedding in the back of a police department. We were working with detectives, solving homicide cases, sexual assault cases, armed robberies, these types of things going in day in, day out. We were there for 12 to 18 months and building product, working on these cases. and the moment where I really started to feel like, okay, we're actually building a product that is adding value and being useful is there was this complex homicide that they had been working on for a few years.

2:20It was gang involved. There were lots of burner phones, rental cars, and a couple of people ended up getting killed. And they had called us to basically ask for help on finding the next lead on this case and seeing if we could help solve this. And that was when I was like, okay, we're at least providing something that they're thinking of us to solve this case. And that case actually moved forward to the point where we were expert witnesses in the trial that ended up solving that particular case. But your product helped solve that case? Yeah, that's right. That's pretty wild. What is your product?

2:57Like, what does your product do? Because again, the fact that you're solving cases, you're also doing wildfires, you touch a lot of different pieces. So what does your product actually do? How did you help solve that case, for example? Yeah. What we saw when we came to that police department is there's been a proliferation of technology point solutions for all sorts of different types of data collection methodologies. And they weren't able to actually leverage that information to achieve their goals. And in this case with the detectives, they were trying to solve cases. So our technology basically put all this data into one current complete asset.

3:31They were able to join other data sets together. When someone commits a crime, you're able to basically request information on that particular time portion, get cellular data. Peregrine's platform puts all that data into a current complete data asset, transforms it, enriches it, and then provides applications on top of it to enable users to explore and find insight from that information. However, I'd really say that I think of Peregrine's product as 50 % of its technology. It's that platform that allows you to get insight, build workflows, and do that type of technological work. The other 50 % of our product is really the way we deploy and the way we partner and work with our customers.

4:12And I think that symbiosis is what made Peregrine successful in the early days and something that we've tried to hold on to. Maybe to bring it all together, like give me, you know, you go to that example where you solve that cold case where you help solve it. Like as a result of your technology and the service layer that, you know, and the partnership and everything, what happens? Like what are you able to uncover? I don't know if you can talk about that specific example, but that would be ideal. But, you know, what can you specifically uncover that maybe before was just, you know, not possible to figure out?

4:40Oftentimes when you're trying to solve a case, you're trying to tie a person to a location at a time and place. And in this particular case, they were able to marry a bunch of different cellular records. Like, it's hard to oversee how complex and varied this information is. Think dozens and dozens of Excel files, different time zones, messy data. Being able to check that all together, visualize it, understand where different phone numbers, different people are in relation to like geospatially and from like a temporal perspective. And marrying that together and understanding, OK, who is here at this point in time?

5:13Who is here at that point in time? and just having that information and understanding the way the movements of the people involved in the crime is critical to actually moving the case forward. Many times I'd say when I talk to founders of companies like this that are very technical and hyper-focused, for example, I talk to somebody in cybersecurity and they're like, yeah, I used to be in the armed forces or I used to be a hacker for, you know, idea of like things like that. I'm looking at your profile, I'm trying to make sense of it. Like, how do you end up here? How do you end up in this company?

5:40So my background, I went to Stanford's Tech Like pure science, I spent every summer working at different Silicon Valley companies. And I really took away from that experience that I wanted to build technology that had meaningful impact on communities around us. And I spent a lot of time working at town companies where I didn't really believe that that was true. And so after school, I went and worked at the UN Refugee Agency, spent a bunch of time deploying technology in very hard to reach places, solving issues that are similar to the issues that I solve today, which was the UN refugee agency has extremely disparate data and it's very difficult to understand how different interventions are working on different refugee populations.

6:22I then did a similar kind of, I joined a similar type of company that was deploying technology in hard to reach places, doing data collection in Africa and India, partnering with governments to have interventions on one, for example, we worked with, the Indian government on ensuring adherence to TB drugs. And both these experiences, I took away a couple of things from it, but one, it's really difficult and challenging to work with the government. It's slow, it's bureaucratic. I was going to say, it's not the obvious place that you then like launchpad for entrepreneurship. Totally. But if you're able to do it and if you're able to partner and you're able to do it well, I think the impact there is real.

7:02And I saw that. And so what gets me really excited about Peregrine generally is we found this way to partner with our cities, our states, our counties, our federal government to build technology, best in class technology to the public servants, the folks who often get the worst technology and give them really great technology to do their jobs better. And so that is the frame of mind that I've had. We got started in law enforcement. We're building a much bigger platform and much bigger technology than that focused area. Tell me more about the origin story. How do you go from building and selling software to government as part of another company to deciding to start your own thing and specifically Peregrine?

7:43Yeah, actually, a lot of it goes back to my co-founder. We did gymnastics together in college, spent a lot of time, 20, 25 hours a week. Someone who I felt was a really great partner. We always wanted to start a business together. We had talked about it in college. He had gone and spent time at Volunteer. We were on what I'd call maybe dual tracks where he was working with different types of government institutions and deploying software in very hard-to-reach places. And I remember in 2017, we kind of linked up with a very similar perspective on how we could partner with these kinds of important institutions to deliver better outcomes.

8:24And that's really when we linked up. I moved across the country to come to San Francisco and really got started kind of in the back of my apartment in 2017. So was that born out of what you were doing? Because the idea is very generic at that point, right? It's like, let's take data together and help law enforcement. Was that kind of the first version of the idea? It was definitely the first version. I think we came to the problem with a very open mind and from first principles. When we went to partner with the first agency we worked with, the San Pablo Calides Department, We didn't have a prescriptive solution.

8:56We had an objective, which was to help these detectives solve the cases that they were working on. And then we worked backward from there. But you somehow knew that it was a problem. Like, obviously, everybody wants to solve more cases, but you knew that they were probably not making the most of the data that was available to them for reasons that you saw, like, at the UN and et cetera? It was actually just because, like, when you go to solve a case, you get a bunch of data that you have to sift through and sort through. And we're like, wow, this is really hard. and it was there where we're like, okay, we need to build something to actually process this information.

9:27And then we started tying it to some of their record management systems that they already had and kind of connecting those dots. And those are like the very initial steps when you're trying to solve a case. Obviously, there's some piece of this where we came from a background where data integration was a very important problem and something that was like front and center for us. But it was also very much a first principles, like how do we solve this problem for the customer? You know, you want to have impact. So I get that that's kind of in the back of your mind. but what pulled you towards law enforcement in the first place?

9:54I think public safety is an incredibly important problem. I spent a lot of time in countries that had no functioning public safety system. And I personally believe that doing public safety correctly and right is a very, very challenging and hard problem. And I was motivated to work on that problem and kind of dig deep on it. So both of you guys just kind of, you just cared about public safety, you just decided, let's talk to some people, see what's happening in that world, to see what problems we could solve. When we initially set out to find a partner, we were knocking on doors. We actually researched a ton of different folks in the Bay Area, different captains, different leaders who might be open to this type of partnership.

10:36And our methodology here was really, we looked at essentially the org chart of these police departments. Who are the number two, number three in charge? They were maybe a little bit younger. They were leaned into technology, isolated that list. We did a bunch of research on these folks, what kind of cases do they work in the past? And then we left very thoughtful messages. We reached out to them and we were persistent in that. Where were you asking them specifically at that point? You know, at that point, it was less of a question and it was more of a, hey, can we have a conversation? I would love to learn more about how you do your work.

11:11And so in our specific example where we in San Pablo, where we, there was a commander at the time, Commander Brian Bubar, who responded to our reach out. And we were essentially like, hey, we are really interested in this case that you solve. We were interested in learning more about how you solve these cases. Could you take us along as a partner? We'd love to learn more. And he said yes. He invited us to the police department. He gave us a bunch of background checks and basically handed us this book. And he's like, all right, let's see what you can do. And we got to work and basically worked out of that department every day for 18 months.

11:46So you went to them and just kind of said, like, I guess I'm just not understanding if it was a pure discovery, like, hey, we just want to learn through the space. Like, you know, you're an expert, whatever. Or whether you came at it as saying, you know, we want to work on something here. This is like the idea we want to do. Can we do it with you? Like, which of the two messages are you going out with to all these initial kind of commanders? We never came to them with like, here's a technology that we want to build for you. It was always, we want to help you solve cases. and we especially want to work with your detectives to do that.

12:19And that was the ethos and mentality that we had. I think, especially in the early days, like a lot of these government agencies have a ton of vendors who are like, hey, here's this technology. You want to use it? And it just doesn't land well. Why would they let you in? You know, like you can't just, like, yo, I want to help you solve a case. Like if you have a product or you're like, hey, I just want to have a chat. I get both of those, but like, I don't have a product and I don't want to have a chat. I just want to help you solve cases. that are like, yeah, come in. Like, here you go. Solve my case.

12:48How does that happen? Yeah, yeah. I mean, he definitely took a chance on us. We were very open and transparent with him in that we want to build a company. We were, you know, looking for folks to learn from and wanted to be kind of design partners with. And he was open to that. And so we tried a lot of people before we got like a yes here. So it's definitely challenging. Did you do a lot of the customer discovery before this, before like jumping in and starting to try to work with this person to help them solve a case? Like how much did you already know going into it in terms of what the world was like?

13:21Yeah, I mean, we did as much as we could, right? Like we read all these cases that he had worked personally. We learned about like law enforcement structure, police department, how they work, how they operate, how do warrants work, these types of things. But you really, in order to make that jump to being an expert, you have to work it. And so that was our approach. And so then what happens? And so he lets you in. What do you start doing at that point? Yeah, he gave us a room in the department. And anytime there was a case, they would essentially treat us as crime analysts. And they'd be like, hey, we got a new homicide in.

13:55Here's what we know about the case. Can you help us with it? And we would be like, sure. And then so we would sit there all day, poring over these files, trying to figure out what happened, pinpoint a phone number. Just like manually, like you're basically free labor for these guys or are you building tech to do this? Definitely free labor at the beginning. I mean, I'm a programmer, so I was writing software to do this. So that was definitely helpful. But this is a job, right? This is what they would do. They would like sift through this many times very manually. So step one really was finding somebody to let you do the job for free, just so you could learn the intricacies, the subtleties of what the job was.

14:30Yeah. It reminds me of, you know, I had a company on here a while ago, a company called Ada. And the way that they built the product, which was like, you know, a chatbot, again, like we're talking 2015, but it was by working as customer service agents, like literally doing the work, responding and getting hired by like seven different companies, and then just learning the job that way and starting to build tools to automate themselves out of that job. And that was, you know, ultimately it was that product. Is that similar to what you guys did? Yeah, exactly. That's, that's exactly the way I would frame it as it was the purest form of method acting.

15:03Tell me a little bit more about, cause this is the key, right? Like if you want to automate something or help transform, let's say, an industry or whatever, you do need somebody to let you in. Like you need somebody to give you all that exposure. And especially law enforcement, like it's not trivial, I don't think for somebody to do this. I mean, you mentioned a lot of people said no. Why did this person say yes? I mean, I'm just thinking about like two people with no necessary law enforcement background. They don't have a product. I'm going to let them in. I'm going to give them background checks.

15:31I'm going to give them all sensitive potential information. I guess worst case, they don't help me. Best case, they do, but it's kind of like, anyways, what's the driver there? I think about that question a lot. I'm not sure I have a satisfying answer for you as to exactly why this person said yes. But I do think the way we crafted our message, the way we wanted to be, we had a service orientation approach. And I think that resonated with this person who is very technologically forward. And we told him, we were computer scientists and we wanted to learn the space and build and deliver great technology for him.

16:06They probably believed already that with tech, they could do a lot more. There's just so many gaps. And then just like, I don't have a budget, I don't have the time. And all of a sudden you two walk in and they're like, okay, I could see this makes sense. Like something like that, which is kind of why I have to go through so many because you need one that actually is already almost all the way there. Like, is that ring true? A hundred percent. And I also think there is like an aspect to, great, I got two free crime analysts who know how to write software and work with Excel really well. That's great.

16:34Right. So you're working with these people that are starting their handy cases and you're learning on the job. What happens next? We had that case. That led to that kind of expert witness experience. And we raised our first initial seed capital after that. And we got our first two or three person office. And we grew really slowly for the first, I'd say, probably three or four years. Word of mouth, our very next customer was the city next door. And it was because the chief talked to that chief and was like, hey, these guys are actually doing a lot of good work for us. And that word of mouth growth is how we built the product and deeply empathize with the problem space and had the opportunity to go that extra mile.

17:21I mean, we learned so much during that time. One of our first customers was Albuquerque. And I remember I was on site one time and I was doing a case with one of the detectives and there is this technology called ShotSpotter that detects gunshots. And I was pulling up these gunshots at time of the crime and I was like, oh my God, there's so many guns firing. Like, was there like a mini war? Like, what's happening? And the guy's like, no, no, this is, so there was a homicide, gun goes off. But there is this like tradition or something that happens in Albuquerque where at the end of night, at the end of a party, someone takes out their gun and shoots it in the air.

17:59Everyone else takes out their gun and shoots it in the air. So this homicide happened, gunshot goes off. People think it's related to a party happening next door. Everyone shoots. And so you look at the map and you're like, everyone's shooting their gun. What's going on? And so you learn these like little bits of context on how they do their job. And that coupled with us constantly iterating the product to make sure that we could like meet their needs. How big was the seed round that you raised back then? Yeah, back then we raised, it was either one or two million dollars okay so one or two million and this was like what's the time like when do you guys start and then when when does the seed round happen the seed round was nine or ten months after we started the the company yeah it's funny like comparing it to the stuff you see today like this is like and and then you end up where you end up which is obviously like hugely successful but like it's good to remember like what i would always call that reality right like i don't know that this can stay forever but you know nine months to raise million dollars today is like, oh my God, you should be raising, you know, like 10 and you should be growing like crazy.

18:57But, but, you know, this is how you, you know, ultimately end up with, with the real business is worth billions of dollars. Like most of the businesses that end up even at this stage, which is still like the less than way less than 1%, you know, have a starting story that looks more like this than, than the highlights they see on TechCrunch today. You know, I really believe that to build big businesses, you got to stack bricks and there are very few shortcuts in life. And I think the things that we've done that have taken a long long time, those are our moats. And those are durable. And so, you know, I don't know these businesses well, but if you can get 500 million in revenue in six months, you'll probably lose 500 million in revenue in six months.

19:34It's just like, it's unclear to me what the moat is when you go super, super quickly. And so I think there's a lot of durability in being able to build your business methodically. We were going to talk about a couple of like tactical areas that we can kind of go deep on. I want to talk about one of those now because I think it's it's related and going to be kind of part of the story of getting to PMF. You were big on forward deployed engineers a long time ago. I mean, now it's like the cool thing to do. Everybody does it, right? Back then used to be called services and it was like, you should not do that.

20:03You want product, you want high margins, all these sort of things. But I mean, you were to the point that if I remember correctly, like when you were small, 10, 15 people, maybe half your team might get deployed for a month on a single customer. Let's walk through that. Like, tell me, you know, how you did it, why you did it, and like how big was the services element? How do you still, obviously you ended up scaling. So I'm trying to understand all that, but let's start at the beginning. Just what was the idea around forward deployed engineers? How did you set it up? I think the overarching principle for us in the early days and still today really is over-investing for success.

20:36And Peregrine started with deep roots in product development and implementation. And that's what we really wanted to be good at. And we weren't so good at marketing and we weren't so good at these other functions. But those are two things where we're going to put all our points into this. And we really believe in those early days that over-investing in ensuring the customer is successful would pay massive dividends. And I think that was also especially the case in government where it's such a high trust network. I mentioned that we got our second customer because the chief just told the other chief that these guys were good and trustworthy.

21:11That dynamic is very, very real. And so, you know, we weren't really thinking too deeply about how do we build an infinitely scalable business. We were thinking about how do we make our customer really successful. And so even in those early days, I remember one of our first engineering hires, we sent him to our second customer in Pittsburgh, where he basically worked out of that office for about three weeks integrating their data. They had this like luau and he cooked a key lime pie and he just completely got embedded with that department, understood their lingo and was able to deliver a much better integration product for them because he understood the difference between different values in their database and could actually map all the disparate data to how they actually talk and spoke within their department.

21:59We have tens of thousands of people who have followed the show. Are you one of those people? You want to be a part of the group. You want to be a part of those tens of thousands of followers. So hit the follow button. The concern, right, always with this stuff. And again, like now maybe it's less of a concern just because everybody's doing it, but it hasn't fundamentally changed the equation, which is how much can you really do for one customer before you mentioned you didn't really care about scalability, but that's still on a lot of investors. And I think a lot of founders minds are like they don't want to get stuck being this consultancy-like thing.

22:30Obviously, in your case, you were able to scale it. Maybe just tell me more about, is there a middle ground? Is there a balance? Is it just a matter of at first it takes a long time, but later on you have a playbook and it's faster? Or is it still really custom? How do you manage that trade-off between wanting to give your customer the best possible experience, which means hand-holding, means going in, embedding, etc., but also wanting to be able to add a lot of customers, add a lot of ARR fast, which means holding those resources back to work on core product. So I actually remember this moment where I told Nick, my co-founder, all our engineers are integrating data right now.

23:04We can't build any product like we need we need some other strategy. And, you know, I think in those moments, we are city breeds innovation. And we started building this other platform that allowed people who weren't engineers to integrate data. And that was our first shift to, oh, okay, if engineers don't need to integrate data, that saves a ton of time. And so we started building out this other function within Peregrine. Deployment strategy is what we called it. And they were, you think of, maybe studied computer science, went to McKinsey for a couple years, wanted to work in technology. And then they could integrate a bunch of data, work with the customer, partner with them to do that last mile configuration.

23:47configuration. And I think we've always thought about that investment as a growth driver, not as something that needs to be optimized away. And of course, as you grow fast, you need to invent and you need to innovate in order to save time and free up resources. That's something we're like continuing to do and we always do. But I think our frame of mind on it is just like maybe a little bit different. One of the challenges I would say with selling into municipalities, law enforcement, like these non like you've got b2b which is the obvious the classic and then you got b2c and then you got business to something else government whatever like these non ro like it's not consumer where it's like you know the sort of things they care about just like entertainment and whatever yep and you got businesses care about making money roi right and then you got these in the middle where it's like depending on the situation depending on the politics depending on whatever they have different priorities and a lot of times at least from a startup perspective it's always like a bit of a hard mode situation because you're like, it's hard to scale, it's slow, et cetera, et cetera.

24:47What do you think has worked in your case? You're deep into it. This is like the perspective of somebody that's outside, the thing that gets said, right? You're actually in there. What are some of the pros and cons of selling into these types of buyers and what helps you crack it in the way that you have, right? And be able to actually build a scalable business. Yeah. And I think some of this is very much hard lessons learned over time. The go-to-market motion for Peregrine was a very hard one. I'd say it was one of the hardest challenges that we had to overcome in the business. We had this phase of the company where I'd say we were in the wilderness trying to find that product market fit.

25:23We had that product market fit. We were trying to expand more. And then getting that scale, that go-to-market scale was really, really hard. And that took a lot of learning and understanding on how government processes work. It took a lot of learning and understanding on building the pipeline. I think there are little tricks in every single state and county that you have to learn. It's hard to enumerate every single one. What did you learn? Ultimately, what was the go-to-market that started to actually work for you guys? Yeah, the go-to-market that actually started to work for us was, one, simplifying down the message what we were trying to sell.

26:01I think Peregrine is a complex piece of technology. It could be hard for maybe a person not familiar with technology to explain that value prop. So it's really important for us to make the value prop of Peregrine very clear and have our champions kind of go to bat for us. And the way we got scale is by hiring account executives across the country and teaching them. And it was card carrying, knocking on doors, and doing this at scale. and building the pipeline, going through the nine to 12 months sales cycle and doing that enough times over and over and over again. And these things get easier as you do more of it because as we've generated penetration within certain areas, the next customer is that much easier.

26:47That state is more familiar with you. That city is more familiar with you. And so they have like a snowball effect. But how fast did things ramp? Like how fast did you get to like a million and then 10 million, for example, in AR? Yeah, we went basically 1, 3, 10. Yeah, I mean, that's the kind of classic, used to be the classic, right? Triple, triple, triple, double, double. Now it's like 1 to 100 in a year. It took a lot. It took a lot. And there was not an easy button. Well, that was going to be my question, right? It's like, did it ever, easy is the wrong word because nothing's ever easy. Like, you know, even the startups are high flying, like revenues, it's not easy.

27:21Like, I'm sure if you go and talk to somebody at Anthropic, like it's not easy even though all the revenue is coming in. So easy is the wrong word. but when did it go from like a push to a pull? Where did it go from where like, at least the growth, the top line was not like the number one, most principal worry was other things. And was there ever, like, did that ever kind of start a shift or was it always like, okay, how are we going to make it this quarter? How are we going to make it this quarter? Like, was that just the real life? Look, I think the reality is Peregrine's goals are always very ambitious.

27:47And so it's always top of mind. How do we expand? How do we build? And how do we grow? And like what we did last year, by definition, we have to do something new and different and we have to either build the fleet out while we have to train the regional sales manager to train the account executives underneath it. Now I will say we're at a point where we have an engine in the state and local space. It can always be better. We always want to grow faster. We're now expanding to different types of verticals. That takes a whole different type of learning. Our whole idea of payroll is like deeply understand a vertical so that you can be successful in it.

28:21And then when we are expanding to emergency operations or expanding to health and human services, we also have to go and do the hard work of learning that vertical and learning the way we go to market because it's different. It's very difficult to just kind of copy and paste. Of course, you can take some of those learnings, but you got to do learning. But it's always been like the challenge has always been like you've never been in a position, just to be clear, where it's like, wow, we have so much pipeline, whether it's Alba or Alba Generate, we have so many contracts closing. Like, how are we even going to deliver on this?

28:50Right. Which is typically like the classic, quote unquote, product market fit that you read about or whatever that market trees would talk about. Like, was that ever the situation? Was it always like, OK, how OK, we're going to triple again. Therefore, and you do like most most startups that I see, at least like they live in that. frankly whether they say they have a problem or not they live in that world where it's like okay shit how are we going to make this score how are we going to make next score and like well if we do this and we do that maybe we'll make ah we're off by 20 and then like the one in 10 are the ones where it's like yeah i'm not worried about making this score i'm worried i'm worried about maybe retention i'm worried maybe about like hiring i'm worried about you know raising money because whatever like i'm worried about all the other things but not growth so i'm curious obviously the beginning it's never like that but did that ever happen yes i specifically remember is the the next bottleneck for Peregrine was that deployment motion that you talked about.

29:37Like, how did you scale that? When we started getting, you know, not like single digit customers, but dozens and dozens. And then it was like, oh man, how does this even work at scale? And I think that was a big moment for us. I would say like the year of 2023 is - You're now in the tens of millions, right? At that point? Uh-huh. Could you point to something? There's probably, there's probably no good answer to this question. I'll ask it anyways. Like what took you from more of a push? hey, we're doing numbers, we're doing great, one, three, 10, that's awesome, to like, wow, we're growing so fast, I got these other problems.

30:07And I'm asking it, you know, just for more content, like that to me is that, you know, we talked earlier about the power market fit moment, which is really like a value delivery moment, right? The first time it was in action, you solved the cold case, like, okay, this thing works. That's not necessarily the same as there is so much demand for this. Like I'm drowning in demand, which is kind of what you're talking about in the 2020s. And I'm curious if that's just a matter of, well, at some point you sell enough, people know you, you know, like you said, commanders to all the commanders, captains and word of mouth takes you there, or if something changed either in your product or the market that all of a sudden demand just kind of took a step change.

30:42That demand, it's a mix of all of those. And the moment that I really felt that we needed to check is we had, you know, we were operating off of a spreadsheet for resourcing on how, who goes where. And like, we just had this big list of customers and we had this small list of deployment folks and they were all tied up in like current customers. And we feel very strongly that like, as soon as the contract is signed, we got to start work on this. We got to start integrating data. We got to start providing the value. And we were taking engineers off the line and doing core product work to be able to do these like far deployed motions.

31:16And that is when we were really testing the scale of how we could develop that playbook to make it more efficient, how we could hire very rapidly to be able to meet the demand. And is that also when, just looking at your fundraiser history, Like, would you say that that was also when fundraising really took off? Like now you're raising massive rounds and I'm sure it's not, it's like probably not hard for you to raise. I mean, you want to optimize and all these sorts of things, but I'm sure you got more demand than supply in terms of, in terms of fundraising. And that obviously wasn't the case when you're raising a million dollars.

31:43Like, was this around the time when that changed as well? Like, is that correlated? Yeah, absolutely. I think whenever you can show that kind of snowball of growth year over year, month over month, quarter over quarter, at a certain point, the business is started to be judged on, on its metrics. and when you can show those, that's when it becomes. Yeah, and it's also when you can go to somebody and say, listen, like, I need money because I got so many deployments coming. I don't need enough engineers to fulfill those deployments. Like, okay, cool. Here you go. How much do you need, right? Like that is a low risk proposition and that's the beauty of, that's what product market fit does to you if and when you can truly get it.

32:19Yes. Yeah, absolutely. So let's do the, we did one of the tackle areas, right? We went on kind of the FDE side and why you did that and how that worked. The other thing that you did that was very different when you were talking before was the amount of research. People talk about you're going to do enterprise sales. You have to research and whatever, but there are gradients into just how far you can take that. And you went to the point where I think it was for that first deployment. You looked at every single captain across the entire Bay Area. You saw all the records, all the cases they handled.

32:53Tell me a little bit about your research-driven enterprise sales motion. Yeah, I think this goes back to our mentality of over-investing for success. And even when you say that, the moment that comes up for me is, it was Christmas 2020, something like that, where everybody was still home for Christmas. And we had this RFP opportunity. And it was one of these situations where it wasn't written for us. We didn't write it. And those are always like high-risk opportunities to begin with. But we like read it. We thought it was great. Yeah, because you assume they wrote it for someone else. So you're already in the backseat.

33:30Exactly. And it was shown to us from somebody who was like, hey, I think this is a good fit for you. But it was working with an agency in the state of California. And they had these four scenarios that we had to demonstrate. And this was for emergency operations, doing wildfire, rescue mission, things like this. And we basically sprinted for three weeks to get our platform to a place where it could show these different demos. One of these demos, and Lake Berryessa is a lake up in Northern California that I have memorized by heart because one of the demos was to show how you could build a path of travel through Lake Berryessa if these roads were closed off due to wildfire.

34:11Very, very detailed. And we spent so much time preparing for this RFP. And it was a basically like four-stage process. we transformed our entire office into an emergency operations center so when they like called in we have these cameras that like mimic the same emergency operations center that they had in California and then like demoed exactly you know all these scenarios and really went I would say like 120 % on the effort there and we won that contract probably shouldn't have won that contract I'm sure it was written for some other billion dollar company you know that has been a lot of our strategy for Now that's different to be clear than the research piece, but this is kind of the amount of prep that you put into every engagement?

34:56Yeah, it's different in like the tactic. Same in the principle of, you know, if we expect to win these kinds of, especially in areas that were unproven, like the word that I think we always talk about and think about is earn. And we have to earn the right to be able to work with these folks. So walk me through it, right? Because the whole point of this is like somebody needs to be able to copy it, right? So you want to go and you want to win a certain organization. What do you do? Like, what are the sort of things that you're doing to do that 120 % to earn it? What would you do, right? Like, imagine me, I'm a founder.

35:29I'm like, dude, like, I think they would be a great customer, like, you know, because XYZ reason, I want to go sell to them. What are the sort of things you would do? I mean, we've been in a lot of situations where for an organization that we haven't worked for, we did a bunch of research on what their priorities are, listen to their speeches. We would get as close as possible to kind of open source data that they might have that looks like their data potentially. We would integrate that, put together a whole demo that solves and speaks to like an exact problem that we know that they have talked about.

36:00and showing up for a first meeting where you can demo and speak to somebody about like pretty much their own data and own problems is really powerful. And we use that technique and often when we're trying to like go work in a place that we don't know as well. I think the other example that we get to dive into is how you source the first captain that you mentioned. Like what sort of work did you do at the beginning? Yeah, and that similar approach was, you know, this is just research work. And we spent, you know, we were in San Francisco So we isolated kind of the cities in the East Bay that we thought were interesting that would probably have a higher level of crime.

36:37So we kind of had a whole map of where we thought that the ideal city was. Then we kind of decomped who was working at these different police departments. Where were they on the stack? What had they done previously? And so we had profiles of all these different police captains, commanders, lieutenants, and started tailoring very custom and purposeful messages for each of these folks. And your hit rate's still low, especially when you don't have a product or any, you're just kind of like two guys. But I assume even when you get that first meeting, you already are coming in with a lot more information.

37:14Like, you know, whether that's building rapport or whether that's going in and not wasting any time and getting right to the crux of it because you know. and then that shows preparation from their side as well? Yeah, the commander who ultimately said yes, we knew the exact case that he worked on. It was Operation Redreach and we knew the details of it and could talk to him about it and we're asking questions about that specific case. And I think, you know, if you like invert that, you don't often get that feeling when you're talking to somebody for the first time and they're trying to quote unquote pitch you on something.

37:45I think, you know, I remember talking to another founder who said one of the challenges when you're doing enterprise sales is you have no credibility. Like when you are selling into a large enterprise, you're competing with other probably established vendors who have a lot of credibility just because they've been there before, they've sold other products. So they walk in with credibility. You might think the sale is 100 % about ROI. That's obviously part of it. But if you have no credibility to deliver that ROI, you're not getting the sale. And things like this are a way for you to show credibility.

38:20It's like, okay, you don't have a brand, you don't have a product, but holy shit, you walked in with a lot of like research, a lot of preparation. The first impression is this person's probably credible, probably reliable. And you're still gonna have to, by the way, play the numbers game, like you said, because most people are gonna say no no matter what. But it increases the odds just enough that at least one person will be like, you know what? I'm gonna take a bet. I'm gonna risk because it's a risk for this person, you know, from their own credibility, frankly, their own social capital. I'm gonna take a risk on you because you've shown like just a little bit of credibility for me to kind of take that next step.

38:49Now it's easy. Now you're Peregrine. Now you've got funding. You've got all these sort of things. But back then you have to find ways as a founder to show these enterprise guys, especially on the enterprise side, that you have some credibility. Absolutely. Yeah, credibility, trust. These are big, really important things to win that first deal. And I think people don't, especially if you're coming from tech and you've been an engineer or something like that, when you purchase a big technology purchase for an organization, if you do that well and you do that right, that can move you up the ladder.

39:18That is a very important piece of your job. And so it is taking a big risk if they go purchase some piece of software that is not useful or helpful. And the reverse is true too. They can climb the ladder based on the smart purchasing and technology they've made. Perfect. Well, Ben, let me stop it there and I'll ask the question we tend to end on, which is what would be a top piece of advice that you'd give a founder that's also in this kind of like early stage, you know, looking for product market fit? Yeah, I always tell founders kind of the same thing as go sit with your customer. Prove value, that is the thing.

39:54And if you're in an apartment or things like that, get out of that apartment, go to the customer, try and find a situation where you can build alongside the customer. Perfect, Ben. Thanks so much for jumping on the show, man. It's been great. All right, Pablo, thank you. So picture this, it's months from now, years from now, and one of your founder friends, a really close founder friends of yours, guess what? Their startup went bankrupt. And it turns out if you had just shared the product market fit show with them, they would have learned everything they needed to, to find product market fit and to create a huge success.

40:26But instead their startup has completely failed. You have blood on your hands. Don't let that happen. You don't want to live like that. It is terrible. So do what you need to do. Tell them about the show, send it to them. Put it on WhatsApp. Put it on Slack. Put it where you need to put it. Just make sure they know about it and they check it out.