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Garrett Langley of Flock Safety on building technology to solve crime

completed 1:44:45 Mar 05, 2026 Watch on YouTube

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Garrett Langley of Flock Safety on building technology to solve crime
Description

Garrett Langley is the founder and CEO of Flock Safety, a public safety operating system that helps communities and law enforcement eliminate crime. He sits down with John to discuss why most crime is opportunistic, how Flock helps clear over one million crimes a year, and the engineering challenges of building solar-powered cameras and autonomous drones. They cover the shifting landscape of criminal technology, why hardware requires making "one-way door" decisions, and his vision for a future where technology prevents crime before it happens. Full transcript on Substack: https://open.substack.com/pub/cheekypint/p/garrett-langley-of-flock-safety-on Subscribe to Cheeky Pint Spotify: https://open.spotify.com/show/2IHbGJJMpiFoz5YrvRfTFw Apple Podcasts: https://podcasts.apple.com/us/podcast/cheeky-pint/id1821055332 Substack: https://cheekypint.substack.com/ Key moments 00:00:19 Flock 00:19:51 Safety vs privacy 00:23:54 Crime and technology 00:32:36 Crime rates 00:43:56 Corporate security 00:52:16 Stripe Radar 00:52:54 Competitive landscape 01:02:41 Drones 01:09:01 The Flock business 01:11:39 Building hardware 01:20:01 Cameras 01:25:17 PD procurement 01:32:56 Building your own drones 01:40:52 What’s next for Flock? Books: - The Digital Silk Road: https://www.amazon.com/Digital-Silk-Road-Chinas-Future/dp/0063046288 - Boyd: https://www.amazon.co.uk/Boyd-Fighter-Pilot-Who-Changed/dp/0316796883

Summary

Generated by gpt-5.6-sol

At-a-Glance

  • Verdict: Watch fully
  • Core thesis: Flock Safety is evolving from a license-plate camera vendor into a vertically integrated, AI-driven orchestration and control plane that connects 911 calls, distributed sensors, cameras, drones, officers, and cross-agency data to compress crime response from days or weeks to minutes.
  • Why it matters: The interview provides a high-signal case study in agentic workflow design, real-world control planes, network effects, regulated-market distribution, hardware-plus-software operations, human-in-the-loop automation, and constitutional guardrails.
  • Best use: Use it as an architecture and operating reference for building consequential agent systems that ingest fragmented data, assemble investigations, recommend or trigger actions, preserve human authority at critical boundaries, and remain auditable.

Executive Summary

Flock began as a neighborhood license-plate camera after a firearm theft in Garrett Langley's Atlanta neighborhood went unsolved. The first camera identified the only nonresident vehicle present during a later theft, leading police to recover the gun. Local television coverage of solved crimes then became Flock's primary acquisition channel through its first roughly $20 million to $40 million of ARR. The founding insight was that conventional security products protect individuals and report that something happened, while public safety requires a community-scale system that helps resolve incidents.

The company now describes itself less as a camera manufacturer and more as the orchestration layer for city safety. Flock OS integrates its own and third-party cameras, real-time 911 calls, free-form visual search, vehicle data, drones, police dashboards, and officer dispatch. Langley gives an example in which an operator searched city cameras for a suspect wearing white Converse shoes and moved from a 911 call to arrest in about 17 minutes. Flock also builds agents for recurring crime patterns, such as detecting vehicles that repeatedly follow armored trucks, so understaffed departments receive preassembled cases rather than manually collecting every signal.

Flock reports approximately $500 million in ARR, coverage of more than 6,000 cities representing well over half the US population, involvement in clearing more than one million crimes during the prior year, and a private-sector business exceeding $100 million in ARR. Its defensibility comes from combining software, proprietary hardware, installation, maintenance, regulatory expertise, and a cross-jurisdictional data network. That integration is operationally punishing: Flock forecasts hardware demand 12 to 18 months ahead, pulled 77 permits per day in the prior year, employs field crews that dig holes and operate bucket trucks, and uses predictive maintenance to service devices before customers notice failures.

Langley argues for abundant sensing paired with strict access controls, short retention periods, perpetual audit trails, legislated use restrictions, and human accountability. He favors humans at the beginning and end of critical workflows—such as answering 911 calls and making arrests—while AI handles triage, correlation, case assembly, anomaly detection, and surge capacity. The unresolved tension is that Flock's benefits increase with coverage and data sharing, while the same scale raises surveillance, federal-access, and constitutional concerns. The company's longer-term ambition is therefore not merely higher arrest volume, but fewer crimes and fewer people entering prison through deterrence, employment investment, and alternatives for opportunistic offenders.

Key Takeaways

  • Claim: The highest-value AI pattern is an orchestration layer that converts fragmented real-time signals into an actionable case while keeping humans at consequential decision points. | Evidence: Flock OS can ingest a 911 call, identify incident characteristics with an LLM, search integrated public and private cameras through Freeform, package relevant evidence, and push it to an officer. In one attempted-homicide example, the only description was white Converse shoes; the workflow found the individual and contributed to an arrest about 17 minutes after the call. | Implication: For Ken's agent systems, optimize around closed-loop case assembly and decision support rather than standalone chat: ingest events, retrieve across systems, form a working investigation, route it to the correct operator, record every action, and preserve explicit human control at the start and finish. | Caveat: Langley explicitly distinguishes assistance from police work: humans still answer calls, interpret context, exercise authority, and make arrests, and Flock avoids claiming sole credit for cases where it supplied only part of the evidence.
  • Claim: Flock's network is valuable because it bridges the fragmented jurisdictional and data boundaries that make US law enforcement structurally inefficient. | Evidence: The US has roughly 17,000 cities with highly localized policing, while criminals cross city and state lines freely. Langley says a four-state human-trafficking case involving 76 arrests was coordinated through Flock among local departments, three state agencies, and the US Marshals. He also says local vehicle hot lists can update immediately while propagation to the FBI's NCIC system may take roughly 24 hours through CSV files and FTP servers. | Implication: The strategic moat is not merely better perception models but normalized permissions, shared schemas, fast propagation, and multi-organization workflow coordination. Ken should evaluate agent platforms by how well they span institutional boundaries without flattening local policy controls. | Caveat: Cross-agency sharing is constrained by state law and political legitimacy; states including California and Virginia restrict some collaboration with federal agencies.
  • Claim: A vertically integrated hardware, software, and field-service stack can create stronger terminal value than software alone, but it introduces irreversible product and capital decisions. | Evidence: Flock designs cameras and drones, installs poles and concrete, manages geographic inventory, monitors device telemetry, and performs predictive maintenance. It pulled 77 permits per day in the prior year, says roughly a third of employees perform physical deployment work, and expects hundreds of millions of dollars in operating cash flow from the now-profitable core business. | Implication: Ken should treat physical infrastructure as both moat and balance-sheet commitment. Hardware-agent businesses need explicit stage gates for product proliferation, 12-to-18-month demand planning, field-service economics, substitute components, and lifecycle support before adding SKUs. | Caveat: Flock expanded from one camera and one primary customer into multiple cameras, drones, trailers, software products, and customer segments too quickly. Langley says the newer hardware lines are still following the same expensive J-curve as Flock did five years earlier, leading the company to pause new hardware introductions for a year or two.
  • Claim: Drones can replace expensive, dangerous, or low-value physical responses when the system is optimized for time on virtual scene rather than maximum flight specifications. | Evidence: A Tennessee customer reportedly reduced initial visibility from a 7.5-minute officer response to a 68-second drone arrival. Departments use drones to avoid high-speed pursuits, triage 911 calls that no longer require an officer, and conduct thermal search-and-rescue. Flock says a San Francisco-sized city could require about 12 drones, an average drone can cover approximately 30 square miles and arrive in under a minute, and its busiest drone flies about 90 hours per week. | Implication: The reusable design principle is to optimize an autonomous system for the user's actual outcome metric, not headline specifications. Better sensing range can reduce travel, energy consumption, latency, and fleet size simultaneously, while event-triggered activation narrows legal and trust exposure. | Caveat: Persistent aerial surveillance creates unresolved Fourth Amendment risk. Flock dispatches drones in response to a defined event such as a 911 call, gunshot, or stolen vehicle rather than keeping them aloft continuously, and points cameras toward the horizon during transit by default.
  • Claim: Auditability, retention limits, and legislated purpose restrictions are core product features for high-consequence AI, not compliance added after deployment. | Evidence: Langley says every action in Flock is logged in perpetuity and can be publicly audited, while typical retention is seven days for live video and 30 days for license-plate data. He praises Virginia's 21-day retention limit, mandatory audits, and restriction to criminal investigations, and Flock employs a team of constitutional attorneys to review product concepts before release. | Implication: Ken should make policy enforcement native to the control plane: immutable action logs, purpose-bound authorization, scoped data retention, warrant or approval escalation, default-safe sensor behavior, and jurisdiction-specific sharing rules should exist at the architecture level. | Caveat: Retention reduces but does not eliminate abuse, and Langley is an interested party who favors substantially more camera coverage. He also objects to broad prohibitions on federal collaboration, illustrating that agreement on procedural controls does not settle who should receive access.
  • Claim: Distribution and installed-base advantages dominate finite-buyer government technology markets and will drive consolidation. | Evidence: Flock reports approximately $500 million in ARR and deployment across more than 6,000 cities, while Langley identifies Motorola Solutions and Axon as the two other scaled platforms. He says Motorola completed roughly 40 acquisitions in two years, Axon completed five in the prior year, and multiple VC-backed vendors now compete in narrow categories such as AI analysis of body-camera footage despite a limited number of police departments. | Implication: For investment and GTM analysis, favor platforms with existing public-sector distribution, deployment capacity, and data integrations over isolated features. In finite-account markets, a technically good point solution may be more valuable as an acquisition target than as a standalone company. | Caveat: Government procurement remains slow and costly: large purchases typically require RFPs, and Langley argues many RFPs are effectively written around a predetermined vendor. Small discretionary thresholds of roughly $25,000 to $50,000 can accelerate initial adoption but do not eliminate later procurement friction.
  • Claim: Flock's scale came from proving measurable outcomes publicly, turning each successful deployment into localized social proof rather than relying on conventional enterprise marketing. | Evidence: After the original neighborhood camera helped recover a stolen gun, a local 5 o'clock news segment generated five neighborhood inquiries the next morning. Langley says local-news stories about solved crimes remained the company's only meaningful growth channel through approximately its first $20 million to $40 million of ARR. The company now reports more than one million crimes cleared with its involvement in the prior year. | Implication: Outcome-based GTM is especially powerful in trust-sensitive markets: build an attribution standard that avoids overclaiming, then package concrete local wins into proof that the next buyer can independently verify. | Caveat: The metric is deliberately phrased as involvement in clearance rather than crimes solved solely by Flock, because tips, investigators, officers, and other evidence often contribute.

Detailed Brief

Crime deterrence depends more on certainty of detection than severity of punishment

  • Claims: Langley argues that many offenders make a Boolean decision based on whether they expect to be caught, rather than calculating the length or severity of punishment.; A city initially suppressing crime may displace it into neighboring jurisdictions, but broad regional coverage can eventually reduce the underlying opportunity rather than merely move it.; He says objective event-based policing, such as responding to a verified stolen vehicle, can reduce reliance on historically biased patterns of patrolling selected neighborhoods.
  • Evidence: Langley cites Cobb County, Georgia, as having a 100% clearance rate for violent crime and argues that this certainty contributes to declining violence.; He says crime shifted toward Oakland as San Francisco adopted Flock, requiring neighboring jurisdictions to adopt comparable capabilities.; Oakland is presented as using stolen-car signals to police where crime is occurring in real time rather than where crime occurred historically.
  • Caveats: The claimed causal link among Flock adoption, higher clearance, deterrence, and falling crime is asserted through examples rather than established with controlled evidence in the interview.; An anomaly or vehicle hit may justify investigation but is not itself proof of guilt; model errors and biased source records can still produce harmful interventions.
  • Implications: A control plane should distinguish between anomaly, investigatory lead, probable cause, and confirmed outcome rather than allowing confidence to inflate as data moves through the workflow.; Regional network coverage changes product value nonlinearly because isolated optimization can displace rather than eliminate the target behavior.

Private-sector expansion targets distributed physical footprints rather than corporate size

  • Claims: Flock's private-sector segment exceeds $100 million in ARR and is described as its fastest-growing business.; The best prospects are companies with many physical locations, employees, and movable assets—particularly retail, healthcare, and logistics—not necessarily the companies with the highest market capitalization.; The use case has shifted from post-COVID theft toward employee safety, executive protection, and early warning around terminated employees or suspicious cross-location activity.
  • Evidence: Langley contrasts a Fortune Five customer with only three large campuses against Dollar General's approximately 7,000 stores, making the latter structurally more valuable to Flock.; A terminated employee can be added automatically from an HR system to a local watch list so security is notified if that person returns.; For executive protection, the same unidentified vehicle appearing at both a CEO's home and office on the same day can trigger review.; In a healthcare case, thieves allegedly impersonated service technicians and removed robotic surgical equipment worth more than $20 million for resale abroad.
  • Caveats: Many detected behaviors are unusual rather than illegal, so enterprise deployments require strict policies separating notification, investigation, denial of access, and law-enforcement escalation.; Corporate and municipal customers operate at radically different geographic scales, making a shared roadmap and organizational structure difficult.
  • Implications: Physical footprint count, incident density, and integration surfaces may be better market-sizing variables than customer revenue.; Enterprise agent systems can create value by joining HR, access, vehicle, location, and security data, but employment and privacy rules must be embedded in alert handling.

International expansion is constrained by sovereign competition and subsidized Chinese infrastructure

  • Claims: Flock is prioritizing the US because Langley believes the domestic opportunity alone could support $5 billion to $15 billion in revenue.; International deployments add local legal complexity, hardware logistics, and direct competition with lower-cost Chinese surveillance infrastructure.; Data sovereignty and geopolitical access are part of the product decision, even when buyers focus primarily on acquisition price.
  • Evidence: In a Mexican government opportunity, Flock competed with Hikvision and was nearly ten times more expensive.; Flock offered to domicile the data in Mexico and argued that a deeply discounted Chinese system could expose real-time feeds to another government, but it still lost on price.; Langley says Chinese-manufactured cameras are also common in Western commercial environments because buyers can purchase them cheaply through consumer channels.
  • Caveats: Langley's description of Chinese state subsidy and access risk is his interpretation; the transcript does not provide documentary evidence for the specific bid.; Restricting expansion to the US avoids complexity but leaves strategic markets and standards influence to competitors.
  • Implications: Sovereign AI and sensor infrastructure may require government financing or procurement policy to compete against state-subsidized alternatives.; Data residency is insufficient as a trust claim unless buyers also understand firmware provenance, remote access, supply-chain control, and operator permissions.

Notable Concepts & Terms

  • Flock OS: The integration and orchestration layer that connects Flock and third-party cameras, 911 events, visual search, drones, officers, and investigative workflows.
  • Amplified intelligence: Flock's framing for AI that removes investigative busywork and expands staff capacity while preserving humans at the beginning and end of consequential workflows.
  • Freeform: A natural-language visual search capability used to locate people or vehicles from descriptions such as white Converse shoes or a white van with black-and-blue paint.
  • Hot list / NCIC: Vehicle alert lists used to identify stolen or wanted vehicles; Flock maintains fast local lists and integrates with the FBI's slower national NCIC process.
  • Cold plating: An anomaly-detection method that compares the visually inferred vehicle make and model against the DMV record associated with its plate to identify a potentially stolen or cloned plate.
  • Time on virtual scene: The primary drone-system metric: how quickly operators gain useful visual awareness, which favors high altitude and long-range sensing over raw flight speed.
  • Safe City: Flock's packaged citywide platform for maximizing crime clearance, estimated by Langley at approximately $20 per resident per year.
  • Thriving Cities Fund: Flock's investment initiative for local businesses that can create accessible jobs in cities adopting its safety platform; Langley reports a 21% IRR in the prior year.

Operator Notes / Why Ken Should Care

  • Add this interview to the reference set for human-in-the-loop agent architectures, specifically as an example of event ingestion, multimodal retrieval, case assembly, action routing, and immutable auditing.
  • Create a control-plane design checklist requiring purpose-bound permissions, jurisdiction-aware sharing, finite retention, operator overrides, escalation thresholds, and a distinction between anomaly detection and authorized action.
  • When assessing physical-world AI investments, model installation, permitting, geographic inventory, maintenance travel, spare parts, telemetry, and component substitution as first-class unit economics rather than treating hardware gross margin as the whole system.
  • Stress-test portfolio companies for product-proliferation risk: require evidence that the core line is through its capital J-curve before funding multiple hardware SKUs or materially different customer segments.
  • Screen public-sector point solutions for acquisition optionality by Axon, Motorola, Flock, or another installed platform; standalone viability should require a distribution advantage or a market larger than a narrow finite set of agencies.
  • For outcome-led GTM, define an attribution vocabulary before publishing wins so the company can distinguish sole causation, material assistance, and incidental involvement without creating credibility or regulatory exposure.
  • Monitor the emerging legal boundary between event-triggered autonomy and persistent surveillance, because the dispatch trigger, default sensor orientation, and cost-driven change in surveillance scale may determine constitutional treatment.

Source/Metadata

  • Title: Garrett Langley of Flock Safety on building technology to solve crime
  • Transcript words: 28656
  • Duration seconds: 6285
  • Timestamp note: No timestamps or chapters were included. The supplied transcript contains substantial duplicated passages and trailing extraction noise, but the substantive interview remains recoverable.

Transcript

20672 words en Processed in 3184.9s

Garrett Langley started Flock Safety in 2017 after a crime in his neighborhood went unsolved. Flock is now one of the most successful companies selling to law enforcement, known for their camera network across the roads, and even drones to support police officers. Cheers! Good to see you. Likewise, thanks for having me. OK, so maybe start by describing how does the Flock product work? Yeah. Maybe we go all the way back, because it's evolved. Mm-hmm. So eight years ago, living in Atlanta, and there's a fun fact: if you're in a place like Atlanta or Memphis or pick a town in the southeast, if you just pull 10 F-150 door handles, some—let's call it three out of 10—will be unlocked. And one out of 10 will have a firearm in the glove box. Which is, regardless of your point of view on it, you should keep the firearm in a safe. [SPEAKER_00] And you should keep it in a safe, not in a glove box. [SPEAKER_01] That's really bad. But that's what people do. Mm-hmm. [SPEAKER_00] And so if you're a gang member [SPEAKER_01] and you're trying to obtain a firearm, the easiest way is to drive into a neighborhood with six kids, because they're kids, jump out, and start pulling door handles. You're not breaking into the car, you're just pulling door handles. So this happened in my neighborhood. Someone got a gun. Someone posted on Nextdoor: "Oh my gosh, I forgot my gun in my car, and it's now gone." And so the Atlanta Police Department comes, and the major was fairly apathetic. "Hey, sorry. Good luck. We're not gonna..." So they're not going to fingerprint the vehicle. Yeah, yeah. And so I was like, okay, great. I was an electrical engineer. So I called a buddy of mine who studied computer science with me at Georgia Tech, and I was like, "Look, we're gonna go build this camera. We're just going to track license plates. That's it. That's what the Atlanta Police Department said." So, okay, great. So we built this thing. And if you ever come to Atlanta office, we still have the original camera on a pedestal that looks terrible. I'm not a mechanical engineer. We put it up. And all it did was track every car that came into our neighborhood. But as you can imagine, after 30 days, you start to know that person clearly lives here. They're in the neighborhood twice a day, four times a day. And so about two months later, another car gets broken into, another firearm stolen. The same major comes back. And I was like, "Oh, by the way, here's the only car that doesn't live in our neighborhood that was here last night." That car gets put on what we call a bolo— be on the lookout for. A couple hours later, they find that vehicle. The gun's in the car. The person goes to jail. And what was really interesting is, we were very proud of ourselves. This was not a business at the time. It was a project. And so the 5 o'clock news would do the story. So I'm on the 5 o'clock news. And the next morning, I had five emails from neighborhoods. And I think I might be the only company that for the first, let's call it 20 or 30 or 40 million of ARR, was strictly driven off of 5 o'clock news. That was our only growth channel. [SPEAKER_00] Yeah, yeah, yeah. [SPEAKER_00] That actual media appearance didn't strike... And every time we solved a crime, we'd be like, "Hey, do you want to cover this story at 5 o'clock?" [SPEAKER_00] And they'd be like, "We'd love to. [SPEAKER_00] We'd love talking about crime." [SPEAKER_00] Yeah, because this is local news. I mean, that's all they're talking about. It's local news. [SPEAKER_01] We're not going to go to the New York Times. [SPEAKER_00] No one cares about a stolen sofa. Yeah, yeah. [SPEAKER_00] Or a stolen dog. [SPEAKER_01] Okay, but that's interesting. Did you start with... Because I associate Flock today with being plugged into the stolen car databases. [SPEAKER_00] But you started without that, just looking up suspicious stuff. Yeah, well, if you think about it, there's 400,000 neighborhoods in America. And there's no consolidation of providing safety for those communities. And when I say neighborhood, that is a legally binding organization that can sign a contract. Yes, yes. [SPEAKER_01] Not like you and me just put 20 bucks together and say, "Let's buy this thing on the street." [SPEAKER_01] So that felt really interesting. [SPEAKER_01] And then the other interesting insight that we developed, which took time, is: I imagine at your house, [SPEAKER_01] you have a security system. You might have a gate to your house. You probably have a dog. [SPEAKER_00] Yeah. You have all these things, right? They do two things that are not helpful. They tell you a crime has happened. They don't actually help you solve it. And what about your neighbor? And so what we'd realize is that every single security system was focused on the individual. [SPEAKER_00] Yes. But I think about my life in Atlanta. There was a crazy random act of violence a couple of years ago. And my wife wouldn't run outside for a year. And it had nothing to do with us. [SPEAKER_00] Yes, yes, yes. Yeah. You have all these things, right? They do two things that are actually not helpful. They tell you a crime has happened. They don't actually help you solve it. And then what about your neighbor? And so what we'd realize is that every single security system was focused on the individual. Yes. But I think about my life in Atlanta. There was just a crazy random act of violence a couple of years ago. [SPEAKER_01] And my wife wouldn't run outside for a year. And it had nothing to do with us. [SPEAKER_01] Yes, yes, yes. It was a mile away. [SPEAKER_01] Yes. [SPEAKER_00] And so the whole premise became that you had to build a safety system for a community. Yes. [SPEAKER_00] Because that's actually what you feel. I mean, you live in San Francisco, you get it. [SPEAKER_01] Even if you've never been the victim, if crime is up, it's really bad. [SPEAKER_01] So it was all neighborhoods for the first three or four years of the business. [SPEAKER_01] So give me the stats on Flock today. Just how many cameras out there, crime stopped, and whatever. [SPEAKER_00] Because again, maybe just describe the product as it exists today. [SPEAKER_00] As it exists today now. [SPEAKER_00] So now it's a much more sophisticated product in that sense. [SPEAKER_01] So we're- Last year, we helped clear just north of a million crimes in America. What does help clear mean? So I mean, we want to be clear that, similar to probably how you feel in that, you help businesses grow, but you didn't do the hard stuff. [SPEAKER_01] I see. You're just involved in them. You made it easy. [SPEAKER_00] You made it really easy for me to grow Flock by making payments simple. [SPEAKER_00] Yeah. I don't actually have to do any of the hard work of chasing bad people, putting my life at risk. We write code and design circuits. It's not hard work. Yeah. [SPEAKER_01] So we like to be very careful of not overstating our value. [SPEAKER_00] Yes. So we were involved in the arrest, in clearance, or successful arrest of over a million crimes. Over a million crimes, wow. [SPEAKER_01] And in a lot of those cases, we are the end, the beginning, and everything. [SPEAKER_00] Yes. Outside of the human putting handcuffs on. And in some cases, we might be the tip of the spear. And so for more sophisticated investigations, like the Brown shooter and the MIT shooter, there was a tip on Reddit, but then Flock was the way they found them. Mm-hmm. We weren't the tips. Sure. We can't take full credit. So maybe I'll walk you through a recent example. And I won't name the city, because the case is still going through prosecution. But so there was a 911 call. This is a major city in America. Our system here is 911 calls. We can tap into 911 calls. This is wild if you think about 911. Today, when you call 911 in San Francisco, it's going to get about 3 million 911 calls a year. A human picks up every single time. A human manually listens, manually types in information. Imagine if you were running Stripe, and every single lead you received was human routed. Mm-hmm. You'd say, this is crazy. That's how we work in cities today. So we hear the 911 call in real time. What that allows us to do is then figure out what are they talking about? Is there any interesting information in the system that could find beneficial? So in this case, we had heard that it was an attempted homicide. Someone was bleeding on the street. And all they could remember was that the suspect was wearing white Converse sneakers. Now, we have a product called Flock OS that allows us to integrate all the cameras in a city, whether they're Flock developed or not. And so that 911 call pops up. The operator is, oh my gosh, there's a 911 call right there. They can listen to the call. They're, this is a really violent situation. There's a privately owned camera. I can tap in that, double-click that camera. They can use one of our products called Freeform. They can say, I'm looking for any individuals in the last 30 minutes that are wearing white Converse sneakers. They then find the individual. They can then push that video to the nearest officer. So we run on the dash of the police vehicles. And then that person gets arrested. And so if you think about the way it used to work, that case never would have been solved. Mm-hmm. It would have been weeks, maybe months, and it could have gone a cold case. [SPEAKER_00] And in this case, this person was from a 911 call to an arrest in about 17 minutes. So we can do that on people. We can do that on vehicles. So in that same version of the story, I'll give you one other story, and then I'll give you a sense of it. [SPEAKER_01] So in a town in Colorado, there was an armed robbery of a Levi's outlet. You've got to get your jeans one way or another. This is a funny one, actually. So they call 911. So we're plugged into 911, right? The real-time crime center operator hears it's an armed robbery. They also hear two things. The person has already fled the store, and they drove away in a white van that looks like a black and blue cow. It's mistake number one is criminal. Don't drive a weird car. Now, this police department also has our drone that we build here in America. So they immediately click a button. The drone automatically flies at 400 feet to the Levi's outlet. That drone knows what to look for. It has the visual nomenclature of a white van with black and blue spray paint. Using that same freeform, we can start to look for it. They also hear two things. The person has already fled the store, and they drove away in a white van that looks like a black and blue cow. [SPEAKER_01] It's mistake number one is criminal. Don't drive a weird car. Now, this police department also has our drone that we build here in America. So they immediately click a button. The drone automatically flies at 400 feet to the Levi's outlet. That drone knows what to look for. It has the visual nomenclature of a white van with black and blue spray paint. Using that same freeform, we can start to look for it. We get another 911 call of another outlet that's having the same time. So the drone is ready in the air, zooms over. Drone has eyes on it. That video feed can now be sent straight to the nearest officer. And so in a traditional response, you're going to come in hot, blue lights flashing. Someone's going to get hurt. In this case, the drone is foreign to the air. You have no idea. The drone is there. The guy drives home. As soon as he pulls in his driveway, two cops pin him in. Safe tactical apprehension. So it's drones. It's some computer vision. It's cameras that track cars. It's quite a robust portfolio. And what is Flock by the numbers today? So how many cameras, how many drones, how many law enforcement agencies, how many individual entities? [SPEAKER_00] Yeah. [SPEAKER_00] So it's just over 6,000 cities. So it's well north of 50% of America. That's covered by Flock. By population. [SPEAKER_00] Yeah, by population. So there's about 17,000 cities in the US. And we have all the big ones outside of Manhattan at this point. [SPEAKER_01] That's the last one to go get. [SPEAKER_01] Yes. [SPEAKER_01] I'm not sure if that's going to happen anytime soon, the current situation there. But yes, it's pretty well deployed. And then the business has gone from zero to about 500 million in ARR in the last seven years, building cameras, drones, and selling it to the government, which is three strikes are out. That's incredible. [SPEAKER_01] And I feel something non-American listeners might not realize is, so I grew up in Ireland, a country of 5 million people, and there is just a police force, the Gardi Síochána, the national... [SPEAKER_00] For the whole country. [SPEAKER_00] Exactly. Police force for the whole country. [SPEAKER_00] And that is a relatively common model in lots of places. In the United States... [SPEAKER_00] It's the opposite. [SPEAKER_00] It's very localized. [SPEAKER_00] And maybe you want to talk about the average size of it. And I feel like what you're providing is, in some ways, scale economies and helping police forces... [SPEAKER_00] Yeah. [SPEAKER_00] Coordinates with other agencies. [SPEAKER_00] It's interesting that there's a dynamic that people don't understand, which you're right. So Ireland, most of the EU, Australia has six police departments. So, I mean, let's call it effectively the same. It's a really big country. It's a lot of land. And most of South America. America is really the only country that operates under a model where local municipalities provide a law enforcement service. It's very rare. Yeah. [SPEAKER_01] And the benefit, the pro is straightforward, which is you actually have a good chance of knowing the police officer that has your territory and has your patch of dirt. [SPEAKER_01] The downside is criminals don't really care where cities start and stop. They don't care where states start and stop. [SPEAKER_01] Yet historically, law enforcement agencies were incapable of sharing information. [SPEAKER_01] So if you were a law enforcement agency, you could not host your data in the cloud until 2022. Maryland was 2023. [SPEAKER_01] So any coordination between agencies was very manual. All phone calls. Yep. [SPEAKER_01] Faxing files. [SPEAKER_01] And so one of the big unlocks of Flock was this realization that you could drive better collaboration. Because if you're a low-level criminal, isn't changing cities. [SPEAKER_01] Mm-hmm. [SPEAKER_01] But you look at some of the most successful cases we've helped work, it's multiple states, right? [SPEAKER_01] We did a huge human trafficking bust. 76 people arrested across four states. [SPEAKER_01] All organized on Flock. [SPEAKER_01] And it's really hard for one agency to wrap their hands around that whole thing. No. At that point, you've got six different local cities, two different... sorry, three different state agencies and the US Marshals. [SPEAKER_01] Yes. All collaborating inside of Flock. Yeah. And that's... [SPEAKER_00] That's how it should work. [SPEAKER_00] Yes. Because in Ireland, that is actually the only option because you're the same police department. [SPEAKER_00] It's a very unique problem that America has created. Law enforcement coordination. Yeah. [SPEAKER_00] Yeah. It should be... It shouldn't be controversial. Yes. But it's actually a very controversial topic. [SPEAKER_00] What's controversial about another way of this controversy? This is an interesting question of your trust in government probably follows some type of logarithmic expectation or linear expectation of the farther you are removed from those people, the least trust you have. And so most people's trust in the federal government is very low. State, a little bit lower. Local, full trust. Yeah. And so there's this interesting dynamic where... Let's talk about the most recent case. My guess is that most people don't have a lot of trust for certain federal agencies. But when stuff goes really bad, the Guthrie kidnapping, it's the federal government that runs the investigation. They are the only ones with the actual resources to work these cases. It's the FBI that's running that investigation. [SPEAKER_01] And so, most people's trust in the federal government is very low. State, a little bit lower. Local, full trust. Yeah. And so, there's this interesting dynamic where… Let's talk about the most recent case. My guess is that most people don't have a lot of trust for certain federal agencies. But when stuff goes really bad, like the Guthrie kidnapping, it's the federal government that runs the investigation. They are the only ones with the actual resources to work these cases. It's the FBI that's running that investigation. The brown shooter, the FBI. The Mar-a-Lago assassination attempt. [SPEAKER_01] The Secret Service. [SPEAKER_01] It goes down, but people have this big distrust. And so, we actually see it in places like California. There is state legislation that law enforcement is not allowed to collaborate with the federal authorities. Yeah. Because of all the other stuff. On certain topics. Because of all of the… [SPEAKER_01] It's just different politics. Yeah. [SPEAKER_01] Yeah. And so, we have to sit in the middle. Yes. [SPEAKER_01] And when it's clearly legislated, like in California, it's actually… It's fine. Yes. That's the law. [SPEAKER_00] That's actually very simple. [SPEAKER_01] Yeah. It's in other states where it's opinion. [SPEAKER_00] Yes. [SPEAKER_01] And that's, oh, that's really messy because we should just write laws. We should… We operate in a regulated space. Regulation, when done properly, just defines the rules of engagement. Mm-hmm. And sometimes it's better or worse, but at least everyone knows these are the rules. [SPEAKER_00] Yes. [SPEAKER_00] Yes. As I think about where Flok grew up and the… [SPEAKER_00] Helping with flagging stolen vehicles and kind of a very vehicle-oriented product, [SPEAKER_00] how does that work at a technical level? [SPEAKER_00] You guys… [SPEAKER_00] There was a stolen database… [SPEAKER_00] There was a database for stolen cars already, but that's an example of prior cross-law. [SPEAKER_00] Yeah. [SPEAKER_00] Who maintains that database? [SPEAKER_00] How does it work? [SPEAKER_00] Yeah. [SPEAKER_00] So, it's a good question. So, there's… You think about… [SPEAKER_01] There's a couple of fun engineering problems that Flok had to solve. [SPEAKER_01] The first is, how do you do it? We just described, you know, read a license plate, track a car on solar power with a 5G backhaul. And… Which is the camera that you have installed at a traffic light. Yeah, exactly. [SPEAKER_00] But you very rarely have fiber or power where you want to put a camera. [SPEAKER_00] So, you want a self-sufficient box that you can throw up… Totally infrastructure-free. [SPEAKER_00] …at an intersection. [SPEAKER_00] Yeah. And be able to track a car going 100 miles an hour and do some level of computer vision on top of it. [SPEAKER_00] Yes. And that was a pretty fun problem because if you put, you know, let's say you wanted to put a GPU in it, [SPEAKER_01] you're going to… Yeah. …you can't run on solar power then. Yeah. [SPEAKER_01] And so then it's, all right, well then what do you do on the edge? What are you doing on the computer? And you can't buy any GPUs these days. Yeah. Yeah. [SPEAKER_00] That would have been a huge disaster for us. [SPEAKER_01] But so the FBI maintains a list called the NCIC, which is about quarter to half a million [SPEAKER_01] known vehicles with other warrants. [SPEAKER_01] Could be Amber, the Amber Alert System, the Silver Alert System. [SPEAKER_01] We saw sadly a ton of Silver Alerts too. [SPEAKER_01] I think we did just over a thousand Amber and Silver Alerts last year that we helped clear. [SPEAKER_01] Mm-hmm. [SPEAKER_01] It's missing adults, missing seniors and missing kids, which is pretty sad stuff. [SPEAKER_01] And so we have a direct integration with the FBI for that. [SPEAKER_01] And then at a local level, let's say the Bay Area. [SPEAKER_01] Yeah. [SPEAKER_01] There is a Bay Area hot list that we maintain with those agencies. [SPEAKER_01] Oh, wait. So I assume that there was a single integrated… [SPEAKER_00] …when a car is called in and stolen. [SPEAKER_00] Yeah. [SPEAKER_00] I assume that went somewhere integrated. [SPEAKER_00] Ah, so this is kind of scary. [SPEAKER_00] So let's say your car is stolen and you're in South Carolina. San Francisco. They will immediately put it in the Bay Area flock hot list immediately. [SPEAKER_01] It will take 24 hours to make it to the FBI hot list. [SPEAKER_01] Oh. And that's a CSV file that gets sent around on FTP servers across the US. [SPEAKER_01] As much as the economy runs. [SPEAKER_01] Yes. We're very used to that model. You should be used to that at some point. [SPEAKER_00] Yeah, yeah, yeah. [SPEAKER_00] Exactly. [SPEAKER_00] But so the real time happens on flock and then there's about a day lag to make it nationwide. [SPEAKER_00] Okay. So, local entities have some kind of local lists and those propagate to a national database, which is an FBI database. [SPEAKER_00] Yeah. [SPEAKER_00] And what you guys are doing is making that real time, which obviously, if a crime is unfolding [SPEAKER_00] in real time, is a big deal. Exactly. Yeah. [SPEAKER_00] Yeah. That's interesting. It's not good to wait a day. [SPEAKER_00] Yes. Yeah. [SPEAKER_00] You can drive really far in 24 hours. [SPEAKER_00] It turns out. [SPEAKER_00] Yes. [SPEAKER_00] Yeah. [SPEAKER_00] And then you had some great stuff before about just a fraction of stolen cars are bad news. [SPEAKER_00] The fraction of crime. [SPEAKER_00] So it's, there's an interesting phenomenon where you don't, no one really steals a car for fun. There's not much you can actually do. Is that true? [SPEAKER_01] All the sideshows and stuff? [SPEAKER_01] Isn't there a little bit of stealing cars for fun? [SPEAKER_00] Yes. [SPEAKER_01] Yeah. You can drive really far in 24 hours. It turns out. Yes. [SPEAKER_00] Yeah. [SPEAKER_00] And then you had some great stuff before about just a fraction of stolen cars are bad news. The fraction of crime. [SPEAKER_00] So there's an interesting phenomenon where you don't, no one really steals a car for fun. There's not much you can actually do. Is that true? All the sideshows and stuff? Isn't there a little bit of stealing cars for fun? Well, the sideshows are definitely fun. Never participated in it. Neither have I, but yeah. But it's a huge problem. [SPEAKER_00] I just want to make clear here. Yeah, yeah. That's my official statement of the matter. Dirt bikes haven't ridden a dirt bike in a sideshow, but have watched plenty of videos online. That's fun. [SPEAKER_01] You're typically not stealing a car. You're typically driving your own car. [SPEAKER_01] Oh, okay. [SPEAKER_01] And those, you typically like, well, there are some people who would steal a car and just drive it for fun. [SPEAKER_01] Yeah. The main use case is when my car was stolen. My car was stolen. And then they used it to go rob three CVS's. Yeah. [SPEAKER_01] Did a bunch of drugs in the car and then ditched it. And that's a normal use case—you steal a car to go do something bad. [SPEAKER_01] Yeah. Yeah. Or you steal a car to go shoot someone because you don't want to shoot someone in your own car. [SPEAKER_01] If you're thinking ahead, you want to do it in a stolen car. [SPEAKER_01] Yeah. Yeah. And so there's— [SPEAKER_01] We've all watched Pulp Fiction. It's— [SPEAKER_00] Yeah. This is how you do this, right? [SPEAKER_01] And so we do a bunch of other interesting things. We have this feature called cold plating, where if we detect that the vehicle from an AI perspective, the make and model doesn't match the DMV record, that clearly the person's driving with a stolen license plate. That's another thing you can do. It's easier than stealing a car. You steal someone's tag. [SPEAKER_01] Uh-huh. [SPEAKER_01] So then you have to go down to stealing the same license plate from the same type of car. [SPEAKER_01] Yeah. [SPEAKER_01] It's weird. That's a glitch in the matrix. So we have all these, and we would call them more anomaly detections where it's like, this isn't— [SPEAKER_01] Mmm. [SPEAKER_01] This isn't illegal yet, but it sure is weird. [SPEAKER_00] Yes. And it's enough to provide enough reason to pull someone over. [SPEAKER_00] Yes. [SPEAKER_00] And depending on the size of the city, it's enough to dispatch an officer. I think if you're a major city, like in San Francisco, you have enough going on. Yes. But if you're a smaller town, where thankfully you don't have violent criminals running around every day. Yes. [SPEAKER_01] You're thinking, "That's weird. We have two cars with the same license plate in different parts of the city. We should go see what's going on." [SPEAKER_01] Yes. [SPEAKER_01] It strikes me that what Flock is doing is not changing any of the norms around privacy, but really expanding law enforcement's bandwidth to deal with stuff. And so I don't think anyone really has an expectation of a right to privacy of the car they are driving just being observed from a distance or their license plate being readable when out on a public road. Yeah. [SPEAKER_00] But if a car is called in as stolen, rather than officers manually looking for that car and that license plate, instead you can just get it much more quickly. And yet this ends up controversial from a privacy point of view. So I don't know, is that take too generous? Is there a steelman of the other side? Why is it? [SPEAKER_00] There is. I mean, I think you're right on the controversy. I would articulate it as: if you're building a business that impacts millions of people's lives, it's going to have some degree of controversy. I'm sure people hate Stripe. I don't know why they would, but I'm sure that person exists. Just like there's someone who hates Walmart. They're trying to sell cheap groceries. Why do you hate? It's like people hate Airbnb. People hate every company. Maybe they hate us more. I don't know. I think there are a few things that make it a steelman argument. One is you can see it. I bet if we pulled up your iPhone and looked at the number of apps that you've given full-time location services, it would shock both of us. And if we looked at the number of data brokers who leveraged that data to sell you ads, we'd be really shocked. And I think if we rewind 30 years ago and said, imagine these private companies tracked your location in real time and sold that to advertisers, we'd be like, that is unacceptable. But because we can't see it, we kind of let it go. We have this perception of anonymity. Anonymity. Anonymity. Thank you. Yet you're an engineer. How many data points do you need to triangulate where someone is? Where they sleep and where they work? And I know exactly who you are. Yep. And so there is that piece: because we operate in the physical world, we are held to a higher standard, which I think is a shame because, in my personal opinion, what I do online is way more interesting and telling about my personality and my life than what I do in the real world. Like I go from work to home and to kids' birthday parties. Anonymity. Anonymity. Thank you. Yet you're an engineer. How many data points do you need to triangulate where someone is? How about where they sleep and where they work? And I know exactly who you are. Yep. And so there is that one piece, which is because we operate in the physical world, we are held to a higher standard, which I think is a shame because personal opinion, what I do online is way more interesting and telling about my personality and my life than what I do in the real world. I go from work to home and to kids' birthday parties on the weekends. That's my life. So there's that piece. The second piece is there is an appropriate debate of what level of privacy erosion are we willing to take for an increase in safety? Now you and I both choose to live in cities that have governments. So we've already chosen to remove some of our privacy. We drive on public roads, where constitutionally we have no extension of privacy because we're using the government's roads with the government's license plate. We have a driver's license in our pocket. Driver's licenses are a modern thing. That hasn't been around for 200 years. It's a newer concept. So we've accepted all of those. Yeah. The articulation that I would have is I want my kids to be safe. Mm-hmm. And as long as there's accountability of how the information is used, which we do, every single action in our system, the audit is stored in perpetuity and it's publicly available. And for us, we really believe in this concept of a certain data retention, which limits the level of abuse. It doesn't eliminate abuse. There's still going to be abuse, but it limits that. If it's seven days, 14 days, 30 days of data, it's just not that interesting. Yeah. And relative to what you see with data brokers online where they have your entire internet history stored forever, you're interested in fresh data. That's what's useful. Yeah. But criminals, yeah. There's a really fast drop off of where have you been in the last couple days versus where were you a year ago? It's very irrelevant in a criminal investigation. Yes. Yes. Or it's protected behind a warrant, which is fine. Right. You talked about cell phone locations and your cell phone having your GPS location. And I'm reminded of the phenomenon where it feels like the balance of power and the offense defense mix within crime fighting tends to change over the years as new technologies are invented. And criminals get wise to fingerprinting existing and things like that. It feels like cell phone locations have had a huge impact on crime fighting. Not even GPS location, but just the coarse cell tower data. And in particular in murder cases, it's had a huge impact. I'm curious what are the other major trends going on from a technology point of view in how crime gets fought? Yeah. That's CDRs would be the nomenclature in the law. What's CDR? Cell phone data dump or CDR cell data records. Something like that. Yeah. Yeah. But it's your point. It's the broader, you hit these three towers, therefore you're in this general vicinity. That is one of the best kept secrets for law enforcement of how to solve crime. Yeah. Which, people dumbly commit crime with their cell phone in their pocket every time. Yep. It's very, I think I've heard of one case in the last 12 months where someone was smart enough to commit a homicide and left their cell phone at home by design. It was a very intentional, they were very organized. It's in the area. A couple other ones. How did they get caught? It's actually a flock obviously. So they were smart enough to leave their cell phone. Yeah. They were dumb enough. They drove from LA up to San Francisco, general area. They had a bunch of flock cameras along the way. They didn't pick up their cell phone until they went back to LAX. And we have cameras all around LAX. And they finally made that one mistake. They had it was a completely cold case until they got a hit on the car pulling into LAX, then got the cell phone, could do the whole thing. Which is a good case. And I guess the thing you can do is you can know that a cell phone's in a car because you can— We don't touch that, but law enforcement can. But you're sorry, law enforcement can cross-reference cell phone location with flock. What were all this? So they knew that the vehicle was in a certain parking lot. Yeah. They can then use, they have to have a warrant at this point. Sure. A warrant to pull what cell phones were in that area and then start to build the case. But to your question, I'd say the most current phenomena that is causing a ton of problems domestically is drones. And this is an example where it's asymmetric warfare that law enforcement is being put up against where criminals have no rules. How are criminals using drones? So here's a good example. In one of the counties we work with, it's an affluent-ish county in the Virginia area. South American cartels fly illegal drones through these neighborhoods. They'll flip on night vision, look through houses to see if anyone's home, then go break in. They don't want a confrontation. They just want to do so much stuff. People are using drones to case houses? To scope out. Yep. Wow. And this is where the downside is. Law enforcement has just recently in the last year been allowed to fly beyond visual line of sight. These guys have been operating for years. Sure. They jerry-rig an LTE modem to a cheap drone. They can fly it anywhere, however they want. And then legally, even to today, law enforcement is not allowed to engage that drone. They can't take it down. Hmm. It's FAA airspace. It's not law enforcement airspace. Sure. Yeah, yeah. Yeah. And so they just sit there. And so that's a problem in neighborhoods. That's a problem in prisons. It's probably the number one problem we have in our prison system today. Well, a lot of problems in prisons. But one of the leading problems for enforcement officers is you've got these pretty incredible, actually, from an engineering perspective, drones that are carrying 10, 20, 30-pound payloads, flying them over the prison walls. And they'll literally dangle it down to the prison cell, and the person will reach out and grab it. It's FAA airspace. It's not law enforcement airspace. [SPEAKER_00] Sure. Yeah, yeah. [SPEAKER_00] Yeah. [SPEAKER_00] And so they just sit there. And so that's a problem in neighborhoods. That's a problem in prisons. [SPEAKER_00] It's probably the number one problem we have in our prison system today. Well, a lot of problems in prisons. But one of the leading problems for enforcement officers is you've got these pretty incredible, actually, from an engineering perspective, drones that are carrying 10, 20, 30-pound payloads, flying them over the prison walls. And they'll literally dangle it down to the prison cell, and the person will reach out and grab it. [SPEAKER_00] Whoa, and we had a killer from Zipline out here. It's Zipline for criminals. It's—and these guys have built a comparable product. Yeah. And I was with a sheriff that I know really well, and he was like, if I shoot that down with a shotgun, I am technically breaking the law. I'm breaking federal law if I shoot this down with a shotgun. [SPEAKER_00] Yeah. [SPEAKER_00] And so you're seeing states now pass, like Louisiana has a state bill. Georgia's working on a state bill that says, sorry, FAA, we're going to do what we want. And that creates a problem, because most law enforcement officers just want to follow the law. Yeah. And presumably that won't stand up from a federal preemption point of view. No. And the other challenge is, I think you and I would say, who's going to enforce this? The FAA is not an enforcement body, but these people want to follow the law. And the law says clearly, you can't shoot a drone down. You can detect it. You can't mitigate. I have no idea. It's a totally crazy law. [SPEAKER_01] Yeah. What else has gotten worse from an offense perspective? [SPEAKER_01] I mean, this is one that's, you know, I don't know if I have strong feelings on this topic, but this concept that we appropriately hold local law enforcement to a very high standard of accountability and audibility. And I think that's very good. [SPEAKER_01] Yes. The downside is we don't with criminals. And so as a citizen, you want to be the victim of a crime. You get really frustrated that they're not working hard enough. And it's really that it's that they don't have the tools. They don't have the data, or they're not legally allowed to get to the data. And the warrant system is a very good thing. It's a very effective tool. But there's a debate of whether law enforcement should have more ability to solve crime faster. And the example of the framework that we use is, I don't know how you land this, is that the severity of a crime should be commensurate with the sophistication of technology. And I'll give you an example. Facial recognition, hot topic. There are thousands of cities in America that have banned law enforcement from using facial recognition. John, facial recognition is not bad. That's a technology. It's not good either. It's just technology. I think a way more effective measure would be to say, hey, look, facial rec has its pros and cons. You can't use it for shoplifting, but for homicides, crimes against children, go to your list of things that we as a society care deeply about. Law enforcement should do everything in their power to solve those cases. And then the petty stuff, we should say, look, we got to make progress there. But you know, you stole a pack of Skittles. We probably shouldn't deploy a drone to find you. If you kill someone, I think we should work really, really hard as a society to hold you accountable. [SPEAKER_01] Yeah. But there's no nuance. That nuance does not come through. [SPEAKER_01] No, they're just like facial rec is bad. And we don't do facial recognition for that reason because it's too controversial. But that's counterintuitive to me when the technology gets better every day. Yes. Yes. And obviously, another interesting thing that's happening amongst these trends is the prevalence of body cams, which I think maybe was in some corners promoted by law enforcement skeptics, but I think now has— [SPEAKER_01] It's backfired? [SPEAKER_01] I wouldn't say backfire, but just like, it's actually, in a lot of cases, been somewhat exonerative, right? Yeah. No, I think in many cases, police were really hesitant to get body cameras. I mean, imagine if you wore a body camera all day at work, you'd be like, I'm not sure if I love that idea. It's a little bit invasive, but they did. And I would say in the majority of cases that I see where foul play is called, it is almost always the inverse where the law enforcement officer was just trying to do their job. And on the other side, there was a mental health issue. There was something gone wrong and it actually exonerates the officer, which is interesting. And I think the same thing is true, at least we're seeing on the camera side, on the streets is, you know, historical policing, sadly, is quite prejudiced, right? We all have our biases, whether it's conscious or unconscious. So you have bad data in, you get bad data out. And so the traditional way of policing is, you go to dangerous neighborhoods, look for suspicious people and arrest them. So it's like you're perpetuating a trend against a certain community. And when you look at Oakland as a good example, who's quite a big supporter of Flock, they're like, we need a more objective way to police. Let's just focus on stolen cars. We don't care who's inside. We will find out eventually that car was stolen. And then you don't wind up policing where crime has happened historically. You wind up policing where crime is happening right now in real time. And that is a fairly fundamental shift in how policing works. And it, for many cities we work with, changes the perception of the community with law enforcement. Because they're no longer felt like they're being targeted. It feels like it's, wherever crime happens, we're going to go chase it. And if there's not been crime in the last couple of days, then we're good. Yep. Yep. Is crime up or down in the US? It is down. I think it'll continue to go down. COVID was really bad. [SPEAKER_01] So it surged during COVID? [SPEAKER_01] Crazy surge. [SPEAKER_01] Okay. [SPEAKER_01] People lost their minds. I think we tested society of what happens if you keep people inside for too long and people got really violent. [SPEAKER_01] Yeah. So do you have an explanation? Is it that it was a mental health issue or was it kind of a There's not been crime in the last couple of days, then we're good. [SPEAKER_00] Yep. Yep. Is crime up or down in the US? [SPEAKER_00] It is down. I think it'll continue to go down. COVID was really bad. So it surged during COVID? Crazy surge. Okay. People lost their minds. I think we tested society to see what happens if you keep people inside for too long and people got really violent. Yeah. So do you have an explanation? Is it that it was a mental health issue or was it a crime of opportunity that things were less well guarded and there's more opportunities for crime. But you think it was just people went a bit batty being locked up? I think so. And resorts to crime. But I mean, I'm obviously not a clinical psychologist. But it's that you just look at the data and there's no other way to articulate why homicides three to four X and then plummeted back down to, let's call it somewhat reasonable levels. There's a very few number of cities that are left at COVID levels. Most cities had this massive spike. Yes. And the way to, if you look at the people who were committing that violence, they tended to be 16 to 22 male and very online. Very online? Yeah. And so this is really sad. That's right. How do you measure very online? Oh, let me give you an example. I was in a town, a major city not too long ago, and I was asking the chief to tell me what's going on. This is a couple of years ago, right? Like during COVID. And she was like, Garrett, these kids are just killing each other. I was like, what? She's like, yeah, they're literally getting in their car and just shooting each other. I'm like, why? I'm like, oh, because this guy posted a picture of him with that guy's girl on Instagram. [SPEAKER_00] And I think in a normal situation, you might've called that person and been like, hey, bro, that's my girl. And in other cases, they're getting in a car shooting someone. And that's not normal. That's not normal behavior. And it wasn't normal before COVID. And it happened a lot during COVID. And then it's largely gone away. But it was a very specific social phenomena where the race to violence was so dramatic. It was so scary. Mm-hmm. And I don't think society has necessarily gone fully back to normal, but if you look at the data, it's hard to articulate that that's the most obvious explanation to me. And I guess there are other empirical measures like air rage incidents, road rage incidents, all of that kind of stuff went up during COVID. Everything went up. Like everything. People just literally lost their minds. I think we need to be outside. Yeah. But okay. So how are we doing now on crime? You say it's down. Is that across all categories? Because you know, you read Twitter and it's like, everything's locked up at CVS and San Francisco is full of, you know, there's all these memes, which are, maybe do some debunking and confirming of all the memes. [SPEAKER_00] So every city is a little bit different. Major cities still have major crime problems. Mm-hmm. I would argue, you know, I live in Atlanta and the mayor, you know, he's made it very clear. Anything greater than zero homicides is a tragedy. And therefore, we're on the race to zero still, like as an unacceptable level. And we're down historic lows over the last decade, but it's still pretty hard to wake up and go, you know, only 52 people died in Atlanta last year. And you can't pat yourself on the back for that. I think where we're focused on is more so clearance rates. And that's actually getting better, but only better in certain cities. Now we track it across Flock, you know, not to overly promote, tends to be that if you have a Flock product, your city has a much higher clearance rate. You look at San Francisco as a great example, the new chief, the prior chief, Mayor Lurie, they are making crime a focus. And the focus is on solving crime. Yes. And when they solve it, as I'm sure you follow on the news, they talk about it. Yeah. And they should, because it's really cool. They're working very hard. And what you'll see is back to the online point I made, obviously, people are online. And so when San Francisco PD is dominating X, it has a deterrent effect. [SPEAKER_00] Oh gosh. Yeah. You don't want to get caught. Yeah. And that's the counterintuitive point on crime is that most people would intuitively say, oh, if the punishment's really, really bad, people will do less of it. But you were 16, 18 at one point, you operate on a Boolean mindset. I will get away with this. Therefore I will do it. I'm gonna sneak out of my house because I'm not gonna get caught. You don't care if the punishment is being grounded for a week or a month. You're gonna get away with it. It's just when I get caught in us. Yeah. Yeah. Yeah. And so when you flip-- I'm not looking at this criminals are so online. So if you flip the, oh, it's a subculture. You gotta get there. But I mean, you'll see. Sorry. Is this like Reddit, Twitter? They're everywhere. Pinterest. I don't, less Pinterest. But I mean, TikTok's really big. Yeah. Instagram's really big. Snapchat's really big. And it is, it's how they recruit though, right? Because the whole recruitment effort is, you know, I'm gonna show a lifestyle online that seems dream worthy. Yeah. To recruit these people. And then they're in, and they're gonna perpetuate that. And the data actually showed it's actually not a very good job. You actually don't make very much money being a criminal. It's the medium income for your average criminal is very, very low. Yeah. But they promote a lifestyle of wealth. So if you look at those cities, like, you take San Francisco, crime's coming down, clearance rates are going up. And I would say, as soon as we can get somewhere like San Francisco to a hundred percent clearance rate, which we have in other cities, crime goes down. dream worthy. Yeah. To recruit these people. And then they're in, and they're gonna perpetuate that. And the data actually showed it's actually not a very good job. You actually don't make very much money being a criminal. It's like the median income for your average criminal is very, very low. Yeah. But they promote a lifestyle of wealth. So if you look at those cities, like San Francisco, crime's coming down, clearance rates are going up. And I would say as soon as we can get somewhere like San Francisco to a hundred percent clearance rate, which we have in other cities, crime goes down. A hundred percent clearance rate is a hundred percent solved. Yes. And it's doable. We have it in major cities. Cobb County would be one, which is the second largest county. Cobb County has a hundred percent. Yep. If you commit violence in Cobb County, yes, you will get arrested. And that's across what sample size? That's the second largest county in Georgia. So let's call it a couple million people, almost a million people. So a decent number of violent crimes. Yeah. Yeah. And but it's going down every year. Sure. So you look at places like that. Because you really get caught. Yeah. And so we have this new concept that we've developed called safe city. And we'll go into a town and say, look, this is the platform you need to solve all the crime in your city. It's your choice. It tends to be about twenty bucks a citizen a year. Yeah. It's your choice. And what's fun to watch is we find these mayors with really strong backbones and they're, I want to be a safe city. There's just this awesome town, Greenville, Mississippi. You've probably never heard of it. Twenty-six thousand people. They have our drones. They have our cameras. They have our AI. They have everything we do and they are lighting it up. And kudos to the mayor in chief, every crime they solve, yes, they're on the five o'clock news. What? So these are highly effective cities. What effect does this, what happens to the criminals? Does it shift it to other localities and need to—it's disease eradication. You ultimately need to do enough to blanket it, to snuff it out because if just one municipality does it, it'll shift to a local municipality. Does it actually within that municipality, people just go to something non-criminal? I'm curious, what are the effects of one municipality getting really good? There's two phases. The first phase, you're spot on—people just change cities. It's like when San Francisco started adopting Flock, Oakland crime went up. So then Oakland needed to adopt Flock. Yes. And now with a couple of false starts, now that that's fully going, they will have the same. But first is the shift. Yes. And then you're right. The majority of criminals, let's call it 99% of criminals, are not evil people. They're not—evil is a random act of violence and that is exceptionally rare. It's very rare. It's all opportunism. And you and I were fortunate enough to be born in a family, in a social construct that we could build great companies, but not everyone had that chance. And some people get pushed in the wrong direction and that's what we have to stop. It's like, as a business, we don't—while we're proud of the impact, making a million arrests, it's actually quite disheartening, because that means a million people will not have to go through the criminal justice system, which doesn't work that well. And there's a million victims. It's bad in every single way. It's also crazy expensive as a society to jail that many people. It's a double negative bottom line where it's costly and prohibitive that they'll probably never reenter society. So we're much more focused on the preventative mechanisms of how do you convince someone this is not a good lifestyle? This is not a long-term plan. And eventually what you will see is they will go get jobs. These are functional members of society. They can be functional members. We should push them in that direction. What kind of crime is on the increase? [SPEAKER_00] So I'll tell you one that's pretty fascinating. If you look in the enterprise community, organized resale crime in stores was really hot during COVID and right after COVID. And that's why you saw CVS lock their stuff up. You saw places like In-N-Out leave Oakland. This was a huge problem. And it's still—for someone like Walmart, I think they reported just shy of a billion dollars of theft last year. So it was a lot of money. Yeah. And their peers aren't doing dramatically better now. Yeah. Flock customers are doing really well. Yeah. And Walmart on neophytes at this stuff—they have a loss prevention program. Yeah. We'll get there with Walmart. But you look at some of our partners, like Lowe's—their shrink has gone down order of magnitude. It's not exactly a problem anymore. Yeah. Yeah. But where the criminals have moved is to the distribution facilities. It's safer and bigger loads. And probably the most sophisticated one that I've heard of is an Eastern European group. They went and bought a legal, well-running freight broker. They now own this asset and they bid on all these projects, low bid on all these projects, show up with real paperwork, fill up a twenty-foot with product, drive away, dissolve the company. Seven million dollars in a single day. That's pretty good business. Yeah. That's very sophisticated though. Yeah. That's harder to solve. That's much harder to solve. Because every car, phone—everything will be disposable, used in that. Everything's going to leave the country as fast as possible and just show up on a street somewhere. Yeah. And then the other interesting challenge is you have to unpack—this is a little bit complicated—who's liable. Mm-hmm. [SPEAKER_00] So as soon as the product goes into a store, that retailer is liable for the theft. It hits their bottom line. For a lot of these companies, they negotiate it such that there is insurance coverage from a different broker that owns that asset until final delivery. And so it's not super clear who actually cares. Everything's going to leave the country as fast as possible and just show up on a street somewhere. Yeah. And then the other interesting challenge is, you have to unpack this, which is a little bit complicated—who's liable. Mm-hmm. So as soon as the product goes into a store, that retailer is liable for the theft. Like it hits their bottom line. For a lot of these companies, they negotiate it such that there is insurance coverage from a different broker that owns that asset until final delivery. And so it's not super clear who actually cares. Well, the insurer cares. Insurer cares eventually. Yeah. But when you talk about the scale of what's called tens of billions of dollars, hundreds of billions of dollars of product being moved, you're like, oh, we lost a couple hundred million. I see. Yeah, yeah. We'll be fine. We have insurance. Yeah, yeah. It will catch up eventually, but that's probably the most interesting type of crime we're tracking is the theft on the distribution. So we have a lot of partners on the distribution side where we're now deploying our product to try to prevent this from becoming an epidemic. Yes. But it's much harder to solve. Like it's a real company. Yes. Yes. Like— I want to ask you more about this, but I'm going to get you another Guinness. This is a good segue into your corporate business. Because again, people associate you with selling to municipalities, but obviously you sell a lot to corporates as well. Yeah. [SPEAKER_00] It's a big part of our business. [SPEAKER_00] Can you say how big? [SPEAKER_00] North of a hundred million of ARR. [SPEAKER_00] Oh, okay. [SPEAKER_00] So like it's real. [SPEAKER_00] Yeah. [SPEAKER_00] Oh, I'm going to go all in. Oh, sorry. [SPEAKER_01] Well, you had some dregs left. I'll get across. That's my fault. Yeah. Take a real one. [SPEAKER_01] You want to just go full up and you'll get more of a head that way. And it's perfectly correct. Oh, it is? [SPEAKER_01] You can trust it. Yeah. Okay. So the corporate business. [SPEAKER_00] Yeah. [SPEAKER_00] North of a hundred million of ARR, probably fastest growing segment. There's some wild stories. [SPEAKER_00] So we help businesses solve two problems. How do you keep your employees safe and how do you keep your assets or your stuff safe? So it's funny because we have a Fortune Five company that's a customer. And you probably don't want to talk about specifics, but we should just imagine big box stores like Home Depot, Walmart, those. [SPEAKER_01] Yeah. [SPEAKER_01] Like we have this Fortune Five company that's a customer. Yeah. [SPEAKER_01] And they spend like a hundred thousand dollars a year because they have like three locations in the country. That's it. [SPEAKER_01] Yeah. [SPEAKER_01] They have like three really big campuses. [SPEAKER_01] So they're actually like, we don't proxy towards necessarily market cap or revenue. [SPEAKER_01] Yeah. [SPEAKER_01] So someone like a Dollar General is a way better prospect for us because Dollar General has 7,000 stores. [SPEAKER_01] Mm. [SPEAKER_01] Yeah. You want Subway. [SPEAKER_01] Yeah. [SPEAKER_01] You want Subway is a good example. [SPEAKER_01] Yeah. [SPEAKER_00] So we tend to focus on retail, healthcare, and logistics. [SPEAKER_00] Yeah. [SPEAKER_00] They tend to have big physical footprints. [SPEAKER_01] Yeah. A lot of employees. Yeah. And a lot of challenges. Or both challenges. And is their main challenge theft? Like that's what they're worried about? That they want to prevent stolen cars coming to do stuff? [SPEAKER_00] I'd say employees. I'd say three years ago when we started the business unit, it was assets. It was like, oh my gosh, coming out of COVID, everyone's stealing everything. [SPEAKER_00] It is much more shifted now to keeping employees safe. [SPEAKER_00] Mm-hmm. So you think about some of these businesses, they might terminate half a million people a year, quarter million people a year. Mm-hmm. It takes one angry employee to come back. And so in our system, you can have an automated notification with the HR system that when employees is terminated, they're added to a localized hot list. Yeah. If that employee ever comes back on campus, it's not illegal. Yeah. But notify security is why people have security teams. Like, don't let them in the building. Yeah. So it's about moving that layer of safety farther out. Yes. The other example is we do quite a bit of work in executive protection. Mm-hmm. So I'll give you a good example. I think like a Fortune 2000 CEO. [SPEAKER_01] Yep. Our stuff's deployed at her house. We also deploy at corporate. [SPEAKER_00] Mm-hmm. It's not illegal, but it's quite weird if the same vehicle on the same day goes to both locations. Mm-hmm. [SPEAKER_00] And so for like— That is not that person. [SPEAKER_01] Yeah, it's not that person or their EP team. And so we're thinking keeping people safe is the number one thing. And then the assets is like it's good, but worst case, you just raise prices, which is not good. But we had this crazy case with one of our healthcare partners where this group— We also deploy at corporate. [SPEAKER_00] Mm-hmm. [SPEAKER_01] It's not illegal, but it's quite weird if the same vehicle on the same day goes to both locations. [SPEAKER_01] Mm-hmm. And so for- That is not that person. Yeah, it's not that person or their EP team. And so we're, I think keeping people safe is the number one thing. And then the assets is good, but worst case, you just raise prices, which is not good. But we had this crazy case with one of our healthcare partners where this group, pretty smart actually, would show up to the hospital dressed in a certain company's uniform. And be like, oh, the robotic surgical arm needs to be repaired. Can you help me grab it? [SPEAKER_00] And some clinic, clinical surgeons like, oh yeah, let me show you where it is. Don't worry, no worries, John. Walk in there. [SPEAKER_01] This is a multimillion dollar piece of equipment. And they literally walk out with it. This happened in- Like some Thomas Crown affair kind of stuff. But it's, you're a physician. You're not thinking, oh, is John actually working at this company? Is the product, I think I used it yesterday. [SPEAKER_01] You're like, oh yeah, we got bad. [SPEAKER_01] That sounds right. [SPEAKER_00] It's super expensive product. [SPEAKER_00] So this is an example to your conversation of where the business gets interesting. We then connected that healthcare provider with federal authorities. So this is not a low, this isn't going to be a local authority to solve this kind of crime. It's a federal crime at this point. But they were taking the product, exporting it and selling it in a different country for clinical work. So we got that one's pretty interesting. There's that's an asset one where actually the healthcare system is like- [SPEAKER_00] This is 20 something million dollars of products stolen. [SPEAKER_00] That's a problem. [SPEAKER_00] Yeah. Yeah. Yeah. Is your business going international? Which countries is this best suited to? Is this a universally applicable product? Do those differences in law enforcement agency structure make it- [SPEAKER_00] I'm just curious. I mean, we're dabbling, but I think payments is probably very global. Everyone wants to process payments. I think- Yes. There's a lot of local nuance. Yeah. I think for us, maybe our ambitions aren't big enough, but when I look at the domestic opportunity, we should be able to get to five, 10, 15 billion of revenue in America. And we're not there. Yes. And so it's the difference of, to your point on the nuance and payments, it's probably comparable to the nuance of working with local government, but then you overlay hardware and that just gets maybe two steps too difficult for my stomach today. Got it. Today. [SPEAKER_01] Yeah. [SPEAKER_01] But there's, I mean, we get inbound. I got, I saw an email this morning from an Australian police department. It's, we'd love to do a demo. And it's why not just do, I mean, I agree that there's a lot of nuance. Is there some aspect of your tech? You've put a lot of work into the cameras, vehicle recognition, stuff like that? [SPEAKER_00] Because I know, again, from painful experience, that localization is never easy and never as easy as you think. Yeah. Here's- [SPEAKER_01] But maybe it's easy. Well, so here's the argument. [SPEAKER_00] So we pursued one really big deal last year in Mexico. [SPEAKER_00] Mm-hmm. [SPEAKER_00] And we had support from one of our investors. We should go after this. And they had connections to the Mexican government. And so we got all the way to the finish line. And it was us versus Hikvision. [SPEAKER_01] Hikvision is a Chinese camera manufacturer, arguably a subsidiary of the CCP. And we were almost 10 times the price. And it came down to, is the Department of Homeland Security going to subsidize this for the Mexican government? Because this, we know their list price is way more than this. [SPEAKER_00] It's very clear this is being subsidized for the Mexican government to make this purchase decision, in which case they will most likely be giving away real time feeds to another government. And we didn't win that deal. And I think that if you look at, there's a great book on this topic. If you look at what China was able to do in Africa with their infrastructure deployments on connectivity. [SPEAKER_00] And they own those countries. [SPEAKER_00] Uh-huh. [SPEAKER_00] What's the book, Cuddy Crasby? I'll find it for you. Okay. [SPEAKER_01] Well, we'll pop it in. I'll find the book. But the book pretty much shows that one of the smartest moves that China did was going to these developing countries and saying, we will give you 5G. Mm-hmm. Really low cost. We'll bond it for a hundred years. So we're not giving away for free, but guess what? Now Chinese government has access to your pipes. And maybe that's not scary for some countries. For me, I'd be a little afraid. And that was our pitch to the Mexican government: don't look at just cost. Look at the sovereignty of the data and who has access. And look, we'll domicile this data in your country. We won't domicile it in America. And they were like, sorry, it's too expensive. And we've seen that we've done a couple of other projects like that, not just picking on Mexico, but other countries where we're not competitive with China, not because our products aren't better. I think they're much better, but we're not being subsidized by the federal government. But presumably NATO countries, you know, Australia should be better. And that was our pitch to the Mexican government: you don't look at just cost. Look at the sovereignty of the data and who has access, and look, we'll domicile this data in your country. We won't domicile it in America. And they were like, sorry, it's too expensive. And we've seen that we've done a couple of other projects like that, not just picking on Mexico, but other countries where we're not competitive with China, not because our products aren't better—I think they're much better—but we're not being subsidized by the federal government. But presumably NATO countries, you know, Australia should be better. But no, I can—we should go walk around a strip mall and I could probably point out 80% of the cameras are Chinese manufactured. [SPEAKER_00] And your average business owner is like, yeah, I got it for 15 bucks on Amazon. [SPEAKER_00] And I've got to know—that's that story on the vacuum cleaners. It's like, you should care about where your data is stored and who's storing it. And that kind of stuff matters to me, but not everyone. [SPEAKER_00] That makes sense. As we've learned from Flock Safety, fighting crime is most effective with network data on your side. The same is true for payment fraud. Most businesses only see their own transactions, which makes it very hard to spot patterns and prevent future attacks. But Stripe Radar tackles fraud using the power of the Stripe network. Our machine learning models train on hundreds of billions of data points across the $2 trillion of payments we see on the Stripe network each year. When new fraud patterns emerge, our models can quickly learn and start blocking similar attacks immediately. So if you want to fight fraud like Flock Safety fights crime, check out Stripe Radar. As I think about your competitive landscape in the U.S. and companies that sell to law enforcement, I think about Axon, which people would associate with making the body cameras, but they make tasers too, but they make lots of other stuff. And then Motorola Solutions, which is the radios and the stuff that gets up in the cars and things like that. Are you three the main three players? Are there others I should be thinking about? And how will this play out—presumably you guys compete more over time? Yeah. So I remember in 2020, trying to raise our Series B, and every investor came to the same conclusion: six, three strikes are out. Strike one: you're based in Atlanta. Now, post-COVID, that's become less of a problem, but strike one, you're in Atlanta. Strike two, you're doing hardware. But that's really bad. Hardware is really expensive. Now it's the only business with terminal value. I would argue that AI is not going to replace cameras or dig holes. And I mean, a third of our employees dig holes for a living. AI is a long ways away from replacing that. [SPEAKER_00] Sorry, what are they digging the holes for? Because most of the time you want a camera where you don't have any infrastructure, we actually show up and dig the hole, we trench it, we pour concrete, put our pole up. I might be—okay, so it's on your own pole. I seem to just mount it on an existing pole. I think I should pull this data. I would not be surprised if I'm the largest general contractor in America. We pulled 77 permits a day last year. And if you've ever built a house, you know how difficult it is to permit something. 77 permits a day—crazy scale. Yes. AI is not going to replace that. It's a very safe asset. But yeah, so when we were trying to raise that Series B, the third strike was—second strike was hardware, third strike was, and you're trying to sell to the government? The last company to go public was Axon. They went public in 2005, which would've been 15 years prior. And in the VC speak, it's like, well, if you can't get big enough to go public, you're not worth investing in. It's like, well, crap. And so luckily, Gary Tan shared my beliefs: safety should be a public right. It shouldn't be a privilege. It should be a right if you live in America. So he did our Series B, which I think is only Series B's ever done. And he was right. I was right. So it's the three of us now. It's Motorola, who's the biggest at about a $90 billion market cap, 120 years old, invented the radio, still has—I think they have 80% market share globally of landmass radio. Just crazy scale. It's funny how durable some of these businesses are. Garmin and others—like you just start doing GPS, you start doing radio, and you stay doing radio. Own it. Yeah. Own it. And to Motorola's credit, they've driven a ton of innovation on the radio itself. Similar to Garmin, which you'd think would have been crushed, but they've been so creative in creating verticals—aviation and all that stuff. And they built an awesome product. Sports. And no one would debate whether Motorola's radios work really well, and when you need them—which would be like a natural disaster—yeah, they work especially well. And that's pretty compelling when your job is to respond to natural disasters. Totally. Yeah. So you have Motorola. Every single thing we do, we compete with Motorola. So that's fun. They're big. Second one would be Axon. You know, like I said, public in 2005, about a $40 billion market cap. Where'd they come out of? I understand where Motorola came out of. Rick Smith, the founder, graduated Harvard. Sick of fun from that. He plays it off. He's a very smart guy. Graduated Harvard, found this taser company. It wasn't called taser at the time. So they started with tasers. Found those, found the IP, the product, and then tried to commercialize it. And if you love a good founding story, it's a good one where they almost went out of business. His dad mortgaged the house. He mortgaged the house. They went public because they couldn't finance it. I think they went out at like a $50 million valuation. sick of fun from that. He plays it off. He's like a very smart guy. Graduated Harvard, found this taser company. It wasn't called taser at the time. So they started with tasers. Yeah. Found that, found the IP, the product and then tried to commercialize it. And if you love a good founding story, it's a good one where almost went out of business. His dad mortgaged the house. He mortgaged the house. Yeah. Went public because they couldn't finance it. I think they went out at like a $50 million market cap. This is like when people went public much earlier. And just has done a really good job of growing the business in the public markets. And taser is a brand. It's like Kleenex. They own, they started as taser. They started as taser and rebranded to axon in 2012 or 2015. Yeah. And got into body cams via acquisition. So they bought a company that had just won the contract for the New York Police Department to do body cams. So bought that. They have a dash camera. And they recently launched a competitive product with me. Yeah. So now we compete. Everything we do, we compete with axon too. Just fun. So it's just a Mexican standoff. Every single city, every single city. And there was interesting because your question was also in the future. There's this really interesting phenomena happening now where because Flock's been somewhat successful, VCs have poured in. And when I used to call a police department seven years ago, now you have a bunch of competitors. No one would know. You could literally just walk into a police department, come and meet the chief. They're like, oh, that's great. Now chiefs are like, great. Seventeen different people calling me for the exact same thing. Now they don't compete with us, thankfully. But when you think about trying to deploy AI to monitor body cam footage, there's seven different companies with VC backing doing that. Mm-hmm. There's not, it's not a big enough market. Yeah. I think your annual report was great, by the way. You all are at what, 1% of GDP or something probably. Okay. I'm in 60 to 70% of the cities that matter. Yes. Yes. There's just not enough space for seven competitors. The market's not big enough and we're not creating new cities. A new business is created every single day. I think you tend to see structurally in these smaller—I mean, it's a large market in total, but where there's a finite universe of buyers—the distributional advantages are very powerful. I think that's what you're saying. I think so. And so I think what we'll see is I see a new VC backed company every day and I'm like, there's just all these things going out of business. So there's just going to be consolidation. And so you see, I think Motorola has done 40 acquisitions in the last two years. Axon did five last year. We did one last year. I just think you're going to see everyone in the space, a ton of consolidation. Because once someone builds a good product, you go great. I already have a sales force. I have the customer base. Yes. We'll just pick you up. [SPEAKER_00] Yeah. So I had no idea about you talking about where the tech goes. I'd no idea about two things actually I learned here. One is that you're doing real time analysis of 911 calls. Yeah. And so is that being fed to an LLM basically, or are 911 calls now scored by an LLM? [SPEAKER_00] So the way I think about it is we are trying to build an orchestration layer for a city's safety. The majority of police departments are understaffed. I think the worst I've heard recently, I was at a higher ed, a college campus, a large college campus, in a football school, they're 40% staffed. Could you imagine if tomorrow you woke up and Stripe had 40% staffed? It'd be tough. You would figure it out. Yeah. But a lot of things that you would deem core today would just stop. Yes. Yes. And so that's how most of our customers operate, which is not sustainable. Yes. And so we view our job as being that force multiplier, or I like to think about this orchestration layer where every manual thing that's done by a human should be automated. Now, the difference in public safety versus maybe payments is I think you want humans at the start and finish still. It's like if I call 911, I still want a person to pick up. And those dispatchers are incredibly well-trained. They're very well-trained. They're very calm. Now where I think it gets valuable is if there's a mass event, AI is way better because if you have a surge of demand and you go from normally one call a minute to 10 calls a minute, AI is better than a busy tone. Yeah. Yeah. And that makes sense. And then I think about for us, we call it amplified intelligence. When that 911 call comes in, the LLM is able to pick up the call, is able to determine what are the characteristics. Can I build an investigation? Can I pull this up so that if you're the detective, whereas historically you walk in, you're like, all right, I'm going to get the call transcript. I'm going to look up my record system. I'm going to do a bunch of analysis. It's the equivalent of having, whether you use something like Glean or another product, you're going to do a lot of the hard work. So that as a sales rep, you show up and you're like, got it. Yeah. Yep. And so we do that for investigators. So they show up, they get delivered a case and a lot of the busy work has been done for them so they can use the human part of their job. I'm grabbing all the data that needs this. All the different data, let's go do this. We solved one of the cooler cases we've solved was an armored truck—like Brinks, they move money around. It's one of the best, it's called a jugging case. It's very popular in Texas where you follow these armored trucks and you typically have a shooter on a nearby building. And when the person walks out, the shooter shoots them. And so we do that for investigators. So they show up, they get delivered a case and a lot of the busy work has been done for them so they can use the human part of their job. I'm grabbing all the data that needs this. All the different data, let's go do this. We solved one of the cooler cases we've solved was an armored truck, like Brinks, they move money around. It's one of the best, it's called a jugging case. It's [SPEAKER_00] very popular in Texas where you follow these armored trucks and you typically have a shooter on a nearby building. And when the person walks out, the shooter shoots them, other guy runs in, grabs all the money and runs away. It's a very, obviously sad, but it's a very, very profitable thing. So we built an agent that tracks armored cars. And so at all times, it is literally saying, okay, here's an armored truck. If we ever see other vehicles tracking this car, flag them automatically. Now it's not illegal, sure. But it is enough that if you're a city like Houston who has a jugging problem, you want to get a subscription to like, let me know whenever you see someone doing that, because I want to know. Yeah. I want to get a step ahead. [SPEAKER_00] Yes. So there's always types of crimes that you can say, okay, this is helping officers not do something new. It is just doing things that when you're at 50%, 40% staffing, sure, 100%, you'd have been doing this yourself. You'd be checking the cars, you'd be in Flock, you'd be running searches, but you can't do that anymore. Yeah. What you're describing is again, having this data to be able to do anomaly detection just allows for a new kind of police work that otherwise just wouldn't have gotten done. No, it's people's lives, you know? And then the other thing I hadn't realized you guys were doing is the drone assistance where, again, this sounds to me like many police departments have a helicopter and then for very serious crimes, you know, they will task it. [SPEAKER_00] Yeah. But that's expensive, very limited resource. And so I think what you're doing is allowing for some manner of air support to just be much more cost effective and available to more officers. That's right. Yeah. I mean, I think it's another example where there's just a lot of tasks we ask law enforcement officers to conduct that a drone could do faster, more effectively and cheaper. [SPEAKER_00] Yes. And so if it's a hit and run, great, send the drone. I was working with a town in Tennessee. It's a pretty good city. Their average response time to 911 calls seven and a half minutes. Their drone from us gets there in 68 seconds. Just a better quality of service. The incremental cost is less than the cost of one single officer. It's really nice when you see technology deliver both a 10x better product at a dramatically lower cost. Yeah. That's how it's supposed to work. [SPEAKER_01] And it's working for them. Where are the drones, what kind of task or intervention are the drones best suited for? Yeah. I mean, the two most, there's three primary use cases. The first would be vehicular pursuits. It's one of the most dangerous things cities conduct is high speed pursuits. Sure. [SPEAKER_01] Typically it's not the suspect that dies. It's some random person or something. Yeah. [SPEAKER_00] So for most of our towns that have adopted our drone program, they end pursuits. They don't pursue anymore. Send the drone. Oh wow. Just send the drone. Yeah. Way better. Yeah. [SPEAKER_00] It's way safer. So that's a big one. So you don't have a police car running at 80 miles an hour down a residential street. [SPEAKER_01] No, you just have a drone four feet up in the air, quietly, safely, waiting for the car to pull into a gas station, pulled into their home, pull in somewhere safe, get to a red light. [SPEAKER_01] And then meanwhile, that video feed's being broadcasted to the entire police department. [SPEAKER_01] It's great. You know, John's over here. Yeah. [SPEAKER_01] Block them in. You know, every pursuit goes to GTA level five immediately. Yes. Yeah. If you're smart. Yeah. So that's a big one. Second is 911 calls. So what's been interesting is that we'll send the drone first. It takes something like Elk Grove up in Northern California. They've got a bunch of our drones flying 911 calls. [SPEAKER_01] Where's Elk Grove? [SPEAKER_01] It's a suburb of Sacramento. Oh, okay. About 75,000 people. So I say suburb, it's a pretty big town. [SPEAKER_00] So like, they'll dispatch for 911. Majority of the calls actually never need a human to show up. [SPEAKER_00] And the example I'd give you is a fist fight. So you call 911. And then what happens is historically seven minutes later, someone shows up. Guess what? Yeah. They're no longer fighting. But now we've dispatched this officer. He's in the area. Maybe I'll grab a Gatorade, walk around, check it out. 30 minutes later, we've wasted a bunch of time. Yeah. You send the drone. In best case, you see the guys fighting and you're like, great, I'm going to keep an eye on them. Yeah. And allow the officer to do his job. Or if there's no fight anymore. Yeah. You dismiss the call. Mm-hmm. [SPEAKER_00] And so you actually decrease the response time for situations you really do need to go to by removing the junk in the system. Yeah. [SPEAKER_00] That's the second one. And the third one is search and rescues. Not every city has a helicopter. Yeah. And as soon as I do, it's a very expensive proposition. Sure. And so sadly, people go missing all the time. You know, pop up the drone, throw on thermals. Yeah. [SPEAKER_00] Sure it's at night, and you find the person. Actually, I hadn't thought of that, but drone plus thermal camera is very transformative for SAR. No, yeah. We had an interesting case in a cold state right now. He's flying our drone. There was a sorry, a lot of my cases involve homicides. I gotta find a better topic than homicides at some point. I have a better topic for you in a second. And so sadly, people go missing all the time, and you can pop up the drone, throw on thermals. Yeah. [SPEAKER_00] Sure it's at night, and you find the person. Actually, I hadn't thought of that, but drone plus thermal camera is very transformative for SAR. No, yeah. We had an interesting case in a cold state right now. He's flying our drone. There was a—sorry, a lot of my cases involve homicides. I gotta find a better topic than homicides at some point. I have a better topic for you in a second. Okay, great. So there's this 911 call—car on the side of the street. Launch the drone, throw in thermals. Actually see where the person went. [SPEAKER_00] Like sensitive enough to see the heat pattern, like there's— Oh yeah. There's in snow. [SPEAKER_00] I want to find the guy, I want to find himself and everything. But it's just interesting to your point, I think we're still very early on in the use case exploration. [SPEAKER_00] Yeah. And I think it's the type of technology that until it's fully proliferated, which give it two or three more years, I think we'll continue to find more ways to augment how we respond. Because I think the last example I'll give you is we typically launch the drone for all first responders. So it's not just law enforcement, it's fire, it's EMS. [SPEAKER_00] Like the whole community gets advantage of it. Yeah. Yeah. [SPEAKER_00] Okay. My fun example, because I agree a lot of the crimes are quite heavy topics. [SPEAKER_00] Yeah. So I feel one of the most satisfying genres of YouTube video to watch is people who laser aircraft, but they are mistakenly lasering a police helicopter. So this is an insane crime that happens. Wait, why do they do that? Okay. So there's this insane crime that happens. Isn't that bad? It's very dangerous. It's very bad. It's very dangerous. Yeah. [SPEAKER_01] But people, to your point, just maybe people going mad during COVID and being cooped up, people just for fun laser aircraft. It's very dangerous. It's dangerous for anyone's eyes, shining a laser into them. But a pilot who is flying a plane full of people at that moment, it's especially bad. But it's a real problem that happened. You listen to ATC recordings all the time, airliner going into LAX, getting lasered by someone on the ground. And so people buy these lasers on Amazon. They're very powerful lasers. Exactly. They're very powerful. And they're just lasering the cockpits of aircraft. But occasionally what happens is they're lasering an aircraft, but it turns out that aircraft is the police helicopter. They're just like, gotcha. And they got the thermal and they're just like—and so you get to watch the whole thing unfold. There's a bunch of these on YouTube. You see the squad cars coming up and it's, yeah. That's odd. Check that out. [SPEAKER_01] But it's such an odd crime and yes, it's very satisfying to see them caught in real time. [SPEAKER_01] Yes. That's a really weird thing. The other thing, because I know you like aviation stuff—yeah. We're seeing more and more police helicopters have to turn off ADS-B as well. Because criminals have the same data that you have. Yeah. And so most of the police helicopters actually fly without ADS-B now, which is a whole challenge. Yeah. Sure. From a separation point of view. Yeah. Okay. I have so many more things to go into or jumping around, but I like this. How's the business evolved? So you're now around 500 million in ARR selling to both law enforcement agencies and corporates. Just, have there been interesting changes in how you monetize? Is it just a question of scaling up? [SPEAKER_01] Yeah. I mean, I'd say the biggest challenge is two or three years ago, we were single product, single customer. We had our neighborhood business. It was growing 20, 30% year over year, but it was operating. [SPEAKER_00] Yeah. And law enforcement was growing over there really fast. We had one product and then maybe made a mistake. I know RJ from Rivian was here. And somebody probably built too many products for too many customers really quickly. And in hardware, that's really expensive. Hardware tends to follow this J curve of huge capex investment upfront to get the thing going, and then you monetize and it actually winds up being—and there's very significant scale economies at very high orders of magnitude. [SPEAKER_00] Yes. And so we went from one camera that tracks cars to a camera that's focused for people, a drone, this trailer, multiple customer segments. And that's really hard. Yeah. So looking back on it, you think you went too broad too quickly. Yeah. I would have— So did you discontinue products and stuff? No, we just— Stuck with them. [SPEAKER_00] ...muscled through it. [SPEAKER_00] Yeah. [SPEAKER_00] Still muscling through it. We've done the race of adding products. We were like, we cannot do any new hardware products this year. Yeah. [SPEAKER_00] We need to take a year or two off of hardware products. We can debate software products, because there's no incremental burn or cash outlay for it. But we know what the J curve looks like. We saw it in the core business. And the core business now is profitable, which is great. We'll generate free cash flow, hundreds of millions of dollars of operating cash flow this year. But those new businesses are effectively like Flock five years ago. [SPEAKER_01] Yeah. [SPEAKER_01] Yeah. [SPEAKER_01] And we know how painful that is, but we were just like, oh, it'll be great. It'll be fine. Yes. Yes. And so I think that's been challenging for us is how do you balance from a product roadmap servicing two customers with just very different use cases? Yes. We saw it in the core business. And the core business now is profitable, which is great. We'll generate free cash flow, hundreds of millions of dollars of operating cash flow this year. But those new businesses are effectively like Flock five years ago. Yeah. And we know how painful that is, but we were just like, oh, it'll be great. It'll be fine. And so I think that's been challenging for us is how do you balance from a product roadmap servicing two customers with just very different use cases? Your average Amazon distribution facility is 30 acres, 50 acres. That's a neighborhood block. And then you've got San Francisco that's got hundreds of square miles. The problems are different. So that is probably the hardest thing that we're still trying to muscle through. And how do you organize your company to service these two different customers without having redundancies? [SPEAKER_00] I haven't figured that out. What have you learned other than don't make too many products? What have you learned by building hardware? Or what have you learned about building hardware? I think there's a couple of things that I would jump to. The first would be, I don't know how you guys think about forecasting demand. It's a full-time profession at Flock. And it typically needs to be 12 to 18 months out. And if you look at hardware companies that don't make it, that's actually where they fail. [SPEAKER_00] We ended up with it. I mean, our hardware business is a very small part of our overall business, but we wildly overproduced at one point and just sitting in a warehouse, like there's all my money. Exactly. Sitting in a warehouse. Now, luckily it's not going to go bad. It's not like bananas. It's not like we have a week to move this product. But it does go bad at some point. [SPEAKER_00] And I think I remember during YC many, many, many years ago, talking to Eric at Pebble about how it was ironic that in the best year ever of the company in terms of revenue is the year they went out of business. That's crazy. But they just overproduced in Q4. Even though it was still a record quarter, it just still wasn't enough. [SPEAKER_00] So I think that has been amplified by also our distribution process, which we're fully first party. So we not only design the stuff, build the stuff, we install the stuff. [SPEAKER_00] And so I have to have forecasting, not just at the product level, but at the geographic level. At least the general area. So I think forecasting has been pretty hard. And the second is every decision you make in hardware is millions of dollars at a minimum and often tens of millions of dollars. And so when you grow up in this Silicon Valley mindset of like, everything's a two way door. Bullshit. Hardware. Everything's a one way door. We're going to live with it for the next five, 10 years. And I don't know, you probably don't track this as much, but probably the dumbest financial mistake I've made in the last year is our supply chain team came to us like six months ago and they were like, solid state memory is getting really expensive. And we had this one part for our cameras and the price had gone up 4x in near time, which indicates that typically one much, much larger company placed a massive order. And so we've seen this time and time again where an Apple or a Sony or some consumer or Samsung will pick a part for a new product that's coming out in 12 months and the supply globally disappears. [SPEAKER_00] So you're feeling the AI data center build out in your supply chain. [SPEAKER_01] Yes. And so my supply chain leader was like, this is getting crazy. And I was like, well, who do we use it? I go use Sandisk. And so I'm looking at their stock and I'm like, should we be buying Sandisk stock? I was talking to my CFO. I was like, should we be buying Sandisk stock? I was like, their prices are going up 3x. It means that a lot of people are buying a lot of products. Now, of course the stock's up like 1200%. And I feel like an idiot for not following that conviction. But our BOM now, luckily it's a small part of our BOM. But we have a full team of people who all they do is mitigate global supply chain risk. Because parts just disappear. So just getting the products into the hands of customers as already specced is non-trivial. So what we wind up doing, which I think a lot of companies do, I'm not sure if we're special, but when we look at a BOM of a product, we'll risk purchase, not necessarily the whole thing, but the cheapest, highest risk things. We should have bought, and we did, we bought a ton of memory so that we didn't run out because we can't. Because parts just disappear. Okay. [SPEAKER_01] So just getting the products into the hands of customers as already specced is non-trivial. [SPEAKER_01] So what we wind up doing, which I think a lot of companies do, I'm not sure if we're special, but it's just that when we look at a bill of a product, we'll risk purchase, not necessarily the whole thing, but the cheapest, highest risk things. [SPEAKER_01] Like we should have bought, and we did, we bought a ton of memory so that we didn't run out because we can't. But I would have thought often these supply chain crunches come on the leading edge, where everyone's fighting over TSMC three nanometer node production capability. [SPEAKER_01] But the auto chips, with much larger gate sizes or larger nodes, are not as contended. Right. So we'll buy everything for the next three years. And then we go, oh crap, we've got to completely change that capacitor. But I'm just surprised you're competing with Apple for components. [SPEAKER_01] I would have thought their capacitors would be different. [SPEAKER_01] It's cheap, everything. Yeah. I mean, well, a capacitor is a capacitor. Yeah. [SPEAKER_01] But so it's actually the capacitor you want. [SPEAKER_01] Yeah. You have to have a supply chain to buy it. You have to have enough inventory with enough lead time. It is. [SPEAKER_00] Yeah. [SPEAKER_00] Not, and so what you wind up doing is early on, your designs are very simple. [SPEAKER_00] You buy everything from, say, Adafruit or whatever. [SPEAKER_00] You buy everything from easy places where you can buy 50 at a time. And then when you move to tens of thousands at a time. Yeah. You start having to have designs that have four different derivatives for every part. So your supply chain doesn't have to call engineering like, this part's out. They know these parts are all substitutes. [SPEAKER_00] You're describing the scale dis-economies of manufacturing, where it's easier to buy three of something than it is to buy 30,000. 100%. And I never would have thought we would need a team of people who all they do is spend money for a living. Just buy stuff. What's hard about operating the hardware? How do you keep the lenses clean on the cameras? And how do you, I don't know what the other is. It's on the one hand, we're some of the best weather forecasters. [SPEAKER_00] We keep track of every major storm. Yes. [SPEAKER_00] Storm, we need to be back up. Mm-hmm. [SPEAKER_01] So we do have a pretty cool, we call it our flight team. And there are technicians that only fly. Yeah. It's that big storm in New York and Boston, they were flying into the storm. We had surge demand to fix stuff. To be on site, when they get a call that something is down, go repair it. Yeah. Well, everything is everything. We have really good telemetry on the equipment. [SPEAKER_01] Yeah. So if a customer calls, something's gone. Yeah. We've really screwed up. You know, before the customer knows. And most of the maintenance at this point is fairly predictive. We know this mechanical part malfunctions after between 100 and 200,000 uses. So if you're in the area, it's ironic that the largest cost structure in replacing equipment is the driving. Yeah. Yeah. Sure. It's driving. [SPEAKER_01] And so if we think the part we need to replace it in six months. Yes. [SPEAKER_00] And we're nearby, it's cheaper just to replace it, refurb it, and get it back in the field. [SPEAKER_00] So we had to build a software company, a hardware company, and a field services business. Do you have parts that wear out? I would have thought the whole thing is fairly solid state. We, most of it's, well drones obviously fly. Sure. Different kettle of fish. [SPEAKER_01] But on the camera side, there's one part, which is the IR cut filter. [SPEAKER_01] So when we operate at night, we operate on infrared and you need a different filter, so that you don't have pink images during the day. [SPEAKER_01] Yeah. So that literally changes twice a day. [SPEAKER_01] Oh, something mechanically. Put a lens over it. I see. And after a couple of thousand uses. That is the one moving part. It's the one moving, and it is the only part that breaks. It's very frustrating. Why don't I just have two lenses? With two different image sensors too? Yeah. [SPEAKER_00] Boom. [SPEAKER_00] Okay. No good reason. Okay. Other than it would just be more expensive. Yeah. But yeah, that part's, I think a third of the company, digs holes, drives bucket trucks. Yeah, sure. Yeah, sure. Keeps track of all the inventory. But if you look at it, I didn't want to build that business. [SPEAKER_00] Yes. But early on in the company, there was this horrific case in Atlanta where a woman was just running in, our version of Mission Dolores or pick your nice park in the city. [SPEAKER_00] Random act of violence. There's cameras everywhere in the park. Yep. None of them were working. [SPEAKER_01] And the city got blasted appropriately for it. And they're like, well, but also, do we really want our police department being in charge of camera uptime? Yeah, yeah. [SPEAKER_00] Yes. But early on in the company, there was this horrific case in Atlanta where a woman was just running in our version of like Mission Dolores or pick your like nice park in the city. [SPEAKER_00] Random act of violence. [SPEAKER_01] There's cameras everywhere in the park. [SPEAKER_01] Yep. [SPEAKER_01] None of them were working. And the city got blasted appropriately for it. And they're like, well, but also, do we really want our police department being in charge of camera uptime? Yeah, yeah. That's a dumb idea. Yeah. We should pay a company, I thought in this case, to just make sure the stuff always works. Yes. So it's not my favorite part of the business in that sense. It's just a lot of stress. [SPEAKER_00] It's very operationally intense, but I think it's valuable to our customers. Yeah. [SPEAKER_00] How do you think about the right? You talked about cameras in the park. Many movies center on this idea of universal surveillance, in the Bourne Identity or something. They have cameras on absolutely everything. Or I guess the Bourne Supremacy, I think is more the Waterloo station scene. And same with lots of other things, just how do you create the right guardrails once you move off roads and into parks and public spaces and kind of creating access controls around that? Yeah. The cop out answer is I don't want to be in charge of deciding that. [SPEAKER_01] Mm-hmm. [SPEAKER_01] Thankfully we have elected officials who we vote to make that decision. [SPEAKER_01] Or what do you think a sensible place for them to land is? I think it's way higher than we have now. For me, at least, for every crime that occurs that doesn't get solved means we didn't have enough cameras. That's to me the easiest rubric. Mm-hmm. Now to your question though, it's a question of where they are, who has access to them. Mm-hmm. And I think it's one of the few cases where the disparity between maybe my knowledge and your knowledge of how the technology works and how an electrical works is pretty big. [SPEAKER_00] And their dreams of how it might work versus actually how it works. It's much less sophisticated than they think or dream up. It's just a camera. [SPEAKER_00] Mm-hmm. [SPEAKER_00] So for me, at least, we should have an abundance of cameras and have an incredibly restrictive controls of how and when they're used. And the example I'd give you is today, everything in Flock. You can generally do. There's data retention where we protect how long something is stored. So for live video, it's typically seven days. For LPR data, it's typically 30 days. You can go longer or shorter if a democratically elected body votes on it. [SPEAKER_00] [SPEAKER_00] But I would challenge why not do more cameras and have a warrant restriction? Mm-hmm. Why not do 30 days of LPR data, but if you have a warrant, you have a year? Yeah. You need fewer cameras. And so I do think there are some nuanced ways to do it. And thankfully, we have a really good government affairs team that is lobbying for that kind of legislation to say there's a way for us to both be safe and maintain civil liberties and it needs to be legislated though. Yes. I can't. Those ideas are not in line with what my customers want. Mm-hmm. And my law enforcement customers, they just want to go catch bad guys. Yeah. They want to follow the constitution. Yeah. Catch bad guys. But that nuance in the middle of what is societally acceptable today really belongs in your elected officials to make that decision. Mm-hmm. [SPEAKER_01] So it can change. And so we push them to be like, let's legislate this now before it becomes a problem. [SPEAKER_01] Where do you think has passed sensible rules? [SPEAKER_01] Sensible. I think Virginia's bill last year was pretty good. [SPEAKER_01] Mm-hmm. [SPEAKER_01] It defined. It did a few things well. And one thing I don't agree with. What it did well is it defined a modest data retention period of 21 days. I think that's fine. I prefer 30, but it's fine. It wasn't. I think the ACLU was lobbying for three minutes. It's a little tough. It's hard to swallow. I think seven, 14, 20 something days is enough. There's a trade off there. [SPEAKER_01] They mandated formal auditing, which I think is great. Not enough of our customers audit themselves on a regular basis. We can build software to make that easier, but we need to be pushed to do that. It was customers don't want it. They need to be told to do it. [SPEAKER_01] So I think that was good. It also validated that this could only be used for criminal investigations, which I think is really good. While that's obvious, it's helpful to write it in law. I think the only thing that I disagree with is they did say effectively there's no participation with the federal government. [SPEAKER_01] Hmm. [SPEAKER_01] I think that's their choice. Yeah. I think it's their choice. Yeah. And that's the beauty of the country is Virginia should do what feels right for Virginia. Yeah. Yeah. But I worry about the types of cases that you don't want to read about on the news that tend to get solved by the U.S. Marshals, the DEA, the ATF, the FBI. [SPEAKER_00] I think the only thing that I disagree with is they did say, effectively, there's no participation with the federal government. Hmm. I think that's just their choice. Yeah. I think it's their choice. Yeah. And that's the beauty of the country is Virginia should do what feels right for Virginia. Yeah. Yeah. [SPEAKER_01] But I worry about the types of cases that you don't want to read about on the news that tend to get solved by the U.S. Marshals, the DEA, the ATF, the FBI. And they can't use our technology in Virginia. Yeah. I said, I live in Georgia, so thankfully it doesn't really impact me. Yes. But as a business, I'm happy they passed some legislation. Yeah. New Mexico passed a similar bill this year. California has a similar bill. Hmm. Well, I think a couple other states have. I think the worst type of bill is not whether it's 14 days or 30 days of intervention. To me, the worst bill is an unenforceable bill. So you can imagine a bill that's like, this product cannot be used for possession of marijuana. Who's going to enforce it? Yeah, yeah, yeah. And it's like, you might believe that. Yeah. And that's great. But someone has to enforce this. [SPEAKER_00] And actually what's going to happen is no one's going to enforce it now. [SPEAKER_00] And that's, I think, really bad law in those cases. [SPEAKER_00] Yeah. [SPEAKER_00] Yeah. That makes sense. [SPEAKER_00] I'm curious what your view is on police department procurement. [SPEAKER_00] What do they do? [SPEAKER_00] What do they buy? [SPEAKER_00] Not enough of? [SPEAKER_00] What do they buy too much of? [SPEAKER_00] They don't feel like they're swimming in procurement dollars. [SPEAKER_00] But yeah, I'm curious. Yeah. I mean, the thing they buy too much of is, and not to pick on Motorola, things that only matter in the 0.001% case. Mm-hmm. So it's like, why don't you just use cell phones? Well, in a natural design. And it's like, got it. Okay. How often do you look at a landmass radio contract and it's in a cost somewhere like San Francisco County, $200 million. [SPEAKER_01] You're talking about that kind of money? [SPEAKER_01] On a TCV basis. [SPEAKER_01] Oh yeah. Wow. I mean, I think Motorola's a really big company. Sure. Yeah. That's how. [SPEAKER_00] Yeah. [SPEAKER_00] It says you don't get there. And you go, well, I get it. If there's an earthquake and every single cell tower goes down, law enforcement definitely needs a way to communicate. [SPEAKER_00] Man, is that really the only way? Yeah. Could you guys just have your own tower? [SPEAKER_00] There's got to be something. Yes. But you look into it. Is this a your margin is my opportunity situation for you guys with radios? Maybe because law enforcement's unique in this case in which they really like that they own the infrastructure. [SPEAKER_00] They own that bandwidth. [SPEAKER_01] Ah. And so they can do whatever they want with it. [SPEAKER_00] Yeah. I don't think they do anything interesting with it, but they can. Yeah. Versus if they're riding on Verizon or AT&T, they have no control over that. No, but why don't you guys just have the exact same products and have a good radio in the spectrum. We probably should. Yeah. [SPEAKER_01] But we have a lot of things. That's my, you know. [SPEAKER_00] I'll take it. A VC and a board. [SPEAKER_00] I'll take it. [SPEAKER_00] Yeah. [SPEAKER_00] It's like, hey, you should go to an $80 billion company that's been in business for 130 years. [SPEAKER_01] I mean, I guess you did it in payments and it worked out pretty well. [SPEAKER_00] But yeah, so I think that part is really crazy. At least in the business world, I buy for my majority case. Yes. Yes. And I deal with the ramifications of the edge case or build around it. Yeah. [SPEAKER_01] And they do that. [SPEAKER_00] I think procurement is exceptionally slow and exceptionally laborious. Everything goes to RFP. [SPEAKER_01] Yep. But the RFP is written for one vendor. So all it does is wind up taking an extra year. Yep. Six months. [SPEAKER_01] That's like, I get why RFPs exist. Yeah. But they're not actually RFPs. I've never seen an RFP that's not written for one vendor. Mm-hmm. I'm sure it exists somewhere. Yeah. Yeah. [SPEAKER_01] I haven't seen it. [SPEAKER_01] I haven't seen it. But what I think they do well is one of the things that I think the government figured out is maybe you need to have an RFP for a $200 million contract. What about a $10,000 contract? Great. So they do have spend levels where if you're a police chief, you can go spend $25,000 or $50,000 and not have to go through the entire process. But no, it's tough. [SPEAKER_01] I would not wish upon anyone selling to local government. I haven't seen it. But what I think they do well is one of the things that I think the government did figure out is maybe you need to have an RFP for a $200 million contract. What about a $10,000 contract? Great. So they do have spin levels where if you're a police chief, you can go spend $25,000 or a $50,000 and not have to go through the entire process. But no, it's tough. I would not wish upon anyone selling to local government. It's more negatives than positives in all ways. And again, that procurement process has evolved for a reason, and to protect against certain other failure modes. But yeah. Well, I mean, you think about it in business and I know you use Stripe. I'm sure you have six competitors. [SPEAKER_00] I don't know. But I know you. Someone shouldn't buy Stripe. [SPEAKER_00] Mm-hmm. [SPEAKER_01] That in the business world is considered very normal. Yeah. [SPEAKER_01] In the government world, that is called illegal. Yeah. [SPEAKER_01] Which is really interesting. Yeah. [SPEAKER_01] What we have. [SPEAKER_00] Again, it's evolved for a reason. You know, the rules are written in blood. Well, no. And then you have plenty of cases where it's gone sideways. Yeah. But it is just interesting, dynamic, for so many things that we take for granted as normal business practice are definitively illegal when procuring with government. [SPEAKER_00] How do you guys use Stripe? I mean, a lot of our customers, a lot of our private sector customers, pay either via credit card or check. [SPEAKER_00] Ah, okay. [SPEAKER_00] With a lot of checks. Okay. [SPEAKER_01] So for the public sector stuff, that'll generally be via a torturous RFP process and PO and something like that. But if you're a private sector. And then, but even, I mean, when we don't want to be in the check deposit business. Sure. And you guys. So you use Stripe for the check functionality. Because no one knows about our check functionality that Stripe can accept checks for you. Am I allowed to talk about it? No, no, no, no, no, no, no. [SPEAKER_01] Because we're bad at marketing. [SPEAKER_00] Oh, I was just, I was just— [SPEAKER_00] Not because it's a secret. [SPEAKER_00] No, yeah, no. [SPEAKER_00] It's, we don't want to be in that business. Yes. It's a remote deposit box or whatever it's called. [SPEAKER_00] Yeah, yeah, yeah. [SPEAKER_00] But yeah, it's great. We can give you an address that you can give to your customers and they can mail checks to it. And we will turn it into digital money. And the fact that a bunch of atoms and an envelope going through the postal system were involved, you can forget about those details. [SPEAKER_00] Not a single customer of ours pays via ACH to either check or credit card. And we do a lot of checks. I'd probably say 80%, 90% are checks, maybe higher. [SPEAKER_00] You're one of the few tech companies to mostly use Stripe for checks. Uh-huh. That's really funny. I love that. [SPEAKER_00] You were talking about police departments maybe being over fixated on the 0.1%, 0.1% cases. Does that apply to a common critique that you hear of police department procurement is the militarization of police departments. And you know, what we really need is a Bear Cat, you know, for this town of 20,000 people, which is an armored personnel carrier. Oh, yeah. And it's a $3 million vehicle. And it's, why couldn't we just get an F-150? Yeah, yeah. [SPEAKER_00] So do you think that applies also to the shiny stuff? [SPEAKER_00] Oh, yeah. I mean, you look at early on when we were building the company, we'd get the question of, well, can it track, can your license plate reader work on a car going 175 miles an hour? [SPEAKER_00] And I was, probably not. I've never driven that fast. I'd have to rent a runway to test this. [SPEAKER_00] Yes. [SPEAKER_00] They're, it's really important. [SPEAKER_00] I'm, uh, really? How often does it happen? They're, in a high-speed pursuit, people drive very fast. And I'm, in high-speed pursuit, you know who they are. We were criticized and had to build a product. Until we got to 120, 150, it was a major blocker to sales. Really? [SPEAKER_00] Huh. I mean, it's, we built a camera that we tested on roads that we drove on. So we'd get up to 80 or 90 and it worked fine. But we had to eventually rent an amateur racing track. Yes. And just drove around in circles at 120 miles. We emailed the employees and we're, who owns a car that goes really fast? And that was actually kind of funny, because a lot of people were— What cars are you used to test this? We had these, there's some fast cars. [SPEAKER_01] Put it at Teslas, Rivians, some other nicer cars. Yep. Drive really fast. [SPEAKER_01] And that was a fun day. Because I put the cameras up and do it. But that kind of stuff— And did the cameras work out of the box or did you have to tune the model performance? Who owns a car that goes really fast? [SPEAKER_00] And that was actually funny, because a lot of people were like— [SPEAKER_00] What cars are you used to test this? [SPEAKER_00] We had these. There's some fast cars. Put it at Teslas, Rivians, some other nicer cars. Yep. Drive really fast. And that was a fun day because I put the cameras up and do it. But that stuff— [SPEAKER_01] And did the cameras work out of the box or did you have to tune the model performance? Yeah. Okay. So it just worked. [SPEAKER_01] Yeah. The only place where we had to make one modification, which is interesting, we deploy our radar. So on really busy roads, where our angle of incident is particularly tight, we can't shoot super far down to shoot at a sharp angle. Yeah. We have a radar attachment that we tilt backwards to notify the cars on the way, get ready. Which helps, but that's a very far edge case because the camera doesn't actually— I think you prime the camera essentially? Yes. [SPEAKER_00] To get ready for a car coming. Huh. [SPEAKER_01] I'm sorry. What— [SPEAKER_00] Because the camera is offline. Oh. [SPEAKER_01] Unless there's a vehicle. [SPEAKER_01] I see. [SPEAKER_00] So you boot it up. [SPEAKER_00] And that's a power saving measure? Yep. Okay. The most expensive thing we do is take a picture. Yeah. The second most expensive thing we do is send stuff to the cloud. Third is just being a computer turned on. Yep. And so it's similar to your iPhone turning your screen off. Ah, okay. So we added the button to take a photo right away. The continuously running radar is very low power? [SPEAKER_00] It's negligible. I see. [SPEAKER_00] Oh, that's cool. Yeah, that was a fun one. We were talking about hardware previously, but what's building your own drones been like? A lot of fun. It's— Sounds fun. No, it's fun, but it's—I've kids. I know you have a kid, it's really fun to build a product that your kids understand. Yeah. And so we drive around Atlanta and my son will count the cameras from home to school, or we're going to the airport or the park. [SPEAKER_00] And I love that he can actually understand what dad does. Yes. I'm not sure if you've taught your son how to use a console. I'm screwed on this access. Yeah. We process the world's payments. And so when you show him a drone, he's like, oh, this is cool. [SPEAKER_01] And he has a little miniature drone. [SPEAKER_01] Well, also you don't need drones, but you do drones to catch bad guys. Like that's very compelling from a very early age. [SPEAKER_01] Yeah. [SPEAKER_01] Like you get—yeah, to be clear, he'll watch Paw Patrol and be like, that's what dad builds. [SPEAKER_01] That's the helicopter. Well, we don't put any people in it. But I think what's been fun is we made a hypothesis that if you studied planes, I think the most interesting plane military-wise is the Warthog because whereas traditionally you built a plane, you're like, right. One thing. Yeah. Like what kind of missiles can we add? And they were like, no, no, let's design the best missile. It's very precise, very big. And then we'll figure out how to fly it. [SPEAKER_00] And so our thesis was, well, we're really good at cameras. A drone is really just a camera that flies. Let's build the best payload and then figure out how to fly it. And so if I showed you, I could show you the payload the next time here in Atlanta, or we could fly one out here. It's the coolest camera ever. It's huge. It's like this big. And it's got four different—four different image sensors, maybe six different optical lenses. [SPEAKER_00] Like we can zoom, we can read a license plate almost a mile away, crazy specs, great thermal. Then we're going to get it to fly. So I don't know, I was an electrical engineer. One of my co-founders was a mechanical engineer. It's fun to build things that fly. So it's like, all right, we have payload, we have this airframe. So we have aeronautical engineers now. It's been fun to grow the engineering team. Yes. [SPEAKER_01] And an imaging team. You think about the dock that it lives in. It's effectively a commercial grade HVAC system. Like the drone lands, it needs to be cold, it needs to be hot. Yeah, yeah. [SPEAKER_00] It has to charge. [SPEAKER_00] If you know anything about lithium ion, lithium ion doesn't like to be too hot or too cold. So you've got to keep that well conditioned. It's huge compressor. It's this massive thing that opens and closes. And if it's snowing, if it's frozen, all of these engineering problems. Yes. [SPEAKER_01] And that's the fun part of this stuff. [SPEAKER_01] Yes, it does. [SPEAKER_01] Everything else is selling is good, but building stuff is fun. [SPEAKER_01] How many drones do you have out there in the world? [SPEAKER_01] Oh, we don't disclose that one. [SPEAKER_00] Okay. [SPEAKER_01] So you've got to keep that well conditioned. It's this huge compressor. It's a massive thing that opens and closes. And if it's snowing, if it's frozen, all of these engineering problems. [SPEAKER_01] Yes. And that's the fun part of this stuff. Yes, it does. Everything else is selling is good, but building stuff is fun. How many drones do you have out there in the world? [SPEAKER_01] Oh, we don't disclose that one. [SPEAKER_00] Okay. But a decent number. [SPEAKER_00] Yeah, yeah, yeah. It's hundreds of cities that are flying. Yeah, are flying drones. Yeah. Yeah. That's cool. [SPEAKER_00] Yeah. [SPEAKER_00] It's funny. [SPEAKER_00] When you talk about the A-10 Warthog, you're reminding me of the Boyd book, which by Robert Coram, which I only read recently, but it's one of those Silicon Valley canon things. Everyone talks about it and everyone talks about him in the context of his OODA loop. Observe, orient, decide, act. But I think that's actually overrated. The main reason Boyd is interesting is helping the Pentagon procure better planes. I'm just reminded that with the Warthog and also your description of needing to run at 170 miles an hour. [SPEAKER_00] Because he came into a Pentagon that had a bunch of bad planes because all the generals were obsessed with specs. Yes. [SPEAKER_01] And they wanted a high top speed and they really judge planes on specs. [SPEAKER_01] And the fighter pilot joke is that there are only two throttle settings in a dogfight: maximum full military power or throttles idle. [SPEAKER_00] Those are the only two energy states that you're in and what matters is maneuverability and the ability to add energy or lose energy quickly. So he was involved in basically all of the good planes that were produced, including the A-10 Warthog, because he got them out of the mindset of just speeds and feeds. Well, and that's for us the spec we track is time on scene. Yeah. And so one of the reasons why we care so much about payload is if you have a payload that can see really far away, you don't have to fly there. So actually you get there faster virtually, which is what, if this was a drone that was carrying a payload like a zip line or something else, actually physically being there matters. But for us, it's just about time on virtual scene. Yes. So that's what we measure ourselves to. That's why we fly high because physics allows you to see farther. Yep. That's why we have this huge payload. [SPEAKER_00] So you don't have to actually fly there. [SPEAKER_00] And then you don't have to fly as fast, which means you can conserve battery life, which means you're in the air longer. All of these designs were around that use case versus you know, I'm sure ZipLine went through a whole separate use case of what's the max payload and all that. So how many drones does a city the size of San Francisco need? 12. [SPEAKER_00] Okay. So a very small number. [SPEAKER_00] Our average drone can cover a 30 square mile radius and get there within under a minute. [SPEAKER_00] And thankfully, knock on wood, there actually aren't that many 911 calls that merit a response. Yeah. So we look at it both ways. [SPEAKER_00] We look at it in terms of geography and then 911 density. [SPEAKER_00] In more rural parts, you need less drones because there's less call for service. [SPEAKER_00] And in more dense urban areas, you need more drones, mostly from a volume of service. [SPEAKER_00] Yeah. But even in our most dense customers, it's pretty rare that they fly two drones at once. Yeah. [SPEAKER_01] It happens, but our busiest drone is being flown 90 hours a week. [SPEAKER_01] That's a lot of flight time. [SPEAKER_01] And sorry, do you dispatch the drone when it's needed from its charging dock or is the idea that it's out there flying already and you just task it? Yeah. [SPEAKER_01] There's it lives in the dock. [SPEAKER_01] Yeah. [SPEAKER_01] There is some debate of whether a drone should be in the air at all times. Hmm. Does that actually save you meaningful time? [SPEAKER_01] Being in the air? [SPEAKER_01] Yeah. [SPEAKER_01] I would save a lot of time. [SPEAKER_01] Oh really? [SPEAKER_01] Yeah. [SPEAKER_01] But look at the Carpenter case in Baltimore and they had an airplane with a very powerful camera 24 hours a day. And that was deemed an unwarranted search. And so it got killed. [SPEAKER_01] Hmm. [SPEAKER_01] And so we're very conscious. [SPEAKER_01] We have another part of our business that is interesting now at scale. [SPEAKER_00] We have a full team of constitutional attorneys. [SPEAKER_00] Yeah. [SPEAKER_00] And I'm sure you have a regulatory team that when you want to build something, they're like, let's check it before we ship. Yes. We have a constitutional team. Cool idea. [SPEAKER_00] Let's actually make sure this doesn't violate the constitution. Look up the fourth amendment here real quick. Let's just double check this thing. And so when you look at the drone, we believe, and there hasn't been tested in court, but these are smart people. [SPEAKER_00] They're like, we just, it's unclear how that would end in court. Yeah. [SPEAKER_01] But if you call 911, there is a reason to fly the drone. Ah. If there is a gunshot, if there is gunshot detection, if there is a stolen car, that is a reason to dispatch versus just flying around looking for stuff. That's not unconstitutional, but we would not push that as a use case. And so when you look at the drone, we believe, and there hasn't been tested in court, but these are smart people. [SPEAKER_00] They're like, look, we just, it's unclear how that would end in court. Yeah. But if you call 911, there is a reason to fly the drone. Ah. [SPEAKER_01] If there is a gunshot, if there is gunshot detection, if there is a stolen car, that is a reason to dispatch versus just flying around looking for stuff. It's not unconstitutional, but we would not push that as a use case. A lot of this precedent, as new technologies come along, people reason by analogy—cars sometimes, your house, but somewhat different. Isn't a drone flying around just like a police cruiser on its patrol? So the, and I'm not an attorney. Yeah. [SPEAKER_01] Neither am I. Never stop the ass. The other analogy that would be the butterfly effect, which is when things are much, much cheaper and much, much easier, a historical precedent gets thrown away. [SPEAKER_01] Mm. And so you take the helicopter example, you could say, oh, well, helicopters fly sometimes. Yeah, but helicopters are so expensive. It's not practical to have 24/7 aerial coverage. With a drone, it's not impractical. Yeah. It's the same reason why when we launch our drone, we want to go from the launch location to the end location. The cameras point the horizon the whole time. We don't want to look in your backyard. [SPEAKER_01] Mm. [SPEAKER_01] That's our point of view of where the law should be. Yes. Yes. [SPEAKER_00] So we'll build a product for that. [SPEAKER_00] Got it. [SPEAKER_00] And then if the operator wants to tilt down, that's their control. But as a default, we're fine. [SPEAKER_00] That's very interesting. [SPEAKER_00] Last question: you guys have grown with cameras out there in cities, now getting into drones, building the software OS to help law enforcement agencies and others synthesize all the information they have. What comes next? What future product ideas are you playing with? Where do you want to go? So I think about it. We talked about this earlier. Failure for Flock is prison population goes up. It's actually really bad. We look at the products today, which are very much focused in the middle of a crime. The crime has already happened and therefore we should solve it. And that's really good. I think we're definitely not done, but we've done a lot of work in that category. I get pretty interested in expanding that and going, well, what about—what can we be doing from a product perspective to prevent crime from happening? And that actually doesn't necessarily look like software. It's one of the interesting things that we started last year. We call it our Thriving Cities Fund. It's probably an analogy similar to your Stripe Press, which is—it's never going to be the core of your business, but you feel really good that it's a part of your business. And so when we go in places like Greenville, Mississippi, we also commit to deploy capital as growth partners to those businesses. Because if we want to convince that 16-year-old to not be a criminal, there does need to be jobs—jobs that a 16-year-old can get. And so we deploy capital in restaurants, nail salons, pick your business that a 16-year-old can work out easily. And we want more of those to exist. Last year, I think we were at 21% IRR. [SPEAKER_00] So it's not a bad business. It's not like Flock stock's done a lot better than 21%. But we've, I feel really strongly that we could deploy hundreds of millions, if not billions of dollars of capital in the cities that also choose to be safe. I don't want to deploy capital in a place that doesn't want to be safe. Yes. But for that, I want to do more there. And then I think to our conversation on the other half, the majority of the crime we solve is not violent. It's nonviolent. And today the discrepancy for a juvenile, non-juvenile, you still wind up in some type of penitentiary or prison system. [SPEAKER_00] I think that's crazy. [SPEAKER_00] All the data shows that as soon as you wind up in prison, you're going to get violent and you're going to come back. And so I would articulate there as an opportunity—I don't know yet what it is—to say, oh, hold on, hold on, hold on. If this was an opportunistic criminal, is there a product with a capital P, because it might not be software, it might be hardware, software, I don't know, that allows that person to have a second chance. [SPEAKER_01] And in a way that is not going to increase their likelihood of doing it again, because that's bad. But prison can't be the answer. It just doesn't work. And the whole concept of prison will never work. [SPEAKER_01] There are some incredibly well-run prisons with really well-intentioned wardens doing the best of their ability. But the concept of putting a bunch of violent people together is by default flawed. And so I question, what could Flock be doing to say, I want to prevent kids from becoming criminals? And if you do wind up on that path, how do I get you back on track as fast as possible? We're a for-profit business, so I'm not looking to be a nonprofit. But I think there is something there. Talking about millions and millions of people who really need—it's actually in our best interest as a society to get them back in and productive. And I want to do both of those. So fewer crimes, fewer people in prisons. Yeah. [SPEAKER_01] Yeah. [SPEAKER_01] That's the end goal. [SPEAKER_01] I want to prevent kids from becoming criminals. [SPEAKER_01] And if you do wind up on that path, how do I get you back on track as fast as possible? And we're a for-profit business, so I'm not looking to be a nonprofit. But I think there is something there. Talking about millions and millions of people who really need it—it's actually in our best interest as a society to get them back in and productive. And I want to do both of those. So fewer crimes, fewer people in prisons. That's the end goal. That's good. Thank you. Thank you. [SPEAKER_00] It was fun. [SPEAKER_01] It was awesome. [SPEAKER_00] Yeah. Thank you. money for a living. Just buy stuff. What's hard about operating the hardware? Like how do you keep the lenses clean on the cameras? And just how do you, I don't know what the other. It's, it's like a, on the one hand, you know, we're some of the best weather forecasters. You know, it's like we keep track of every major storm. Yes. It's like storm, like we, we need to be back up. Mm-hmm. So we do like, we have a pretty cool, we call it our flight team. And there are technicians that only fly. Yeah. It's like that big storm in New York and Boston, like they were flying in to the storm. Like we had surge demand to fix stuff. To be on site to, when they get a call that something is down, go repair it. Yeah. Well, so everything's everything. We have really good telemetry on the equipment. Yeah. So like if a customer calls, something's gone. Yeah. Like we've really screwed up. You know before the customer knows. And most of the maintenance at this point is fairly predictive. Like we know this mechanical part malfunctions after between 100 and 200,000 uses. So like if you're in the area, it's ironic that the, the largest cost structure in replacing equipment is the driving. Yeah. Yeah. Sure. It's driving. And so like, if we think the part we need to replace it in six months. Yes. And we're nearby, it's cheaper just to replace it, refurb it, and get it back in the field. So that part's been like, like we had to build a software company, a hardware company, and a field services business. Do you have parts that wear out? I would've thought the whole thing is fairly solid state. We, most of it's, well drones obviously fly. Sure. Different kettle of fish. Um, but on the camera side, um, there's one part, which is the IR cut filter. So when we operate at night, uh, we operate on infrared and you need a different filter, so that you don't have pink images during the day. Yeah. So that literally changes twice a day. Oh, like something mechanically. Put a lens over it. I see. And after a couple of thousand uses. That is the one moving part. Is the one moving, and it is the only part that breaks. It's very frustrating. How do I just have two lenses? Uh, with two different image sensors too? Yeah. Bomb. Okay. No good, like no, no good reason. Okay. Other than it would just be more expensive. Yeah. But yeah, that part's like, I think a third of the company, like I said, digs holes, drives bucket trucks. Yeah, sure. Yeah, sure. Keeps track of all the kind of inventory. But if you look at it, you know, I didn't want to build that business. Yes. Um, but early on in the company, um, there was this horrific case in Atlanta where a woman was just running in, you know, our version of like Mission Dolores or pick your like nice park in the city. Random act of violence. There's cameras everywhere in the park. Yep. None of them were working. And the city got blasted appropriately for it. And they're like, well, but also like, do we really want our police department being in charge of like camera uptime? Yeah, yeah. That's like, that's a dumb idea. Yeah. We should like pay a company, I thought in this case, to just like make sure the stuff always works. Yes. Um, so it's not the, you know, my favorite part of the business in that sense of like, it's just, it's a lot of stress. It's very operationally intense, but I think it's valuable to our customers. Yeah. How do you think about the right, um, you talked about cameras in the park, you know, many movies, um, center on this idea of, um, universal surveillance, you know, in the, the born identity or something, you know, they have cameras on absolutely everything, or I guess the born supremacy, I think is more the, um, the waterloo station scene. And, um, same with lots of other things, just how do you create the right guardrails once you move off roads and into parks and public spaces and kind of creating access controls around that? Yeah. Um, the cop out answer is like, I don't want to be in charge of deciding that. Mm-hmm . Thankfully we have elected officials who we vote to make that decision. Or what do you think a sensible place for them to land is? I think it's way higher than we have now. Like, I think that for me, at least, for every crime that occurs that doesn't get solved means we didn't have enough cameras. Um, like that, that's to me the easiest rubric. Mm-hmm . Now I think to your, to your question though, it's a question of where they are, who has access to them. Mm-hmm . And I think it's one of the few cases where, you know, the disparity between, uh, maybe my knowledge and your knowledge of how the technology works and how an electrical works is like, it's pretty big. Um, and like their dreams of how it might work versus actually how it works. Like it's much less sophisticated than they think or dream up. Uh, it's just a camera. Mm-hmm . So for me, at least, we should have an abundance of cameras and have an incredibly restrictive controls of how and when they're used. And the example I'd give you is like today, everything in Flock just, you can, you can generally do. There's a, there's data retention where we protect, you know, how long something is stored. So for live video, it's typically seven days. For LPR data, it's typically 30 days. You can go longer or shorter if a democratically elected body votes on it. But like, I would challenge why not do more cameras and have a warrant restriction? Mm-hmm . Like why, why not do 30 days of LPR data, but if you have a warrant, you have a year. Yeah. Um, you need less cameras. And so I do think there are some nuanced ways to do it. And, you know, thankfully, uh, we have a really good government affairs team that is lobbying for that kind of legislation to say like, there's a way for us to both be safe and maintain civil liberties and it, it needs to be legislated though. Yes. Like I can't, um, those ideas are, are not in line with what my customers want. Mm-hmm . And my law enforcement customers, they just want to go catch bad guys. Yeah. They, they want to follow the constitution. Yeah. Catch bad guys. But that nuance in the middle of like, but what is societally acceptable today really belongs in your elected officials to make that decision. Mm-hmm . So as it can change. And so we push them to be like, let's legislate this now before it becomes a problem. Where do you think has passed sensible rules? Um, sensible. Um, I think Virginia's bill last year was pretty good. Mm-hmm . Um, it defined, it did a few things well. Um, and one thing I don't agree with, what it did well is it defined, uh, a modest data retention period of 21 days. I think that's fine. I like 30, but tomato, tomato, it's fine. It wasn't, I think the ACLU was lobbying for three minutes. It's a little tough. It's like hard to swallow. Uh, I think, you know, seven, 14, 20 something days is like enough. There's a trade off there. Um, they mandated, uh, formal auditing, which I think is great. Enough of our, not enough of our customers audit themselves on a regular basis. We can build software to make that easier, but we need to be pushed to do that. It was like, customers don't want it. Yeah. They need to be told to do it. So I think that was good. Um, it also validated that this could only be used for criminal investigations, which I think is really good. While that's, that's obvious, it's helpful to write it in law. I think the only thing that I disagree with is they did say, you know, effectively, there's no participation with the federal government. Hmm. I think that's just, it's their choice. Yeah. I think it's their choice. Yeah. Like that. And that's the beauty of the country is like, Virginia should do what feels right for Virginia. Yeah. Yeah. But I worry about the types of cases that you, you don't want to read about on the news that tend to get solved by the U.S. Marshals, the DEA, the ATF, the FBI. And like, they can't use our technology in Virginia. Yeah. Like I said, I live in Georgia, so thankfully it doesn't really impact me. Yes. But as a business, I'm like, ah, I don't know if that's right, but I'm more than anything, just happy they passed some legislation. Yeah. New Mexico passed a similar bill this year. California has a similar-ish bill. Hmm. Well, I think a couple other states have, I think the worst type of bill is actually not, you know, whether it's 14 days or 30 days of the intervention. To me, the worst bill is an unenforceable bill. So you can imagine a bill that's like, this product cannot be used for possession of marijuana. Like, who's going to enforce it? Yeah, yeah, yeah. And it's like, you might believe that. Yeah. And that's great. But someone has to enforce this. And actually what's going to happen is no one's going to enforce it now. And that's, I think, like really bad law in those cases. Yeah. Yeah. That makes sense. I'm curious what your view is on police department procurement. What do they do? What do they buy? Not enough of? What do they buy too much of? They don't feel like they're swimming in, you know, procurement dollars. But yeah, I'm curious. Yeah. I mean, the thing they buy too much of is, and not to pick on Motorola, things that only matter in the 0.001% case. Mm-hmm. So it's like, guys, why don't you just use like cell phones? Like, well, in a natural design. And it's like, got it. Okay. Like, how often, like, so you look at like a landmass radio contract and it's in a cost somewhere like San Francisco County, you know, $200 million. Like, I mean, like, it's like. You're talking about that kind of money? On a, on a TCV basis. Oh yeah. Wow. I mean, I mean, I think, uh, Murillo's a really big company. Sure. Yeah. That's how. Yeah. It says you don't get there. Uh, and you, and you go, well, I get it. Like if there's an earthquake and every single cell tower goes down, law enforcement definitely needs a way to communicate. Man, is that, is that really the only way? Yeah. Like, well, could you guys just like have your own tower? Like there's, there's gotta be something. Yes. But you look into it. Is this a, your margin is my opportunity situation for you guys with radios? Maybe because law enforcement's unique in this case in which like, they really also like that they own the infrastructure. Like they own that bandwidth. Ah. And so they can do whatever they want with it. Yeah. I don't think they do anything interesting with it, but they can. Yeah. Versus if they're riding on, on Verizon or AT&T, they have no control over that. No, but why don't you guys just have the exact same products like. And have a good radio in the spectrum. We probably should. Yeah. Um, but we got a lot of things. That's my, you know. I'll take it. Like a VC and a board. I'll take it. Yeah. It's like, hey, you should go to an $80 billion company that's been in business for 130 years. Like, I mean, I guess you did it in payments and it worked out pretty well. Um, but yeah, so, so I think like, uh, that part I think is really, really kind of crazy. At least like in the business world, I feel like I buy for my majority case. Yes. Yes. And I deal with the ramifications of the edge case or built around it. Yeah. And they, they do that. Uh, I think procurement is exceptionally slow and exceptionally laborious. Everything goes to RFP. Yep. But the RFP is written for one vendor. So all it does is wanting, wind up taking an extra year. Yep. Six months. That's like, that's, I get why RFPs exist. Yeah. But they're not actually RFPs. I've never seen an RFP that's not written for one vendor. Mm-hmm. Um, I'm sure it exists somewhere. Yeah. Yeah. I haven't seen it. I haven't seen it. Um, but what I think they do well is like one of the things that I think, uh, the government did figure out is maybe you need to have an RFP for a $200 million contract. What about a $10,000 contract? Great. So they do have spin levels where, you know, if you're like a police chief, you can go spend $25,000 or a $50,000 and like not have to go through the entire process. But no, it's tough. Like it's, I would not wish upon anyone selling to local government. It's more negatives than positives in all ways. Um, yeah. And again, that procurement process has evolved for a reason, uh, you know, and to protect against certain other failure modes. But yeah. Well, I mean, you think about it in business and like, I know you, we use Stripe. I'm sure you have like six competitors. I don't know. But like, I know you. Someone shouldn't like buy Stripe. Mm-hmm. That in the business world is considered very normal. Yeah. In the government world, that is called illegal. Yeah. Which is really, it's, it's really interesting. Yeah. Like what we have. Again, it's evolved for a reason. You know, the rules are written in blood. Um, well, no. And then like, you have plenty of cases where it's, you know, it's, it's gone sideways. Yeah. But it is just interesting, dynamic, like for so many things that we take for granted as normal business practice are definitively illegal when procuring with government. How do you guys use Stripe? Um, I mean, a lot of our customers, our, a lot of our private sector customers, uh, pay either via credit card or check. Ah, okay. With a lot of checks. Okay. So for the, um, uh, public sector stuff, that'll generally be via a torturous, you know, RFP process and PO and something like that. But if you're a private sector. And then, and then, but even, I mean, when we don't want to be in the check deposit business. Sure. And you guys. So you strike for the, um, check functionality. Because no one knows about our check functionality that Stripe can accept checks for you. Am I allowed to talk about it? No, no, no, no, no, no, no. Because we're bad at marketing. Oh, I was just, I was just like, oh. Not because it's a secret. No, yeah, no. It's like, we don't want to be in that business. Yes. Um, it's like, it's a remote deposit box or whatever it's called. Yeah, yeah, yeah. But yeah, it's great. We can give you an address that you can give to your customers and they can mail checks to it. And we will turn it into digital money. And the fact that a bunch of atoms and, you know, an envelope going through the postal system were involved, you can be, um, you can forget about those details. Not a single customer of ours pays via ACH to either check or credit card. And we do a lot of checks. I'd probably say 80%, 90% are checks, maybe higher. You're one of the few tech companies to mostly use Stripe for checks. Uh-huh. That's really funny. I love that. Um, you were talking about police departments maybe being, um, over fixated on kind of the 0.1%, uh, 0.1% cases. Does that apply to, you know, a common critique that you hear of police department procurement is the sort of militarization of police departments. And, you know, what we really need is a bear cast, you know, for this town of 20,000 people, which is like an armored personnel carrier. Oh, yeah. And it's like a $3 million vehicle. And it's like, why couldn't we just like get an F-150? Yeah, yeah. So do you think that applies also to kind of the shiny stuff? Oh, yeah. I mean, you look at like early on when we were building the company, we'd get the question of like, well, can it track, can your license plate reader work on a car going 175 miles an hour? And I was like, probably not. I've never driven that fast. I'd have to rent a runway to go like test this. Yes. They're like, it's really important. I'm like, uh, really? Like, how often does it happen? They're like, in a high-speed pursuit, people drive very fast. And I'm like, in high-speed pursuit, you know who they are. Like, we were criticized and had to build a product. Until we got to like 120, 150, it was a major blocker to sales. Really? Huh. I mean, it's like, we built a camera that, I mean, we tested it on roads that we drove on. So we'd get up to like 80 or 90 and it worked fine. But we had to eventually, we rented a, um, like, you know, an amateur racing track. Yes. And just drove around in circles at 120 miles. We had, we emailed the employees and we're like, who owns a car that goes really fast? And that was actually kind of funny, because a lot of people were like- That's what what cars are you used to test this? We had these, like, there's some fast cars. Put it at Teslas, Rivian's, some other nicer cars. Yep. Uh, drive really fast. Uh, and like, that was like a fun day. Because I put the cameras up and like, and do it. But that kind of stuff- And did the cameras work out of the box or did you have to tune the model performance? Yeah. Okay. So it just, it worked. Yeah. The only place where we had to make one modification, which is kind of interesting, we deploy our radar. So on really busy roads, where our angle of incident is particularly tight, I like, we can't shoot super far down to shoot at a sharp angle. Yeah. Um, we have a radar attachment, um, that we tilt backwards to notify like the cars on the way, like get ready. Um, which helps, but that's like a very like far edge case. Because the camera doesn't actually- I think you prime the camera essentially? Yes. To get ready for a car coming. Huh. Um, I'm sorry. What- Because the camera is offline. Oh. Unless there's a vehicle. I see. So you boot it up. And that's a power saving measure? Yep. Okay. The most expensive thing we do is like take a picture. Yeah. The second most expensive thing we do is send stuff to the cloud. Third is just like being a computer turned on. Yep. And so it's similar to your iPhone, you know, turning your screen off. Ah, okay. So we added the button, you know, to take a photo right away. The continuously running radar is very low power? Uh, it's negligible. I see. Oh, that's cool. Yeah, that was a fun one. We were talking about hardware previously, but, um, what's building your own drones been like? A lot of fun. Uh, it's- Sounds fun. No, it's fun, but it's like, like, um, you know, I've, I've, I've kids, I know you have a kid, it's like really fun to build a product that your kids understand. Yeah. And so we, we drive around Atlanta and my son will count the cameras from like home to school, you know, or we're going to like the airport or we'll go like to the park. And like, I love that he can actually like understand what dad does. Yes. Uh, I'm not sure if you've taught your son like how to use a console. I'm screwed on this access. Yeah. It's like, yeah, I got, yeah. We process the world's payments. Um, and so when you show him a drone, he's like, oh, this is so cool. And he has like a little miniature drone. Well, also you don't need to drones, but you do drones to catch bad guys. Like that's very compelling. From a very early age. Yeah. Like you get like, yeah, to be clear, like he'll watch Paw Patrol and be like, that's what dad builds. Like that's the, that's the helicopter. Like, well, we don't put any people in it. Um, but I think what's, what's been fun is we made a, uh, a hypothesis that, you know, if you studied, um, planes, I think the most interesting plane, military wise is the Warthog. Because whereas traditionally you built a plane, you're like, right. One thing. Yeah. Like what, what do we, what kind of missiles can we add? And they were like, no, no, let's design the best missile. It's like very precise, very big. And then we'll figure out how to fly it. And so our, our, our, our, our thesis was, well, we're really good at cameras. A drone is really just a camera that flies. Let's build the best payload and then figure out how to fly it. And so like, if I, if I showed you, I could show you the payload the next time here in Atlanta, or we could fly one out here. It's like the coolest camera ever. It's huge. It's like this big. Um, and it's got, you know, four different, uh, four different image sensors, maybe six, different optical lenses. Like we can zoom, we can read a license plate almost a mile away, like crazy specs, great thermal. Then we're going to get it to fly. Um, so like, I don't know, I was an electrical engineer. One of my co-founders was a mechanical engineer. It's fun to build things that fly. So it's like, all right, we have payload, we have this airframe. So we have aeronautical engineers now. Like it's been fun to grow the engineering team. Yes. Um, an imaging team, you think about the dock that it lives in. It's effectively a commercial grade HVAC system. Like the drone lands, it needs to be cold, it needs to be hot. Yeah, yeah. It has to charge. If you know anything about lithium ion, lithium ion doesn't like to be too hot or too cold. So you've got to keep that well conditioned. It's like huge compressor. It's this massive thing that opens and closes. And if it's snowing, if it's frozen, like all of these engineering problems. Yes. Um, and that's like, that's the fun part of this stuff. Yes, it does. Everything else is, you know, selling is good, but like building stuff is fun. How many drones do you have out there in the world? Oh, we don't, we don't disclose that one. Okay. But decent number. Yeah, yeah, yeah. It's, it's hundreds of cities that are flying. Yeah, are flying drones. Yeah. Yeah. That's cool. Yeah. It, it, it, it's funny. When you talk about the, um, the A-10 Warthog, you're reminding me of the, uh, the Boyd book, which, uh, by Robert Coram, which I only read recently, but it's like one of those kind of Silicon Valley canon. And everyone talks about it and everyone talks about him, uh, in the context of his OODA loop, you know, um, orient something, decide, act. Um, but I think that's actually kind of overrated. Uh, and actually the main reason Boyd is interesting is helping the Pentagon procure better planes. I'm just reminded that with the Warthog and also, you know, your description of needing to run at 170 miles an hour. Because basically he came into a Pentagon that had a bunch of bad planes because all the generals were just obsessed with specs. Yes. And they wanted, you know, a high top speed and like, they really judge planes on, uh, specs. And, um, actually, you know, the, the fighter pilot joke is that there are only two throttle settings in a dogfight. Uh, you know, maximum full military power or throttles idle. Uh, like those are the only two energy states that you're in and what matters is maneuverability and the ability to add energy or lose energy quickly. So anyway, he was involved in basically all of the good planes that were produced, including the A-10 Warthog, because he got them out of the mindset of just kind of speeds and feeds. Well, and that's like for us, the, the spec we track is like time on scene. Yeah. And so one of the reasons why we care so much about payload is like, if you have a payload that can see really far away, you don't have to fly there. So actually you get there faster virtually, which is what, like, if this was a drone that was carrying a payload, like a zip line or something else, like actually physically in there matters. But for us, it's just about time on virtual scene. Yes. So that's what we measure ourselves to. So that's why we fly high because like physics allows you to see farther. Yep. That's why we have this huge payload. So you don't have to actually fly there. And then you don't have to fly as fast, which means you can conserve battery life, which means you're in the air longer. Like all of these designs were around that use case versus like, you know, I'm sure ZipLine went through a whole separate use case of like, you know, what's the max payload and all that kind of stuff. So how many drones does a city the size of San Francisco need? 12. Okay. So a very small number. No, I mean, our average drone can cover a 30 square mile radius and get there within under a minute. And thankfully, you know, knock on wood, like there actually aren't that many 911 calls that merit of response. Yeah. So we look at it both ways. We look at it in terms of geography and then 911 density. So in, you know, more rural parts, you need less drones because there's less call for service. And then in more dense urban areas, you need more drones, mostly from a volume of service. Yeah. Um, but even in our most dense customers, like it's pretty rare that they fly two drones at once. Yeah. It happens, but it's like, I think our busiest drone is being flown, you know, 90 hours a week. That's like, that's a lot of flight time. And sorry, do you dispatch the drone when it's needed from its charging dock or is the idea that it's out there flying already and you just task it? Yeah. There's like, it lives in the dock. Yeah. Um, there is some, there's debate of whether a drone should be in the air at all times. Hmm. Does that actually save you meaningful time? Being in the air? Yeah. I would save a lot of time. Oh really? Yeah. But like you look at the carpenter case in Baltimore and they had a airplane with a very powerful camera, 24 hours a day. And that was deemed like a, um, unwarranted search. And so it got killed. Hmm. And so we're very conscious. Like we have a, uh, other part of our business that is kind of interesting now at scale. It's like, we have a full team of constitutional attorneys. Yeah. And I'm sure you have like a regulatory team that when you want to build something, they're like, let's check it before we ship. Yes. We have a constitutional team. It's like, cool idea. Let's actually make sure this doesn't violate the constitution. Look up the fourth amendment here real quick. Let's just like double check this thing. Um, and so when you look at the drone, like we believe, and there hasn't, this hasn't been tested in court, but these are smart people. They're like, look, we just, it's unclear how that would end in court. Yeah. But if you call 911, there is a reason to fly the drone. Ah. Um, if there is a gunshot, if there is like gunshot detection, if there is a stolen car, like that is a reason to dispatch versus just like flying around looking for stuff is not, it's not, it's not unconstitutional, but we would not push that as a use case. But sorry, like a lot of this, um, precedent, you know, uh, as new technologies come along, you know, people reason by analogy of like, you know, uh, cars sometimes, some hot like your house, but somewhat different, you know, whatever. Like, isn't a drone flying around just like a police cruiser on its patrol? So the, the, and I'm not, I'm not an attorney. Yeah. Neither am I. Never, never stop the ass. The other analogy that would be the butterfly effect, which is like, when things are much, much cheaper and much, much easier, a historical precedent gets thrown away. Mm. And so you take the helicopter example, you could say, oh, well, helicopters fly sometimes. Yeah, but helicopters are so expensive. It's not practical to have 24 seven, you know, aerial coverage. With a drone, it's not impractical. Yeah. Um, it's the same reason why like when we launch our drone, we want to go from like the launch location to the, you know, end location. The cameras point the horizon the whole time. We don't want to look in your backyard. Mm. Like our point of view of where the law should be. Yes. Yes. So we'll build a product for that. Got it. And then look at the, if the operator wants to tilt down, that's their control. But as a default, we're fine. That's very interesting. Last question, you know, so you guys have grown with cameras out there, uh, in cities, now getting into drones, uh, building the software OS to help law enforcement agencies and others kind of synthesize all the information they have. Just what comes next? What future product ideas are you playing with? Where do you want to go? So I think about it. Um, we talked about this earlier. Um, failure for flock is prison population goes up. It's actually like really bad. Um, and we look at, you know, the products today are very much focused in the middle of a crime. The crime has already happened and therefore we should solve it. And that's really good. And I think we're definitely not done, but we've, we've done a lot of work in that category. I get pretty interested in, in expanding that and going, well, what about, what can we be doing from a product perspective to prevent crime from happening? Um, and that actually doesn't necessarily look like software. It's like one of the interesting things that we started last year. So we call our thriving cities fund. It's probably an analogy similar to your, like Stripe Press, which is like, it's never going to be the core of your business, but like you feel really good that it's a part of your business. And so when we go in places like Greenville, Mississippi, we also commit to deploy capital as, as growth partners to those businesses. Because if we want to convince that 16 year old to not be a criminal, there does need to be jobs, jobs that like a 16 year old can get. And so we deploy capital in, you know, restaurants, nail salons, like pick your business that you can be 16 and work out easily. And like, we want more of those to exist. Um, you know, last year, I think we were at, you know, 21% IRR. So like, it's not a bad business. It's not like Fox stock's done a lot better than 21%. But like we've, I feel really strongly that we could deploy hundreds of millions, if not billions of dollars of capital in the cities that also choose to be safe. I don't want to go deploy capital in a place that doesn't want to be safe. Yes. But for that, so I'm like, I want to do more there. And then I think to our conversation on the, on the other half, you know, the majority of the crime we solve is not violent. It's nonviolent. And today the, the discrepancy for a juvenile, non juvenile, you still wind up in some type of, of penitentiary or prison system. I think that's crazy. Like all the data shows, as soon as you wind up in prison, you're going to get violent and you're going to come back. And so I would articulate there as an opportunity, don't know yet what it is to say, oh, hold on, hold on, hold on. If this was an opportunistic criminal, is there a product with a capital P, because it might not be software, it might be hardware, software, I don't know, that allows that person to have a second chance. And in a way that is not going to increase their likelihood of doing it again, like that's bad. But like prison can't be the answer. Like it just doesn't work. And the whole concept of prison will never work. Like, and there are some incredibly well-run prisons with really well-intentioned wardens doing the best of their ability. But the concept of putting a bunch of violent people together is like by default flawed. And so I question like, what could Flock be doing to say, I want to prevent kids from becoming criminals? And if you do wind up on that path, how do I get you back on track as fast as possible? And we're a for-profit business, so I'm not looking to be a nonprofit. But I think there is something there. I mean, talking about millions and millions of people who really need, like it's actually as a society in our best interest to get them back in and productive. And I want to do both of those. So fewer crimes, fewer people in prisons. Yeah. Yeah. That's the end goal. That's good. Thank you. Thank you. It was fun. It was awesome. Yeah. Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Haha Thank you.