AI Summary
5 min read“We were driving a Honda Accord across the Bay Bridge out of San Francisco every day to work with gang homicide investigators,” Nick Noone recalls of Peregrine’s early days, “and we had very close friends standing outside the women’s center in San Francisco protesting the police.” That tension—between building technology for public safety and holding empathy for those who distrust it—is the operating paradox at the heart of Peregrine, the company Noone and Ben Rudolph founded in 2018 to make cities safer without building a surveillance state.
The Forward Deployed Ethos
Both founders came to this mission from radically different but complementary backgrounds. Noone spent years as a forward deployed engineer at Palantir, embedding inside military and intelligence agencies in the Middle East. He learned two counterintuitive truths: you must co-own the customer’s problem and take pride in getting them to the outcome, but you must also recognize that it is the customer’s win, not yours. “Letting go of our own skills and abilities, trying to suspend our ego and really get into the customer’s context—it’s such a high-empathy, patient way of working,” he says. Rudolph, meanwhile, chose the UN Refugee Agency over Airbnb after college, deploying to Sudanese and Colombian borders. He saw that humanitarian crises were downstream of data problems: disconnected spreadsheets that made c
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What you'll learn
- 1 (00:00) **The Peregrine Thesis: Safety as Infrastructure** - The founders define the company’s core mission: leveraging technology to make cities awesome, starting with the foundational layer of safety.
- 2 (02:07) **What "Forward Deployed Engineering" Really Means** - Nick Noone explains the Palantir-originated concept and what Silicon Valley misunderstands about working inside institutions.
- 3 (05:46) **The Humanitarian Side of the Thesis** - Ben Rudolph shares his path from the UN Refugee Agency to building last-mile healthcare solutions, forming a parallel thesis about data problems.
- 4 (08:42) **The Founding Story: From Baghdad and Africa to American Cities** - The co-founders explain how their divergent experiences converged on the idea of building for municipal public safety.
- 5 (10:57) **The First "Yes": How They Got Inside San Pablo PD** - The founders detail the scrappy, trust-based approach that got them their first customer in a skeptical environment.
- 6 (14:36) **Navigating the "Defund the Police" Era** - Nick describes the psychological and cultural challenge of building a public safety company during a time of intense social turmoil and polarization.
- 7 (18:25) **The Anti-Data Collection Model** - Peregrine’s structural inversion of the traditional public safety tech business model (like Flock or Axon) is explained.
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Show Notes
Most public safety technology companies grow by collecting more data. Peregrine inverted the model: no sensors, no new data, a business built on connecting the data and information cities already own. Co-founders Nick Noone and Ben Rudolph received more than two dozen no's before San Pablo PD let them in the door in February 2018. Today, Peregrine powers law enforcement, emergency medical services, fire and rescue, and other services in more than 400 cities and communities globally. Nick and Ben explain their north star for data sovereignty, and discuss how Peregrine's philosophy and privacy-first approach to data access and ownership preserves individual privacy and cities' sovereignty. They walk through how AI and long-horizon agents are being deployed: a cold case agent that reproduced an exoneration detectives had reached by hand, a Wisconsin county that placed a suspect using cell records buried in 300GB of evidence, identifying threats to a synagogue, root-causing an escalation in weather-related incidents, and more.
00:00 Introduction
02:07 What Forward Deployed Engineering Means
03:58 What Silicon Valley Gets Wrong
05:23 UNHCR, Dimagi And Downstream Data Problems
08:25 Why Cities, Why Safety
10:45 Two Dozen Nos And San Pablo PD
14:19 Building Through Defund The Police
18:16 The Inversion Of The Collection Model
21:20 Data Ownership And Governance
22:57 From Nice Search To Deep Analysis
29:59 Agents Writing The Integrations
31:45 The Cold Case Agent
35:02 The Anti-Network-Effect Proposition
38:40 Facial Recognition And Hard Decisions
40:48 Technology For The Underdogs
42:54 Trusting The Individual Contributor
48:50 Ten Thousand Cities
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