How Peregrine Built a $6.8B Company by Doing Their Customer's Job

Two founders with no product and no pitch walked into a police department and offered to help solve crimes. That bet—working for free for 18 months—became the foundation of Peregrine, now valued at $6.8 billion. Ben Rudolph breaks down exactly how they did it.

Key Facts

• Latest Valuation: $6.8 billion, following a $250M raise (Pablo Srugo)
• Time Embedded in First Police Department: 18 months working as free crime analysts (Ben Rudolph)
• Average ACV: ~$250,000 (Ben Rudolph)
• Early ARR Trajectory: $1M → $3M → $10M (one, three, ten) (Ben Rudolph)
• First Seed Round Size: $1–2 million, raised ~9–10 months after founding (Ben Rudolph)

The Product-Market Fit Moment: Solving a Cold Case

Peregrine's PMF moment came when detectives called them—unprompted—to help crack a complex gang homicide they'd been working for years. Being the team a customer thinks of when they have their hardest problem is the signal. Peregrine's platform and team eventually served as expert witnesses in the resulting trial.

Most founders describe product-market fit as a revenue milestone or a retention metric. Ben Rudolph's version was more visceral: a homicide detective called him for help on a cold case. 'There was this complex homicide that they had been working on for a few years. It was gang involved. There were lots of burner phones, rental cars, and a couple people ended up getting killed,' Rudolph recalled. 'They had called us to basically ask for help on finding the next lead on this case.'

That moment—being the team a customer calls when the stakes are highest—is what Rudolph points to as the real signal. The platform Peregrine had been quietly building inside the department could ingest dozens of messy Excel files of cellular records, normalize them across time zones, and visualize movements geospatially. 'Being able to connect that all together, visualize it, understand where different phone numbers, people are in relation to, geospatially and from a temporal perspective—understanding the movements of the people involved in the crime is critical,' he said. The case moved forward to trial, with Peregrine serving as expert witnesses.

"That was when I was like, okay, we're at least providing something that they're thinking of us to solve this case." — Ben Rudolph

How to Get a Police Department to Let You In With No Product

Rudolph and his co-founder researched every captain and commander in the Bay Area—reading their past cases, mapping org charts, identifying tech-forward leaders—then sent highly personalized outreach. They weren't pitching a product. They were offering to help solve cases. One commander said yes.

Before Peregrine had a product, a pitch deck, or any law enforcement background, the founders needed a design partner who would let them observe, learn, and eventually build. Their approach was systematic. '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,' Rudolph explained. 'Isolated that list, we did a bunch of research on these folks, what kind of cases they worked in the past, and then we left very thoughtful messages.'

The message that landed with Commander Brian Bubar of the San Pablo Police Department wasn't a pitch—it was curiosity. They had researched a specific case he'd worked, Operation Red Reach, and asked to learn how he solved it. 'We were essentially like, hey, we are really interested in this case that you solved. We were interested in learning more about how you solve these cases. Could you take us along as a partner?' Bubar handed them a book of background checks and said: 'All right, let's see what you can do.'

The key insight: government agencies are flooded with vendor pitches. Showing up with research instead of a product is a credibility signal in a sea of noise. As Rudolph noted, '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.' Curiosity and service orientation does.

"The commander who ultimately said yes, we knew the exact case that he worked on. It was Operation Red Reach, and we knew the details of it. And could talk to him about it." — Ben Rudolph

"He definitely took a chance on us. We were very open and transparent with him in that we want to build a company." — Ben Rudolph

• Map the org chart: target number-two or number-three leaders who lean toward tech
• Research each individual's past cases and public records before reaching out
• Lead with service orientation, not a product pitch
• Reference specific work they've done—show you've done real homework
• Expect many rejections; you need one yes

Method Acting as Product Development: 18 Months as Free Crime Analysts

Once inside the department, Rudolph and his co-founder worked daily as crime analysts—manually sifting through case files, writing code to process data, learning the job the hard way. This 18-month immersion let them build software that solved real problems, not assumed ones.

Getting in the door was one thing. What happened next was unusual even by startup standards. The department gave them a room. Whenever a new case came in, they treated Rudolph and his co-founder like staff. 'They would essentially treat us as crime analysts and they'd be like, hey, we got a new homicide in. Here's what we know about the case. Can you help us with it?' The answer was always yes, even when they were doing it manually.

Rudolph, a programmer, was writing code throughout—but the starting point was always manual labor. This mirrors a pattern seen in other customer-led product builds. As Pablo Srugo noted on the show, a company called Ada built its chatbot by literally working as customer service agents for seven different companies first. Rudolph agreed with the framing immediately: 'Yeah, exactly. That's exactly the way I would frame it. It was the purest form of method acting.'

The on-the-ground learning also shaped the product in ways no user interview could. During an early deployment in Albuquerque, Rudolph was mapping gunshots from ShotSpotter data around a homicide. The pattern looked chaotic—dozens of shots. A detective explained that in Albuquerque, it's tradition to fire guns in the air at the end of a party. 'You learn these 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 meet their needs.' That kind of contextual knowledge becomes a durable competitive moat.

"It was the purest form of method acting." — Ben Rudolph

"I think of Peregrine's product as fifty percent of its technology. The other fifty percent of our product is really the way we deploy and the way we partner, and work with our customers." — Ben Rudolph

Forward-Deployed Engineers: Growth Driver, Not Margin Problem

Peregrine sent engineers on-site to customers for weeks at a time—embedding them deeply enough to integrate messy data, understand local terminology, and ensure the product delivered value. What looked like a services cost was actually their primary retention and growth engine in a high-trust market.

When Peregrine signed its second customer in Pittsburgh, they sent one of their first engineering hires to work out of that office for about three weeks. 'He basically worked out of that office for about three weeks integrating their data. They had this luau and he cooked a key lime pie, and he just completely got embedded with that department,' Rudolph said. The result was a far better data integration—because the engineer understood how that specific department talked about its own data.

This approach—now called forward-deployed engineering—was considered a liability by many investors at the time. The concern was always margin compression. But Rudolph reframes it: 'I think we've always thought about that investment as a growth driver, not as something that needs to be optimized away.' In a high-trust, word-of-mouth market like law enforcement, a successful deployment doesn't just retain a customer—it generates the next one. Peregrine's second customer came directly because one chief told another.

As the customer list grew from single digits to dozens, resource constraints forced product innovation. 'All our engineers are integrating data right now. We can't build any product,' Rudolph told his co-founder. That constraint led them to build a self-serve data integration platform—so non-engineers could do the work. They also created a new 'deployment strategy' function: professionals with a technical background who could handle last-mile configuration without pulling core engineers off product. Scarcity, in this case, bred the scalable model.

"I think we've always thought about that investment as a growth driver, not as something that needs to be optimized away." — Ben Rudolph

"If a customer is receiving value that is way more than what they are paying for, then you are in good long term shape with that customer." — Ben Rudolph

• Early FDEs delivered white-glove integration that created sticky, high-retention accounts
• Resource constraints forced Peregrine to build a self-serve integration layer
• A new 'deployment strategy' role (technical but non-engineering) scaled the motion
• High deployment investment = retention + word-of-mouth in a trust-driven market

Winning RFPs Written for Someone Else: The 120% Prep Rule

When Peregrine encountered an RFP almost certainly written for a billion-dollar competitor, they spent three weeks transforming their office into an emergency operations center, built bespoke demos using real local geography, and delivered what Rudolph describes as '120%' effort. They won a contract they probably shouldn't have.

Around Christmas 2020, Peregrine received an RFP for emergency operations work—wildfire rescue scenarios—in California. The contract wasn't written for them. These situations are high-risk by default. But Rudolph's team read the brief and decided to compete. 'We basically sprinted for three weeks to get our platform to a place where it could show these different demos,' he said.

The preparation was surgical. One demo required showing a path of travel through Lake Berryessa if roads were closed due to wildfire. Rudolph memorized the lake. The team transformed their office to visually mirror the customer's own emergency operations center—cameras positioned to match what the evaluators would see on their end of the call. 'We spent so much time preparing for this RFP... we went, I would say like a hundred and twenty percent on the effort there. We won that contract, probably shouldn't have won that contract. I'm sure it was written for some other billion dollar company.'

The broader principle applies to every enterprise sales motion: use research to manufacture credibility before you've earned a reputation. For first meetings, Peregrine would find open-source data resembling a prospect's actual data, integrate it, and walk in with a demo of their own problem. 'Showing up for a first meeting where you can demo, and speak to somebody about, pretty much their own data and own problems is really powerful,' Rudolph said. In markets where incumbents win on brand, effort and specificity are the equalizer.

"We went, I would say like a hundred and twenty percent on the effort there. We won that contract, probably shouldn't have won that contract." — Ben Rudolph

"Showing up for a first meeting where you can demo, and speak to somebody about, pretty much their own data and own problems is really powerful." — Ben Rudolph

Building Durably: Why Slow Early Growth Creates Moats

Peregrine grew from $1M to $3M to $10M ARR over several years—deliberately. Rudolph argues that the things that take the longest to build become the hardest to copy. Deep vertical knowledge, trust networks, and deployment playbooks aren't replicable by a well-funded competitor in a quarter.

Peregrine's early revenue trajectory—$1M, $3M, $10M—looks modest against today's AI-era funding stories. But Rudolph is direct about why that pace was the right one. '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 time—those are our moats, and those are durable.'

The go-to-market motion for government is genuinely hard. Sales cycles run nine to twelve months. Every state and county has its own procurement rules, political dynamics, and buyer quirks. 'There are little tricks in every single state and county that you have to learn,' Rudolph said. 'It's hard to enumerate every single one.' Each new vertical—emergency operations, health and human services—requires its own learning curve. Peregrine's strategy is to deeply understand one vertical before expanding to the next, rather than copying and pasting a playbook.

The fundraising flywheel followed the revenue flywheel, not the other way around. When Peregrine could show consistent year-over-year, quarter-over-quarter growth and a deployment backlog that outpaced their team's capacity, investors responded. '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 starting to be judged on its metrics and when you can show those, that's when it becomes,' Rudolph said. The $250M round at $6.8B is the result of that compounding.

"I really believe that to build big businesses, you got to stack bricks, and there are very few shortcuts in life. Those are our moats, and those are durable." — Ben Rudolph

"Go sit with your customer. Prove value, that is the thing. Get out of that apartment, go to the customer, try and find a situation where you can build alongside the customer." — Ben Rudolph

Vendor Pitch vs. Peregrine's Service-First Approach