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- [00:01]
A
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.
- [00:14]
B
Cheers. Likewise. Thanks for having me.
- [00:18]
A
Okay, so maybe start by describing how does the Flock product work?
- [00:24]
B
Yeah, maybe we go, we rewind, like, all the way back. Because it's evolved. So eight years ago, living in Atlanta, and there's a fun fact is if you're in a place like Atlanta or Memphis or pick a town in the southeast, if you just pull ten F150 door handles, some, let's call it, three out of ten will be unlocked. And, like, one out of ten will have a firearm and a glove box, which is, like, regardless of the firearm, your point of view on it. It's like, you should keep safe, and you should keep it in a safe, not in a glove box. That's just really bad. But that's what people do. And so if you're a gang member and you're trying to obtain a firearm, the easiest way is just to just drive into a neighborhood. Six kids, because they're kids, jump out. You start pulling door handles. You don't have anything breaking into the car. You're pulling door handles. So this happened in my neighborhood. Someone got a gun. Someone posts on next door, like, 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, like, fairly apathetic, like, hey, sorry, good luck. Like, we're not gonna. So to your Bosch thing. They're not gonna fingerprint the vehicle, like, no one's been hurt.
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A
Yeah. Yeah.
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B
And for most major cities, there's no
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A
stakeout happening for this.
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B
There's no stakeout. There's no, like, oh, we're gonna go do all this. Resources. For most major cities, if a human is not physically hurt, the crime goes just to the bottom of the list. And I found that really frustrating because this should be, like, really easy. Like, these people drove into our neighborhood. They stole a firearm. Like, we should. We should go after these people. And he was like, well, we don't have any information. Okay, what do you need? We need a license plate.
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A
Okay, great.
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B
So 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 going to go build this camera scout, just, like, track license plates. That's it. That's what the Atlanta Police department said, okay, great. So we built this thing. And if you ever come to Atlanta office, we still have the original camera, like on a pedestal that looks like garbage. 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 be able 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 would be called Ebola. Like, 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 like the. We were like, very proud of ourselves. This was not a business at the time project. And so the 5 o' clock news wanted to do the story. So I'm on the 5 o' clock news and the next morning, like, I had five emails from neighborhoods. And I think we might be the only company that for the first, let's call it 20 or 30, 40 million of ARR. Strictly driven off of 5 o' clock news. That was our only growth channel that
- [03:29]
A
actual media appearance didn't strike.
- [03:31]
B
And every time we solved a crime, we'd be like, hey, do you want to cover the story at five o' clock clock? And they'd be like, would love to. We'd love, we'd love talking about crime
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A
because this is local news. I mean, that's local news.
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B
We're not going to go to the New York Times. No one cares about like a stolen sofa. Yeah, yeah. Or like a stolen dog. Okay, that's interesting.
- [03:47]
A
Did you start with. Because I associate flock today with being plugged into the stolen car databases. But you started without that. Just looking up, just suspicious stuff.
- [03:58]
B
Yeah, Well, I mean, if you, if you think about it in the classic, I don't know who gets credit for it. You know, 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.
- [04:17]
A
Yes, yes.
- [04:18]
B
Not like you and me just put 20 bucks together and say, let's buy this thing on the street. So that felt really interesting. And then the other kind of interesting insight that we developed, which took time, is I. I imagine at Your house, you have a security system. You might have a gate to your house, you probably have a dog. You have all these things. Right. They do two things that actually are 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 realized is that every single security system was focused on the individual.
- [04:45]
A
Yes.
- [04:46]
B
But like, I think about my life in Atlanta. There was just a crazy random act of violence a couple years ago. And, like, my wife wouldn't run outside for a year, and I had nothing to do with us. It was like a mile away. And so the whole premise became that you had to build a safety system for a community.
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A
Yes.
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B
Because that's actually what you feel. I mean, you live in San Francisco, you get it. Like, even if you've never been the victim, if crime is up, it's really bad. So it was all neighborhoods for the first three or four years of the business.
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A
So give me the stats on Flock today. Just how many cameras out there prime stopped, because again, and maybe just describe the product as it exists today.
- [05:22]
B
As it exists today. So now it's a much more sophisticated product in that sense. So we're. Last year we helped clear just north of a million crimes in America.
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A
What does help clear mean?
- [05:32]
B
So, I mean, we want to be clear that similar to probably how you feel in that, like, you help businesses grow, but, like, you didn't do the hard stuff. Like, you just made it easy. You made it really easy for me to grow Flock by making payments. Simple. I don't actually have to do any of the hard work of, like, chasing bad people, putting my life at risk. Like, we write code and design circuits like it's not hard work. So we like to be very careful of, like, not overstating our values. So we were involved in the arrest in clearance or successful arrest of over a million crimes. And in a lot of those cases, we are the end, the beginning and everything 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. Like, we weren't the tips. You can't take full credit. So maybe I'll walk you through a recent an example. And I won't name the city because it's the. The case is still going through prosecution, but. So there was a 911 call. This is a major city of America. Our system hears 911 calls. We can tap into 911 call. This is kind of wild if you think about 911 today when you call 911 in San Francisco. Let's go. You 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. 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 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 their flock develops or not. And so that 911 call pops up. The kind of an operator is like, oh, my Gosh, there's a 911 call right there. They can listen to the call. They're like, 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. And you 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. If you think about the way, the way it used to work, that case never would have been solved. It had been weeks, maybe months. And you could have gone a cold case. 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 did 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. So in a town in Colorado, there was an armed robbery of a Levi's outlet. Gotta 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. 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 400ft to the Levi's outlet. That drone knows what to look for. It has the visual kind of 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 already 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. This case, the drone's four feet up in the air. You have no idea. The drone's 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.
- [09:43]
A
And what is flock by the numbers today? So how many cameras, how many drones, how many law enforcement agencies, how many individual entities?
- [09:52]
B
Yeah, so it's just over 6,000 cities. So it's like well north of 50% of America. That's covered by flock.
- [10:00]
A
By population?
- [10:01]
B
Yeah, by population. There's about 17,000 cities in the US and we have all the big ones outside of Manhattan at this point. That's like the last, the last one to go get. 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 them to the government, which is like three strikes are out.
- [10:29]
A
That's incredible. And I feel like something non American listeners mightn't realize is. So I grew up in Ireland, country of 5 million people, and there is just a blue, the gardishi Khana, like the national country. Exactly. Police force for the whole country. And that is a relatively common model in lots of places. In the United States, it's the opposite. It's very localized and just maybe you want to talk about the average size of that. And I feel like what you're providing is in some ways scale economies and helping police forces coordinate with other agencies.
- [11:04]
B
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. Most of South America, like America is really the only country that operates under a model where local municipalities provide a law enforcement service. It's very rare.
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A
Yeah.
- [11:27]
B
And the benefit, the pro is very straightforward, which is like you actually have a good chance of knowing the police officer that has your territory and has your patch of dirt. The downside is criminals don't really care where cities start and stop. They don't care where states start and stop. Yet historically, law enforcement agencies were incapable of sharing information. To give you a sense of timeline, the cloud was only recently made legal in Florida as recently as 2022. So if you were a law enforcement agency, you could not host your data in the cloud until 2022. Maryland was 2023.
- [12:05]
A
So any coordination between agencies was very manual.
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B
All phone calls, faxing files. And so one of the big kind of unlocks of flock was this realization that you could drive better collaboration. Because if you're kind of low level criminal isn't maybe changing cities. But you look at some of the most successful cases we've helped work. It's like multiple states. Right. Like we did a huge human trafficking bust. 70, 76 people arrested across four states. Like all organized on Flock. And like.
- [12:41]
A
And it's really hard for one agency to wrap their hands around that whole thing.
- [12:44]
B
No. At that point you've got like six different local cities, two different. Sorry, three different state agencies, and the US Marshals all collaborating inside a flock. And like that's, that's how it should work.
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A
Yes.
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B
Because in Ireland that is actually the only option because you're the same police department. It's a very unique problem that America has created.
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A
Law enforcement coordination.
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B
Yeah, yeah. Like it should be. It shouldn't be controversial.
- [13:08]
A
Yes.
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B
But it's actually a very controversial topic.
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A
What's controversial about. I'm not aware of this controversy.
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B
This is an interesting question of like
- [13:17]
A
you,
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B
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 of the federal government is very low. State a little bit lower local, full trust. And so there's this interesting dynamic where. Let's talk about 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. Like 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 of timp. The Secret Service. Like 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 because of all the certain topics. Because of all of the. There's different politics. And so we kind of have to sit in the middle.
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A
Yes.
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B
And when it's clearly legislated, like in California, it's actually. It's fine. It's. That's the law. That's actually very simple. It's in other states where it's opinion.
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A
Yes.
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B
And that's like, oh, that's really messy because we should just write laws. I mean, we operate in a regulated space. Regulation, when done properly, just defines the rules of engagement. Sometimes it's better or worse, but at least everyone knows these are the rules.
- [14:49]
A
Yes, yes. As I think about where Flock grew up and helping with flagging stolen vehicles and kind of a very vehicle oriented product. How does that work at a technical level? There was a stolen database. There was a database for stolen cars already. But that's an example of prior cross law. Like who maintains that database? How does it work?
- [15:16]
B
Yeah. So it's a good question. So you think about a couple of fun engineering problems that Flock how to solve. The first is how do you do what we just described? Read a license plate, track a car on solar power with a 5G backhaul,
- [15:32]
A
which is the camera that you have. Traffic light.
- [15:34]
B
Yeah, exactly. But you very rarely have fiber or power where you want to put a camera.
- [15:39]
A
So you want a self sufficient box that you can totally infrastructure free at an intersection.
- [15:43]
B
Yeah. And be able to track a car going 100 miles an hour and do some level of computer vision on top of it. And like that was a pretty fun problem because if you put, you know, let's say you wanted to put a GPU in it, you're going to. You can't run on solar power then. And so then it's like, all right, well then what do you do on the edge? What are you doing on the computer?
- [16:00]
A
And you can't buy any GPUs these days.
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B
Yeah, yeah. That would have been a huge disaster for us. But. So the FBI maintains a list called the ncic which is about quarter to half a million known vehicles with either warrants. Could be Amber, the Amber Alert system, the Silver Alert system. We saw, sadly, a ton of silver alerts. Too. I think we did just over 1,000amber and silver alerts last year that we helped clear. It's like missing adults, missing seniors, and missing kids. Pretty sad stuff. And so we have a direct integration with the FBI for that. And then at a local level, let's say, like the Bay Area, there is a Bay Area hot list that we maintain with those agencies.
- [16:45]
A
Oh, wait. So I assumed that there was a single integrated. When a car is called in as stolen, I assume that went somewhere integrated.
- [16:54]
B
So this is kind of scary. So let's say your car is stolen and you're in South San Francisco. They will immediately put it in the Bay Area Flock hot list. Immediately. It will take 24 hours to make it to the FBI hot list. And that's a CSV file that gets sent around on FTP servers across the
- [17:15]
A
US as much the economy runs, you
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B
should be used to that at some point.
- [17:19]
A
Yeah, exactly.
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B
So the real time happens on Flock and then there's about a day lag to make it nationwide.
- [17:24]
A
Okay, so local entities have some kind of local lists, and those propagate to a national database, which is an FBI database. And what you guys are doing is making that real time, which obviously, if a crime is unfolding in real time is a big deal.
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B
Exactly. Yeah, yeah. It's not good to wait a day.
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A
Yes.
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B
You can drive really far in 24
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A
hours, it turns out. Yes. And then you had some great stat before, about just a fraction of, like, stolen cars are bad news. Like the fraction of crimes that involve stolen cars.
- [17:52]
B
There's an interesting phenomena where you don't. No one really steals a car for fun. Like, there's not much you can actually.
- [18:00]
A
Is it true, like, all the sideshows and stuff? Like, isn't there a little bit of stealing cars?
- [18:03]
B
Well, the sideshows are definitely. They look fun. Never participated in it.
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A
Neither have I, but. Yeah.
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B
I just wanna make clear here. Yeah, yeah.
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A
It's my official statement on the back.
- [18:11]
B
Dirt bikes. Haven't ridden a dirt bike in a sideshow, but have watched plenty of videos online. That's fun. You're typically not stealing a car. You're typically driving your own car. Oh, you typically. While there are some people, I guess, who would steal a car and just drive it for fun, the main use case is like, when my car was stolen, my car was stolen. And then they used it to go rob 3cvss, did a bunch of drugs in the car and then ditched it. And that's like a normal. You steal a car to go do something bad. Yeah. Or you steal a car to go shoot someone, because you don't want to shoot someone in your own car. If you're thinking ahead, you want to do it in a stolen car.
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A
You all watch Pulp Fiction.
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B
Yeah. This is how you do this, Right? And so we do a bunch of other interesting things. Like 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, is you steal someone's tag. So then you got to go down to, like, we got to steal the same license plate from the same type of car. But then if we detect an anomaly that the same car is in two places at once, we'll flag that. It's like, that's kind of weird. That's like a glitch in the Matrix. We have all these, and we would call them more like anomaly detections, where it's like, this isn't illegal yet, but it sure is kind of weird.
- [19:25]
A
Yes. And it's enough of it provides enough reason to pull someone over.
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B
Yes. 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. But if you're a foster city, you're a smaller town where, thankfully, you don't have violent criminals running around every day. You're like, ooh, 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.
- [19:50]
A
Yes. It strikes me that. A way you can think about what Flock is doing is not changing any of the norms around privacy, but really expanding law enforcement's bandwidth to go deal with stuff. And so I don't think anyone really has an expectation of. Of, you know, 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. But if a car is called in and stolen, rather than officers manually, you know, looking for that car and that license plate instead, you can just kind of much more quickly get it. And yet this kind of stuff ends up super controversial from a. I don't wanna say super controversial, but it ends up controversial from a privacy point of view. And so, I don't know, is that take too generous? Is there a steelman of the other side? Why is it there?
- [20:51]
B
Is, I mean, I think you're right on the controversy. I would articulate it as like if you're building a business that impacts millions of people's lives, it's going to be controversy of some degree. I'm sure there's someone who hates Stripe. I don't know why they would, but I'm sure that person exists. Just like there's someone who hates Walmart. It's like they're trying to sell cheap groceries. Why do you hate. It's like people hate every company. Maybe they hate us more, I don't know. I think there's a few things that make it for the Steelman argument. One is you can see it. So I bet you if we pulled up your iPhone and we looked at the number of apps that you've given full time local location services, it would shock both of us. And then if we looked at the number of data brokers who then leverage that data to sell you ads, we'd be really shocked. And I think if we rewind it 30 years ago and said imagine these private companies tracked your location in real time and sold out to avatars, 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 anomaly anonymity or being anonymous. 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. 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 a 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. We're constitutionally, we have no extension of privacy, but we're using the government's roads with the government's license plate like we have a driver's license in our pocket. Driver's license are a modern thing. That's not a, that hasn't been around for 200 years. It's a newer concept of A driver's license. So we've accepted all those. The articulation that I would have is like I want my kids to be safe. And like as long as there's accountability of like 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 there for us, like we really believe in this concept of a certain data retention which kind of limits the level of abuse. It doesn't eliminate abuse. There's still going to be abuse, but it limits that. Hey, if it's 7 days, 14 days, 30 days of data, it's just not that interesting relative to what you see with data brokers online where they have your entire Internet history stored forever.
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A
You're interested in fresh data. That's what's.
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B
Yeah, but criminals, yeah, there's a really fast drop off of where have you been in the last couple days versus like where were you a year ago? It's very irrelevant in a criminal investigation.
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A
Yes, yes.
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B
Or it's protected behind a warrant, which is fine.
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A
Right. You talked about cell phone locations and you know 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 you know, criminals get why is that fingerprinting exists 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 just what are the other major trends going on from a technology point of view in how crime gets fought?
- [24:39]
B
Yeah, that's CDRs would be the nomenclature in the law enforcement cell phone data dump or cdr, cell phone data record, something like that. Yeah, but it's your point. It's the broader. Like you hit these three towers, therefore you're in this general vicinity that is like one of the best kept secrets for law enforcement of like how to solve crime. Which people dumbly commit crime with their cell phone in their pocket every time. It's very rare. 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 self on their home by design. It was a very intentional. They were very organized in the area. Couple other ones.
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A
How did they get caught?
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B
It's actually flock obviously. So they were smart enough to leave their cell phone, they were dumb enough so they Drove from LA up to San Francisco general area. They hit a bunch of flat cameras along the way. They didn't pick up their cell phone till they went back to lax. And we have cameras all around lax. And like 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. This is a good case.
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A
And I guess the thing you can do is you can know that a cell phone's in a car because you can.
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B
We don't touch that.
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A
But the law enforcement, Sorry, law enforcement can cross reference cell phone location would flock.
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B
So they knew that the vehicle was in a certain parking lot they can then use. They have to have a warrant at this point, get 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 current phenomena that is causing a ton of problem 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 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 very much.
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A
Drones to case out, to scope out.
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B
Yep.
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A
Wow.
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B
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.
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A
Sure.
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B
They jerry rig an LTE modem to cheap drone. They can fly it anywhere however they want. And then legally, even today, law enforcement is not allowed to engage that drone. They can't take it down. It's FAA airspace. It's not law enforcement airspace.
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A
Sure, yeah, yeah.
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B
And so they just sit there. So that's a problem in neighborhoods. Also a problem in prisons. That'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 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.
- [27:40]
A
Cell phones, drugs, guns, Teller from zipline here, it's zipline for criminals.
- [27:45]
B
And these guys have built a comparable product. 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. 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 gonna do what we want. And that creates a problem because most law enforcement officers just wanna follow the law.
- [28:11]
A
Yeah. And presumably that won't stand up from a federal preemption point of view.
- [28:15]
B
No. And like, the other challenge is, like, I think you and I were like, who's gonna enforce this? The FAA is not an enforcement body. But these people want to follow the law. And the law says clearly, like, you can't shoot a drone down.
- [28:25]
A
Yes.
- [28:26]
B
You can detect it. You can't. You can't mitigate.
- [28:28]
A
I have no idea.
- [28:29]
B
And it's a totally crazy law.
- [28:31]
A
Yeah. What else has made. What else has gotten worse from an offense perspective?
- [28:38]
B
I mean, this is one that's like, you know, I don't know if I have strong feelings on this, 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.
- [28:53]
A
Yes.
- [28:54]
B
The downside is, like, 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 very early 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, very good thing. It's like, a very effective tool. But, like, there's a debate of, like, should law enforcement have more ability to solve crime faster? And the example, 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 as 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, yeah, the petty stuff, we should say, look, we gotta make progress there. But, you know, you stole a pack of Skittles. Like, we probably shouldn't deploy a drone to find you. Like, if you kill someone, I think we should work really, really hard as a society to hold you accountable.
- [30:18]
A
Yeah.
- [30:19]
B
But there's no. There's no nuance.
- [30:21]
A
That nuance does not come through.
- [30:22]
B
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. It's counterintuitive to me when the technology gets better every day.
- [30:31]
A
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.
- [30:47]
B
It's backfired.
- [30:48]
A
I wouldn't say backfired, but just like it's actually in a lot of cases been somewhat exonerative. Right.
- [30:55]
B
Yeah. No, I think in many cases police were really hesitant to get body cameras. Just like, I mean, imagine if you wore a body camera all day at work. You'd be like, ah, not sure if I love that idea. It's kind of 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 law enforcement officer was just trying to do their job. And on the other side, there was other mental health issue, There was something gone wrong and it actually exonerates the officer, which is kind of interesting. And I think the same thing is true. What at least we're seeing on the camera side on the streets, is historical policing. Sadly, it's 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 like, 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, like, 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.
- [32:03]
A
Yep.
- [32:04]
B
We don't care who's inside. We will find out eventually that car was stolen.
- [32:07]
A
Yep.
- [32:08]
B
And then you don't wind up policing where crime has happened historically. You end 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 this, the kind of 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 days, then we're good.
- [32:35]
A
Yep. Yep. Is crime up or down in the
- [32:38]
B
US it is down. I think it'll continue to go down. Covid was like really bad.
- [32:47]
A
Surged during COVID Crazy surge. Okay.
- [32:50]
B
People lost their minds. I think we tested society of like, what happens if you keep people inside for too long and people got really violent.
- [32:58]
A
Yeah. So do you have an explanation? Is it that, like, it was a mental health issue or was it kind of a crime of opportunity that, you know, things were less well guarded and, you know, there's more opportunities for crime. But you think it was just people went a bit batty being locked up?
- [33:12]
B
I think so.
- [33:13]
A
I'm resorts to crime, but I mean,
- [33:14]
B
I mean, I'm obviously not a clinical psychologist by any means, but it's like you look at the data and there's no other way to articulate why homicides 3-4-XED 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. 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 like, this is. This is like, this is really sad.
- [33:53]
A
How do you measure very online?
- [33:54]
B
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 kind of what's going on. This is a couple years ago, right, 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? Like, oh, because this guy posted a picture of him with that guy's girl on Instagram. And I think in a normal situation, you might have called that person and been like, hey, bro, that's my girl. And in other cases, they're getting in a car shooting someone. That's not normal. It'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. 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's the most obvious explanation to me.
- [34:53]
A
And I guess there are other empirical measures, like air range incidents, road rage incidents. Like, all of that kind of stuff
- [34:59]
B
went up during COVID Everything went up? Yeah, like, everything. People just literally lost their minds. I think we, like, need to be outside.
- [35:05]
A
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, like, there's all these memes which are maybe do some debunking and confirming
- [35:20]
B
of all the memes. So every city is a little bit different. Major cities still have major crime problems, 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. 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. Like, 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, like, they are making crime a focus, and the focus is on solving crime.
- [36:20]
A
Yes.
- [36:20]
B
And when they solve it, as I'm sure you follow on the news, they talk about it.
- [36:23]
A
Yeah.
- [36:24]
B
And they should, because, like, it's really cool. They're working very hard. And what you'll see is back to the online point I made. All these people are online. And so when San Francisco PD is dominating X, it has a deterrent effect. Oh, gosh. Yeah. You don't want to get caught.
- [36:38]
A
Yeah.
- [36:39]
B
And that's like, the unintuitive or 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 would 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. You're 17 people.
- [37:03]
A
I got caught in us.
- [37:03]
B
Yeah, yeah, yeah. And so when you notice criminals are so online. So if you, if you flip that. Oh, it's like, it's, it's a subculture. You gotta get there. But I mean, you'll see.
- [37:12]
A
Sorry, is this like Reddit, Twitter, they're everywhere.
- [37:15]
B
Pinterest, probably less Pinterest, but I mean, TikTok's really big. Instagram's really big, Snapchat's really big. And like, it is. It's how they recruit though, right? Because, like, the whole recruitment effort is, you know, I'm going to show a lifestyle online that seems dream worthy to recruit these people. And then they're in and they're going to 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 medium income for your average criminal is like, it's very, very low. But they promote a lifestyle of wealth. So if you look at those cities, like, so take San Francisco. Crime's coming down, Clearance rates are going up. And I would say, like, as soon as we can get somewhere like San Francisco to 100% clearance rate, which we have in other cities, crime goes down.
- [38:01]
A
100% clearance rate is like 100% solved.
- [38:03]
B
Yes. And it's doable. We have it in major cities. And like, like Cobb county would be one, which is like the secondary has 100%. Yeah. If you commit violence in CO, you will get arrested.
- [38:15]
A
And that's across spot sample size.
- [38:17]
B
That's the second largest county in Georgia. So let's call it, you know, couple million people. Almost a million people.
- [38:23]
A
So a decent number of violent crimes.
- [38:24]
B
Oh, yeah, yeah, yeah. And like, but it's going down every year. Sure. So you look at places like that. Yeah. And so, like, we have this new concept that we've developed called like, 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 like about 20 bucks a citizen a year.
- [38:44]
A
Yeah.
- [38:45]
B
It's like, it's your choice. And like, what's fun to watch is we find these Mayors with really strong backbones and they're like, I want to be a safe city. There's this awesome Town, Greenville, Mississippi, you probably never heard of it. 26,000 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 like, kudos to the mayor in chief. Like every crime they solve.
- [39:07]
A
Yes.
- [39:08]
B
They're on the five o' clock news.
- [39:10]
A
So these are highly effective cities. What effect does this? What happens to the criminals? Does it shift it to other localities? And like you need to, it's like, you know, disease eradication. You ultimately need to do kind of enough to blanket it, to snuff it out. Because if just kind of 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.
- [39:38]
B
There's two phases. The first phase, you're spot on. Like people, they just change cities. It's like when San Francisco started adopting flock, Oakland crime went up. So then Oakland needed to adopt flock.
- [39:49]
A
Yes.
- [39:49]
B
And now there's a couple of false starts. Now that it's fully going, they will have the same. But first is the shift and then you're right, people don't. The majority of criminals, let's call it 99% of criminals are not evil people. They're not like evil is a random act of violence and that is exceptionally rare.
- [40:10]
A
It's mostly opportunism.
- [40:11]
B
It's all opportunitudism. And like you and I were fortunate enough to be born in a family, in a social construct that we could go 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. 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 like they will go get jobs. These are functional members of society. They can be functional members. We should push them in that direction.
- [41:06]
A
What kind of crime is on the increase?
- [41:08]
B
So I'll tell you one that's pretty fascinating. So if you look in the enterprise community, organized resale crime in stores was really hot during COVID and right after Covid. That's why you saw CVS lock their stuff up. You saw places like In N Out leave Oakland. Like this was a huge problem. And it's still, you know, for someone like Walmart, I think they reported just shy of a billion dollars of theft last year. So it's a lot of money. And like their peers aren't doing dramatically better. Now Flock customers are doing really well.
- [41:39]
A
And Walmart aren't neophytes at this stuff.
- [41:40]
B
You know, they have, yeah, we'll get there with Walmart. But like you look at some of our partners like a Lowe's, you know, their shrink has gone down order of magnitude. It's not exactly, it's not really a problem anymore. But where the criminals have moved is to the distribution facilities. It's safer and bigger loads. And so 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 low bid on all these projects, show up with real paperwork, fill up a 20 foot with product, drive away, dissolve the company. $7 million in a single day, that's pretty good business. Yeah, that's very sophisticated though. That's harder to solve. That's much harder to solve because every
- [42:39]
A
car phone, everything will be disposable, used in the.
- [42:43]
B
Everything's going to leave the country as fast as possible and just show up on a street somewhere. And then the other interesting challenge, you have to unpack. This is a little bit complicated. Who's liable? 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 negotiated 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. And it's going to take insurer cares. Insurer cares, eventually. But when you talk about the scale of, let's call it, you know, tens of billions of dollars, hundreds of billions of dollars of product being moved, you're like, oh, you know, we lost a couple hundred million.
- [43:30]
A
I see.
- [43:30]
B
Yeah, yeah, we'll be fine. We have insurance. It will catch up eventually. But that's probably the most interesting type of crime we're tracking is the tacking 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.
- [43:50]
A
Yes, Yes. I want to ask you more about this, but I want to get you another. Goodness. 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.
- [44:02]
B
Yeah, it's a big part of our business.
- [44:05]
A
Can you say how big?
- [44:08]
B
North of 100 million of our north.
- [44:09]
A
Oh, okay.
- [44:10]
B
So, like, it's real. Probably fastest growing segment. There's some, like, wild. There's some wild stories. So, you know, we. We help businesses solve two problems. How do you keep your employees safe, and how do you keep your assets or your stuff safe?
- [44:25]
A
Yep.
- [44:25]
B
So it's like, kind of funny because we have a Fortune 5 company that's
- [44:29]
A
a customer, and you probably don't want to talk about specifics, but we should just imagine big box stores that kind of.
- [44:34]
B
Well, this is the same thing. It's like we have this, like, Fortune 5 company as a customer, and they spend like $100,000 a year because they have like, three locations in the country. That's it. They have like, three really big campuses. So they're actually like, we don't proxy towards necessarily like market cap or revenue. We proxy to physical locations. Like how many locations? So someone like a Dollar General is a way better prospect for us because dollar general has 7,000 stores. Yeah.
- [45:00]
A
Want Subway?
- [45:01]
B
Yeah, you want Subway is a good example. So we tend to focus on retail, healthcare, and logistics. They tend to have big physical footprints. A lot of employees and a lot of challenges.
- [45:14]
A
And is their main challenge theft? Like, that's what they're worried about, that they want to prevent stolen cars coming to steal stuff.
- [45:24]
B
I'd say employees is. 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. It is much more shifted now to keeping employees safe. So you think about some of these businesses. They might terminate half a million people a year, quarter million people a year. Takes one angry employee to come back. And so in our system, you can have it automated with your HRS that like when employee is terminated, they're added to a localized hot list. That employee ever comes back on campus. It's not illegal, but Notify security is why people have security teams, like, don't let them in the building. So it's about kind of moving that layer of safety farther out.
- [46:03]
A
Yes.
- [46:03]
B
The other example is like, we do quite a bit of work in executive protection. So I'll give you a good example. Like a Fortune 2000 CEO. Our stuff's deployed at her house. We also deploy at corporate. It's not illegal, but it's quite weird if the same vehicle on the same day goes to both locations. And so frikking.
- [46:24]
A
That is not that person.
- [46:25]
B
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 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, pretty smart, actually would show up to the hospital dressed in like a certain company's uniform and be like, oh, the robotic surgical army is. It needs to be repaired. Can you help me grab it? And some clinical, clinical surgeons like, oh, yeah, let me show you where it is. No worries, no worries. John, walk in there. This is a multimillion dollar piece of equipment and they literally walk out with it.
- [47:09]
A
This happened in Thomas Crown Affair, kind of.
- [47:12]
B
But it's like, I mean, you're a physician, you're not thinking like, oh, is John actually working at this company? Is the product. I think I used it yesterday. You're like, oh, yeah, we get that sounds right. It's super expensive product. So this is an example to your conversation of like, where the business gets interesting is we then connected that healthcare provider with federal authorities. But so this is not a, this isn't going to be a local authority to solve this kind of crime. It's a federal crime. At this point. They were taking the product, exporting it and selling it in a different country for kind of, you know, clinical work. So we think that one is pretty interesting. There's like, that's an asset one where actually the healthcare system is like, this is a like 20 something million dollars of product stolen. Like that's a problem.
- [47:51]
A
Yeah, yeah. Is your business going international? Which countries is this best suited to? Like, is this a universally applicable product? Do those differences in, you know, law enforcement agency structure make it. I'm just curious.
- [48:05]
B
I mean, we're, we're dabbling, but we think payments is probably like a very global, like everyone wants to process payments.
- [48:16]
A
I think, yes, there's a lot of local nuance.
- [48:18]
B
Yeah. I think for us Maybe our ambitions aren't big enough, but when I look at the domestic opportunity, you know, we should be able to get to 5, 10, 15 billion of revenue in America. And like we're not. We're not there.
- [48:34]
A
Yes.
- [48:35]
B
And so it's the difference of, to your point on the nuance in 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. But there's, I mean we get an inbound. I saw an email this morning from an Australian police department. It's like, we'd love to do a demo.
- [48:56]
A
And it's like, why not just do. I mean, I agree there's a lot of nuance. Is there some aspect of your tech, like you've put a lot of work into the cameras, vehicle recognition, stuff like that. I know again from painful experience that localization is never easy and never as easy as you think.
- [49:13]
B
Yeah, but maybe it's easy. Well, so here's the argument. So we pursued one really big deal last year in Mexico. We had support from one of our investors, like we should go after cigar. Great. And they had connections to the Mexican government. So we got all the way to the finish line. And it was US versus hikvision. Hikvision as a Chinese camera manufacturer, arguably a subsidiary of the ccp. And we were almost ten times the price. And it came down to like, well, is the Department of Homeland Security going to subsidize for this for the Mexican government? Because we know their list price is way more than this. It's very clear this is being subsidized for the Mexican government to make this purchase decision of 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, they own those countries.
- [50:23]
A
Lots of boat cutting cross here.
- [50:26]
B
Okay, well I'll find the book. But the book pretty much shows that like one of the maybe smartest moves that China did was going to these developing countries and saying we will give you 5G, really low cost. We'll bond it for like 100 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, that was Our pitch to the Mexican government is like, 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 in America. And they were like, sorry, it's too expensive. And we've seen that. We've done a couple 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
- [51:15]
A
federal government, but presumably NATO countries, you know, Australia
- [51:21]
B
should be better. But I mean, no, I mean, I can. We should go walk around, you know, a strip mall. And I could probably point out 80% of the cameras are Chinese manufactured. And your average would be business owner is like, yeah, I got it for 15 bucks on Amazon.
- [51:37]
A
Yeah.
- [51:38]
B
And like, I don't know if you know, that's that story on kind of like the, you know, vacuum cleaners that someone like hacked into.
- [51:45]
A
It's like the robot vacuums.
- [51:46]
B
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 that makes sense.
- [51:57]
A
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,
- [52:06]
B
which makes it very hard to spot
- [52:07]
A
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 Flux Safety fights crime, check out Stripe Radar. As I think about your competitive landscape in the US and companies that sell to law enforcement, I think about Axon, which people would associate with making the body cameras, but they make lots of. And tasers, I think, but they make lots of other stuff. And then Motorola solutions, which has kind of the radios and like the get 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, like, presumably you guys compete more over time?
- [53:02]
B
Yeah. So I remember in 2020 trying to raise our series B and every investor came to the same conclusion. Three strikes are out. Like strike one. You're based in Atlanta now, like post Covid, that's become like less of a problem. But, you know, strike one, you're in Atlanta. Trike 2, you're doing hardware. But that's really bad. Hardware is like really expensive now.
- [53:25]
A
Now it's the only business with terminal value.
- [53:27]
B
I would argue that, like, AI is not going to like, replace cameras or dig holes. Yes, yes. A third of our employees dig holes for a living. Like, that's just. AI is a long ways away from, I think, replacing that.
- [53:38]
A
Sorry, what are they digging the holes for?
- [53:39]
B
Because most of the time you want a camera where you don't have any infrastructure.
- [53:42]
A
We actually sewing post or something.
- [53:44]
B
We dig the hole, we trench it, we pour concrete, put our pole up.
- [53:48]
A
I mean, okay, so it's on your own pole. I assume you just mounted on an existing pole.
- [53:52]
B
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 ever built a house, you know how difficult it is to permit something. 77 permits a day. By crazy scale, yes. AI is not going to replace that. It's like a very safe asset. But so, 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 have been 15 years prior to. 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. So luckily, Gary Tan shared my beliefs of, like, 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 is, I think, to say only Series B he's ever done. That's awesome. And he was right. And I was right. So it's the three of us now it's Motorola, who's the biggest. They're about a $90 billion market cap, 120 years old. Invented the radio. Still are the. I think they have 80% of market share globally of Landmass Radio. Just like crazy scale.
- [54:59]
A
It's funny how durable some of these businesses. Garmin. Another, like, you just start doing gps, you start doing radio and you stay doing radio.
- [55:06]
B
And to like, Motoro's credit, like, they've, they've driven a ton of innovation on the radio itself, similar to Garmin, which, like, you'd thought Garmin would have been crushed.
- [55:14]
A
And it's like they've been so Creative in creating verticals, you know, aviation, all this stuff.
- [55:18]
B
Awesome products, 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, they work especially well.
- [55:29]
A
Yeah.
- [55:29]
B
And that's, like, 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.
- [55:46]
A
Where'd they come out of? Like, I understand where Motorola came out of.
- [55:49]
B
Yeah. So Rick Smith's the founder, graduated Harvard. It's like, a fun fact. He plays it off. He's a very smart guy. Graduated Harvard, found this Taser company. It wasn't called Taser at the time.
- [56:02]
A
Okay. So they started with Tasers.
- [56:04]
B
Yeah. Found that. Found those kind of the ip, the product, and then tried to commercialize it. And it's. If you're. You love a good founding story, it's a good one where, you know, almost went out of business is like, dad mortgaged the house. He mortgaged the house, 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.
- [56:31]
A
And Taser is a brand. It's like Kinex they own. So they started.
- [56:35]
B
They started Taser and rebranded to Axon in 2012 or 2015, 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'd recently launched a competitive product with me. So now we compete. Everything we do, we compete with Axon, too, which is fun.
- [57:00]
A
So it's just a Mexican standoff.
- [57:01]
B
Ironically, every single city. Every single city. And then what's 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, like, poured in. And when I used to call a police department seven years ago, now you
- [57:20]
A
have a bunch of competitors.
- [57:21]
B
No one would know. Like, you could literally just walk into police department, meet the chief. That's great. Now chiefs are, like, 17 different people calling me for the exact same. Now, they don't compete with us, thankfully. But, like, you think about. Take, like, trying to deploy AI to monitor body cam footage. There's seven different companies with VC backing doing that. There's not, it's not a big enough market. Yeah, yeah, I think your annual report was great, by the way. Y' all are at what, 1% of GDP or something? Probably. Okay, I'm in 60 to 70% of the cities that matter.
- [57:56]
A
Yes, yes.
- [57:57]
B
There's just not enough space for seven competitors. The market's not big enough. And we're not creating new cities. There's new businesses create every single day.
- [58:03]
A
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.
- [58:16]
B
I think that's what you're saying. Yeah, 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 are going out of business or 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 gonna see a ton of consolidation because once someone builds a good product, you go, great, I already have a salesforce, I have the customer base. We'll just pick you up.
- [58:43]
A
Yeah, yeah. So I had no idea about the, you know, you're talking about where the tech goes. I had no idea about two things actually, I learned here. One is that you're doing real time analysis of 911 calls. And so is that, I mean, is that being fed to an LLM basically or like 911 calls now scored by an LLM?
- [59:00]
B
So the, 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, at a higher ed, so college campus, a large college campus, you know, a football school, they're 40% of staffing. Could you imagine if like tomorrow you woke up and stripe had.
- [59:25]
A
Was 40% staff?
- [59:26]
B
40% staff. Yeah, it'd be tough. You would like figure it out. But a lot of things that you would deem core today would just stop.
- [59:32]
A
Yes, yes.
- [59:33]
B
And so that's how most of our customers operate, which is not sustainable.
- [59:38]
A
Yes.
- [59:38]
B
And so we view our job as like 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 like, I think you want humans at the start and finish still. So If I call 911, still kind of want a person to pick up.
- [59:58]
A
And those dispatchers are incredibly well trained.
- [60:00]
B
They're very well trained, they're very calm. Now, where I think it gets valuable is like, but let's say there's a mass event. AI is way better. Because if you have a surge of demand and you go from only one call a minute to 10 calls a minute, AI is better than a busy tone. Yeah, that makes sense. And then I think about, for us, we call it amplified intelligence. When that 911 call comes in, LLM is able to pick up the call, is able to determine what are the characteristics. Can I go sort of build an investigation? Can I go pull this up? So that if you're the detective, whereas historically you walk in your car. I'm going to go get the call transcript. I'm going to go look up my record system. I'm going to go do a bunch of analysis. It's the equivalent of having, whether you use something like a Glean or another product that's like, do a lot of the hard work so that as a sales rep, you show up and you're like, got it. And so we do that for investigators. So they show up to get delivered a case in. A lot of the busy work has been done for them. So they can use the human part of their job.
- [60:52]
A
They're getting all the data that needs,
- [60:53]
B
thus all the different data. Like, let's go do this. Like, we solved. One of the cooler cases we've solved was like armored trucks, like Brinks, they move money around. What's one of the best? It's called, like a jugging case. It's very popular in Texas where you follow these armored trucks and you typically have like a shooter on a nearby building. And when the person walks out, the shooter shoots him. The other guy runs in, grabs all the money and runs away. It's like a very. It's 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. Yeah, yeah, sure, right. 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, you let me know whenever you see someone doing that, because I want to know. Yeah, I want to get A step ahead. So there's all these types of crimes that you can sort of say, okay, this is helping officers not do something new. It is just doing things that when you're at 50%, 40% staffing, if you're at 100%, you would 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.
- [62:05]
A
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.
- [62:18]
B
No, it's. And it's like people's lives, you know.
- [62:22]
A
And then the other thing I hadn't realized you guys were doing is the drone assistance, where again, this sounds to me like, you know, obviously already it's the case that, you know, many police departments have a helicopter and then for very serious crimes, you know, they will task us. 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.
- [62:47]
B
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.
- [62:59]
A
Yes.
- [63:00]
B
And so if it's, you know, calling out a hit and run, great, send the drone. I was working with a town in Tennessee. It's a pretty, it's a good city. Their average Response time to 911 call is 7 1/2 minutes. Their drone from us gets there in 68 seconds. Just like a better quality of service and the incremental cost is less than the cost of one single officer. It's really nice when you see technology deliver both like a 10x better product at a dramatically lower cost. Yeah, that's how it's supposed to work. And it's working for them.
- [63:34]
A
Where are the drones? What kind of task or intervention are the drones best suited for?
- [63:40]
B
I mean, the two most. There's three primary use cases. The first would be vehicular pursuits. So one of the most dangerous things cities conduct is high speed pursuits. Typically it's not the suspect that dies, it's some random person cartoon or something.
- [63:52]
A
Yeah.
- [63:53]
B
So for most of our towns that have adopted our drone program, they end pursuits they don't pursue anymore. Send the drone.
- [64:00]
A
Oh wow.
- [64:01]
B
Just send the drone. Way better. Yeah, yeah, it's way safer.
- [64:05]
A
So you don't have like a police car running at 80 miles an hour down a residential street.
- [64:09]
B
No, you just have a drone 400ft up in the air, quietly, safely waiting for the car to pull into a gas station, pull into their home, pull in somewhere safe, get to a red light, and then meanwhile, that video feed's being broadcasted to the entire police department. It's like, great. The police, you know, John's over here.
- [64:24]
A
Yeah.
- [64:25]
B
Block him in.
- [64:25]
A
It's. You know, every pursuit goes to GTA level five immediately.
- [64:29]
B
Basically, yeah. If you're. If you're smart. So that's a big one. The second is 911 calls. So what's been interesting is that, you know, we'll send the drone first. Take someone like Elk Grove up in Northern California. They've got a bunch of our drones flying the 911 calls.
- [64:45]
A
So where's Elk Grove?
- [64:46]
B
Elk Grove, it's a suburb of Sacramento.
- [64:49]
A
Okay.
- [64:49]
B
But maybe 75,000 people. So I say suburb. It's like a pretty big town, but. So they'll dispatch for 911. Majority of the calls actually never need a human to show up. And the example I'd give you is, like, you see a fist fight, so you call 911, and then what happens is, historically, like, seven minutes later, someone shows up. Guess what? They're no longer fighting. But now we've dispatched this officer, he's like, well, I'm in the area. Maybe I'll grab a Gatorade, walk around, check it out. Thirty minutes later, like, we've wasted a bunch of time. You send the drone in. Best case, you see the guys fighting and you're like, great, I'm gonna keep an eye on them and allow the officer to do his job. Or there's not a fight anymore. You dismiss the call. And so you actually increase. Sorry. Decrease the response time for situations you really do need to go to by removing the junk in the system. That's the second one. And the third one is search and rescues. Not every city has a helicopter as soon as I do. It's a very expensive proposition. And so, sadly, people go missing all the time. And you can pop up the drone, throw on thermals at night, and find the person.
- [65:56]
A
Actually, I hadn't thought of that. But drone plus thermal camera is very transformative for us.
- [66:03]
B
Ar. 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.
- [66:18]
A
I have a better topic for you in a second.
- [66:19]
B
Okay. Great. So there's this 911 car on the side of the street, launched the drone, Throw in thermals, actually see where the person went. Like sensitive enough to see the heat pattern. There's a dip in there. Want to find the guy, find himself on everything. But it's just interesting, to your point. I think we're still very early on in the use case exploration. And I think it's just the type of technology that until it's fully proliferated, which give it two, three more years, I think we'll continue to find more ways to augment how we respond. Because I think just 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. The whole community gets advantage of it.
- [67:03]
A
Yeah. Yep. Okay. My fun example. Cause I agree a lot of the, you know, crimes are quite heavy topics. So I feel like 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 insane crime that happens.
- [67:24]
B
Wait, why do they do that?
- [67:25]
A
Okay, so there's this insane crime that happens.
- [67:27]
B
Isn't that bad? It's like, very dangerous.
- [67:29]
A
It's very bad. It's very dangerous. Yeah, but like bored people, to your point of just maybe people going mad during COVID and being cooped up, people just for fun, laser aircraft. It's very dangerous. Like, it's dangerous for anyone's eyes shining a laser into them. But like 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 like ATC recordings all the time. Like airliner going into lax, you know, getting lasered by someone on the ground. And so people buy these lasers on Amazon.
- [67:52]
B
Yeah. And they're like. They're like very powerful lasers.
- [67:54]
A
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.
- [68:03]
B
They're just like, gotcha.
- [68:04]
A
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. We'd like to see the squad cars coming up. And it's.
- [68:10]
B
Yeah, let's check that out.
- [68:12]
A
But it's such an odd crime. And yeah, it's very satisfying to see them caught in real time.
- [68:19]
B
Yes, that's a really Weird. The other interesting too, because I know you like aviation stuff. Yeah. We're having to see. 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.
- [68:32]
A
Yeah, yeah, sure.
- [68:32]
B
And so most of the police helicopters actually fly without ADSB now, which is like a whole challenge.
- [68:38]
A
Yep, sure.
- [68:38]
B
From a separation point of view. Yeah.
- [68:41]
A
Okay. I have so many more things to go into. We're kind of jumping around, but I like this. How's the business evolved. So you're now. You said around 500 million in error 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?
- [69:02]
B
Yeah, I mean, I'd say the biggest challenge is two, 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 kind of operating and law enforcement was going really, really fast. We had one product and then maybe made a mistake. I know RJ from Rivian was here. Similarly, 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.
- [69:41]
A
And there's very significant scale economies as very high orders of maintenance.
- [69:46]
B
And so, you know, 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.
- [70:01]
A
So looking back at it, you think you went too broad too quickly?
- [70:03]
B
Yeah, I would have better.
- [70:05]
A
So did you discontinue products and stuff? We just stuck with them through it. Yeah. Still, when you slow down the race
- [70:13]
B
of adding products, we were like, we cannot do any new hardware products this year. Like, 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 flock five years ago. And we know how painful that is. But we were just like, oh, it'll be great, it'll be fin. And so I think that's been. That's been challenging for us is how do you balance from a product roadmap servicing two customers, which is very different use cases. Like your average Amazon distribution facility is, you know, 30 acres, 50 acres. That's, that's like a neighborhood block. Yeah. And then you've got like a San Francisco that's got hundreds of square miles. It's. The problems are different. So that, that is probably like the hardest thing that we're, we're still.
- [71:12]
A
Yes.
- [71:12]
B
Trying to muscle through that. And like how do you organize your company to service these two different customers without having redundancies? Haven't figured that out.
- [71:19]
A
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?
- [71:28]
B
Yeah, I think the, there's a couple 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.
- [71:42]
A
Sure.
- [71:43]
B
And it typically needs to be 12 to 18 months out.
- [71:45]
A
Yeah, yeah.
- [71:46]
B
And if you look at the like hardware companies that don't make it, that's actually where they fail.
- [71:49]
A
Yeah. No, we ended up with, I mean our hardware business is a very small part of our overall business, but we wildly overproduced. At one point, just sitting in a
- [71:58]
B
warehouse, like, there's all my money.
- [71:59]
A
Exactly. Sitting in a warehouse, sitting around.
- [72:01]
B
Now luckily it's not, you know, it's not going to go bad. It's not like bananas. It's like, oh gosh, we have like a week to move this product.
- [72:07]
A
Yes. But it kind of goes bad.
- [72:09]
B
But it does go bad at some point. And I think I remember during YC many years ago talking to Eric at Pebble of how it's like the irony that in the best year ever of the company in terms of revenue is the year they went out of business. They're like, that's crazy.
- [72:27]
A
Yes.
- [72:27]
B
But they just overproduced in Q4. Even though it was still a record quarter, it just still wasn't enough. So I think that has been amplified by also our distribution process, which we're full first party. So we not only design the stuff, build the stuff, we install the stuff. And so I have to have forecasting maintain us, presumably maintain it as well. So I have to have forecasting not just at the product level, but at the geographic level by product with some level of discrepancy. I don't need to know this city versus that city, but at least the general area. So I think forecasting a decision that's been pretty hard. And the second is every decision you make in hardware is millions of dollars at a Minimal 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. You want to pick that part?
- [73:21]
A
Yeah, yeah, great. We're going to live with it for the next five, ten years.
- [73:24]
B
Yeah. And like, 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 like we had this one part that was in 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 apart for a new product that's coming out in 12 months and the supply globally disappears.
- [74:00]
A
Okay, so you're feeling the AI data center build out in your supply chain.
- [74:04]
B
Yes. And so our supply chain leader was like, this is getting crazy. And I was like, well, who do we use? I'm like, oh you sandisk. And so I'm looking at their stock and I'm like, oh, should we be buying, like I was Talking to my CFO, should we be buying SanDisk stock? Their prices are going up 3x. It means that like a lot of people are buying a lot of products now of course the Stock's up like 1,200% and I feel like an idiot for not like following that conviction. But no, yeah, I mean our bom now luckily it's a small part of our bom, but like we have a full time, full team of people who all they do is mitigate global supply chain risk. Those parts just disappear.
- [74:36]
A
Okay, so just getting the products into the hands of customers as already spec'd is non trivial.
- [74:42]
B
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 like you don't think about this is when we look at a BOM of a product, we'll risk purchase. Not necessarily the whole thing, but the cheapest, highest risk things 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.
- [75:00]
A
But I would have thought, you know, often these supply chain crunches come on the leading edge where you know, everyone's fighting over TSMC, you know, 3 nanometer node production capability. But you know, the auto chips at you know, much larger gate sizes are not or larger nodes are not as contended. And I would have thought that you guys are not using tippity top end cameras and lenses and memories and things like that. But that's not a panacea.
- [75:32]
B
It's like capacitors. The point I give you is let's say we ship 100,000 units. That's tiny. And so all it takes is, you know, if we need this capacitor from Texas Instruments, all it takes is Apple saying, well the iPhone 27 is going to have that capacitor. And Apple's like cool, we'll buy everything for the next three years and then we go, oh crap, we got a completely.
- [75:57]
A
But I'm just surprised you're competing with Apple for components like I would have thought their capacitors and your capacitors, I
- [76:04]
B
mean, well, capacitor is a capacitor. But so to actually know the capacitor you want, you have to have a supply chain to buy it. You have to have enough inventory with enough lead time like it is. And so what you wind up doing is like early on your designs are very simple. You buy everything from Adafruit or whatever. You buy everything from easy places where you can buy 50 at a time. And when you move to tens of thousands at a time, you start having to have designs that have four different derivatives for every part so that your supply chain doesn't have to call engineering being like this part's out. They know these parts are all sub ins.
- [76:35]
A
You're describing the scale of diseconomies of manufacturing where it's easier to buy three of something than it is to buy 30,000.
- [76:41]
B
And I never would have thought we would need like a team of people who all they do is spend money for a living, just buy stuff.
- [76:47]
A
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.
- [76:54]
B
It's like 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.
- [77:01]
A
Yes.
- [77:02]
B
It's like storm like we need to be back up. 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
- [77:17]
A
stuff to be on site when they get a Call that something is down, go repair it.
- [77:23]
B
Yeah, well, so everything's. Everything. We have really good telemetry on the equipment. So if a customer calls, something's gone. Like, we've really screwed. Yeah.
- [77:30]
A
You know, before the customer knows.
- [77:30]
B
We 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 largest cost structure in replacing equipment is the driving. Yeah, yeah, sure, driving. And so, like, if we think the part. We need a replacement in six months.
- [77:50]
A
Yes.
- [77:50]
B
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. We had to build a software company, a hardware company, and a field services business.
- [78:02]
A
Do you have parts that wear out? I would have thought the whole thing is fairly solid state.
- [78:07]
B
Most of it's, well, drones, obviously.
- [78:08]
A
Different kettlefish.
- [78:10]
B
But on the camera side, there's one part which is the IR cut filter. 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. So that literally changes twice a day.
- [78:25]
A
Oh, like something mechanically put a lens over it. I see.
- [78:30]
B
And after a couple thousand uses, the one moving part, it is a woman, and it is the only part that breaks.
- [78:36]
A
Why not just have two lenses with
- [78:38]
B
two different image sensors, too?
- [78:39]
A
Yeah.
- [78:40]
B
Bomb.
- [78:41]
A
Okay.
- [78:41]
B
No good. Like, no. No good reason.
- [78:44]
A
Okay.
- [78:44]
B
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.
- [78:53]
A
Yeah, yeah, sure.
- [78:54]
B
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. But early on in the company, 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.
- [79:15]
A
Yep.
- [79:16]
B
None of them are working. And the city got blasted appropriately for it. And they're like, well, but also like, do you really want our police department being in charge of, like, camera uptime? Yeah, yeah, that's like. That's a dumb idea. We should pay a company, I. E. Flock in this case. So just make sure the stuff always works. So it's not my favorite part of the business in that sense of. It's a lot of Stress, it's very operationally intense, but I think it's valuable to our customers.
- [79:41]
A
Yeah. How do you think about the. Right. You talk 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 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?
- [80:14]
B
Yeah, the cop out answer is like, I don't want to be in charge of deciding that. Thankfully, we have elected officials who we vote to make that decision.
- [80:23]
A
But what do you think is a sensible place for them to land us?
- [80:26]
B
I think it's way higher than we have now. I think that 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. Now I think to your question though, it's a question of where they are, who has access to them. 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 electroficial work is like, it's pretty big. 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. It's just a camera. So for me at least we should have an abundance of cameras and have 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 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. But I would challenge why not do more cameras and have a warrant restriction? Why not do 30 days of LPR data? But if you have warrant, you have a year. Yeah, you need less 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, like, there's a way for us to both be safe and maintain civil liberties. And it needs to be legislated though.
- [82:04]
A
Yes.
- [82:05]
B
I can't. Those ideas are not in line with what my customers want. They want law enforcement customers. They just want to go catch bad guys. They want to Follow the Constitution, 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 so it can change. And so we push them to be like, let's legislate this now before it becomes a problem.
- [82:32]
A
Where do you think has passed sensible rules?
- [82:36]
B
Sensible. I think Virginia's bill last year was pretty good. 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 like 30. But tomato, tomato, it's fine. I think the ACLU was lobbying for three minutes. It's a little tough. It's hard to swallow. I think 7, 14, 20 something days is like enough. There's a trade off there. 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. Customers don't want it, they need to be told to do it. So I think that was good. It also validated that this can only be used for criminal investigations, which I think is really good. While that's obvious, it's helpful to write in law, I think the only thing that I disagree with is they did say effectively there's no participation with the federal government. I think that's just. It's their choice. I think it's their choice. That's the beauty of the country, is Virginia should do what feels right for Virginia. 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 like, they can't use our technology in Virginia, which is, like I said, I live in Georgia, so thankfully it doesn't really impact me. But as a business, I'm like, I don't know if that's right. But I'm more than anything just happy they passed some legislation. New Mexico passed a similar bill this year. California has a similar ish bill. 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 data retention. 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. I'm like, who's going to enforce it?
- [84:46]
A
It's not noble.
- [84:46]
B
You might believe that. 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 this case.
- [84:56]
A
Yeah. 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.
- [85:16]
B
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. So it's like, guys, why don't you just use like cell phones? Like, well, international disaster. And it's like, got it.
- [85:34]
A
Okay.
- [85:36]
B
How often. So you look at like a land mass radio contract and it's gonna cost someone like San Francisco county, you know, $200 million. I mean, like, you're talking about that kind of money on a TCV basis. Oh, yeah.
- [85:48]
A
Wow.
- [85:49]
B
I mean, I mean, I think Murray's a really big company.
- [85:51]
A
Sure. Yeah.
- [85:52]
B
That's how he 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, man. Is that really the only way?
- [86:06]
A
Yeah.
- [86:07]
B
Could you guys just have your own tower? There's gotta be something. But you look into it.
- [86:12]
A
Is this your margin as my opportunity situation for you guys with radios?
- [86:16]
B
Maybe? Because law enforcement's unique in this case in which they really also like that they own the infrastructure. They own that bandwidth, and so they can do whatever they want with it. I don't think they do anything interesting with it, but they can. Versus if they're riding on Verizon or AT&T, they have no control over it.
- [86:32]
A
But why don't you guys just have the exact same products and have a radio in the spectrum?
- [86:36]
B
We probably should, but we gotta.
- [86:39]
A
That's my, like a VC in the board VC.
- [86:41]
B
Yeah. $80 billion company that's been in business for 130 years. I mean, I guess you did it in payments and it worked out pretty well, but yeah. So I think, like, 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 and I deal with the ramifications of the edge case or build around it, and they do that. I think procurement is exceptionally slow and exceptionally laborious. Everything goes to rfp, but the RFP is written for one vendor, so all it does is wind up taking an extra year, six months. That's like, that's. I get why RFPs exist, but they're not actually RFPs. I've never seen an RFP that's not written for one vendor. I'm sure it exists somewhere.
- [87:25]
A
Yeah, yeah.
- [87:26]
B
I haven't seen it. But what I think they do well is like, 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 like 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. I would not wish upon anyone selling to local government. It's more negatives than positives in a lot of ways.
- [87:55]
A
Yeah. And again, that procurement process has evolved for a reason and to protect against certain other failure modes. But yeah.
- [88:01]
B
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 I know you. I'm just trying to buy Stripe. That in the business world is considered very normal. In the government world, that is called illegal, which is really interesting.
- [88:22]
A
But again, it's evolved for a reason. The rules are written in blood.
- [88:25]
B
Well, no. And then you have plenty of cases where it's gone sideways. 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.
- [88:37]
A
How do you guys use treb?
- [88:39]
B
A lot of our customers. A lot of our private sector customers pay either via credit card or check. A lot of checks.
- [88:46]
A
Okay, so for the public sector stuff, that'll generally be via a torturous RFP process, NPO and something like that. But for your private sector.
- [88:58]
B
But we don't want to be in the check deposit business, you guys.
- [89:02]
A
So you use Stripe for the check functionality because no one knows about our check functionality. That Stripe can accept checks for you.
- [89:07]
B
Am I allowed to talk about it?
- [89:09]
A
Sorry, no one knows because we're bad at marketing.
- [89:11]
B
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. It's like it's a remote deposit box or whatever it's called.
- [89:18]
A
But yeah, 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 in. You can forget about those details.
- [89:33]
B
Not a single customer of ours pays via ach, either check or credit card. We do a lot of checks. I'd probably say 80%, 90% of checks, maybe higher.
- [89:42]
A
You're one of the few tech companies to mostly use stripe for checks.
- [89:46]
B
It's trying to buck the trend every day of the week.
- [89:50]
A
That's really funny. I love that you were talking about police departments maybe being over fixated on the.01%, 0.1% cases. Does that apply to a common critique that you hear of police department procurement is the sort of militarization of police departments. And what we really need is a Bearcat for this town of 20,000 people, which is like an armored personnel carrier,
- [90:14]
B
like a $3 million vehicle. When it's like, why couldn't we just get an F150?
- [90:18]
A
So do you think that applies also to kind of the shiny stuff?
- [90:21]
B
Oh, yeah. I mean, you look at. Early on when we were building the company, they would. We'd get the question of like, well, can it. Can a track. Can your license plate reader work on a car going 175 miles an hour? 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, 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.
- [90:56]
A
Really? Huh.
- [90:58]
B
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 like, you know, an amateur racing track and just drove around in circles at 120 miles. We emailed the employees and we were like, who owns a car that goes really fast? And that was actually kind of funny because a lot of people were like,
- [91:19]
A
what car do you use to test this?
- [91:20]
B
We had these. There's some fast cars putting it. Teslas, Rivians, Some other nicer cars drive really fast. And that was a fun day because I put the cameras up and do it. But did the cameras work out of
- [91:32]
A
the box or did you have to tune the performance yeah. Okay, so it worked.
- [91:35]
B
They're the only place where we had to make one modification, which is kind of interesting. We deploy a radar. So on really busy roads where our angle of incident is particularly tight, we can't shoot super far down. We have to shoot at a sharp angle. We have a radar attachment that we tilt backwards to notify like the car's on the way, like, get ready, which helps. But that's like a very, like, far edge case, whereas the camera doesn't actually.
- [92:00]
A
You prime the camera, essentially.
- [92:02]
B
Yes. To get ready for a car coming.
- [92:03]
A
Huh.
- [92:04]
B
I'm sorry, the camera is offline unless there's a vehicle.
- [92:09]
A
I see. So you boot it up and that's a power saving measure.
- [92:14]
B
Yeah. The most expensive thing we do is take a picture. Second, most of the thing we do is send stuff to the cloud. Third is just like being a computer turned on. And so it's similar to your iPhone turning your screen off.
- [92:27]
A
Okay.
- [92:28]
B
So we added the button to take a photo right away.
- [92:30]
A
The continuously running radar is very low power.
- [92:33]
B
It's negligible.
- [92:34]
A
I see. That's cool.
- [92:36]
B
Yeah, that was a fun one.
- [92:37]
A
We were talking about hardware previously. Buzz, what's building your own drones been
- [92:42]
B
like, a lot of fun?
- [92:45]
A
Sounds fun.
- [92:45]
B
No, it's fun, but I have kids and you have a kid. It's really fun to build a product that your kids understand. It's like we drive around Atlanta and my son will count the cameras from home to school, or we're going to the airport, or we'll go to the park. And I love that he can actually, like, understand what dad does.
- [93:10]
A
Yes.
- [93:11]
B
I'm not sure if you've taught your son, like, how I'm screwed on those accidents. Yeah. It's like, yeah, we process the world's payments. And so when you show him a drone, he's like, oh, this is so cool. And he has like a little miniature drone.
- [93:24]
A
Well, also, you not only do drones, but you do drones to catch bad guys. Yeah, yeah.
- [93:27]
B
It's like very compelling.
- [93:28]
A
Very early age.
- [93:30]
B
Yeah. To be clear, like, he'll watch Paw Patrol and be like, that's what dad builds. Like, 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 Warhog. Whereas traditionally, you built a plane thing. Yeah. What kind of missiles can we add? And they were like, no, no, no, let's design the best missile. It's very precise, very Big, and then we'll figure out how to fly it. 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. It's like if I showed you, I could show you the payload the next time you're in Atlanta. Or we could fly one out here. It's like 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. We can read a license plate almost a mile away. Like crazy specs, great thermal. Then we're going to get 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 a payload, we have this airframes, we have aeronautical engineers now. It's been fun to grow the engineering team, an imaging team. You think about the dock that it lives in. It's effectively a commercial grade H vac system. Like the drone lands, it needs to be cold, it needs to be hot, it has to charge. If you know anything about lithium ion, lithiumion doesn't like to be too hot or too cold. So you gotta keep that well conditioned. It's like this 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.
- [95:04]
A
Yes.
- [95:05]
B
And that's like, that's the fun part of this stuff. Yes, because everything else is, you know, selling is good, but like building stuff's fun.
- [95:11]
A
How many drones do you have out there in the world?
- [95:13]
B
We don't discuss that one. But.
- [95:15]
A
But decent number.
- [95:16]
B
Yeah. No, it's hundreds of cities that are
- [95:18]
A
flying, are flying drones. Flight drones. That's cool. It's funny, when you talk about the, the A10 warthog, you're reminding me of the Boyd book by Robert Coram, which I only read recently, but is like one of this kind of Silicon Valley canon. And everyone talks about it and everyone talks about him in the context of his OODA loop, you know, orient something, decide, act. But I think that's actually kind of overrated. And actually the main reason Boyd is interesting is, is helping the Pentagon procure better planes. I'm just reminded of that with the Warthog and also 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 and they wanted a high top speed and they really judged planes on specs. And actually the fighter pilot joke is that there are only two throttle settings in a dogfight. Maximum full military power or throttle's idle. 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 A10 warthog, because he got them out of the mindset of
- [96:33]
B
just kind of speeds and feeds well. And that's like, for us, the spec we track is like time on scene.
- [96:38]
A
Yeah.
- [96:38]
B
And so one of the reasons why we care so much the 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 zipline or something else, like actually physically in there matters, but for us it's just about time. On virtual scene.
- [96:56]
A
Yes.
- [96:56]
B
So that's what we measure ourselves to. So that's why we fly high, because like physics allows you to see farther. 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 these designs were around that use case versus like, you know, I'm sure zipline went through a whole separate use case of like, what's the max payload and all that kind of stuff.
- [97:16]
A
So how many drones does a city the size of San Francisco need?
- [97:20]
B
12.
- [97:21]
A
Okay, so a very small number.
- [97:23]
B
No, I mean our average drone can cover a 30 square mile radius and get there within under a minute. And thankfully, in a knock on wood, like, there actually aren't that many 911 calls that merit of response. So we look at it both ways. We look at it in terms of geography and then 911 density. So in 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. But even in our most dense customers, it's pretty rare that they fly two drones at once. It happens. But it's like, I think our busiest drone is being flown 90 hours a week. That's a lot of flight time.
- [98:03]
A
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?
- [98:09]
B
Yeah, there's like, it lives in the dock. There is some. There's debate of whether a drone should be in the air at all times.
- [98:17]
A
Does that actually save you meaningful time
- [98:20]
B
being in the air? I would save a lot of time.
- [98:21]
A
Oh, really?
- [98:22]
B
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 unwarranted search. So it got killed. And so we're very conscious. Like, we have a other part of our business that is interesting now at scale is like, we have a full team of constitutional attorneys, 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. That's like, cool idea. Let's actually make sure this doesn't violate the Constitution.
- [98:54]
A
Look up the fourth amendment here real quick.
- [98:56]
B
Yeah, let's just like double check this thing. And so when you look at the drone, like, we believe. And 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. If there's a gunshot, if there is like, we've 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.
- [99:24]
A
It's hard. Like a lot of this precedent, as new technologies come along, people reason by analogy of cars, somewhat like your house, but somewhat different. Whatever. Isn't a drone flying around just like a police cruiser on its patrol?
- [99:43]
B
And I'm not an attorney, neither am I never stopping.
- [99:47]
A
Yes.
- [99:47]
B
The other analogy, that would be the butterfly effect, which is like, when things are much, much cheaper and much, much easier, historical precedent gets thrown away. And so take the helicopter example. You could say, oh, well, helicopters fly sometimes. But. Yeah, but helicopters are so expensive, it's not practical to have 24. 7 aerial coverage with a drone. It's not impractical. 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 at the horizon the whole time. We don't want to look in your backyard. That's like, we feel really strong. And that's not a law. That's just like our point of view of where the law should be.
- [100:24]
A
Yes, yes.
- [100:24]
B
So we'll build a product for that.
- [100:25]
A
Got it.
- [100:26]
B
And then look at if the operator wants to tilt down, that's their control. But as a default, we're flying straight up.
- [100:31]
A
That's very interesting. Last question. You know, so 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 kind of synthesize all the information they have. Just what comes next. What future product ideas are you playing with? We're doing now.
- [100:52]
B
So I think about it, we talked about this earlier. Failure for Flock is prison, population goes up. It's actually like really bad. And we look at, you know, the products today are very much focused in the middle of a crime. A crime has already happened and therefore we should solve it. And that's really good. And I think we're not done, but we've, 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 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 growth partners to those businesses. Because if we want to convince that 16 year old to not commit criminal, there does need to be jobs, jobs that like a 16 year old can get. And so we deploy capital in restaurants, nail salons. Pick your business that you can be 16 and work at easily. And we want more of those to exist. Last year I think we were at 21% IRR. So it's not a bad business. I think Fox stock's done a lot better than 21%. But I feel really strongly 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, but for that. So I'm like, 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. I think that's crazy. 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 is an opportunity, don't know yet what it is to say, well, 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 or 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. That's bad. But prison can't be the answer. It just doesn't work. The whole concept of prison will never work. 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 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.
- [104:03]
A
So fewer crimes, fewer people in prisons.
- [104:05]
B
Yeah, that's the end goal.
- [104:08]
A
Thank you.
- [104:09]
B
Thank you. It was fun.
- [104:09]
A
It was awesome.
- [104:10]
B
Yeah.