The Exchanges

Q Where do you think has passed sensible rules?

A Um, sensible. Um, I think Virginia's bill last year was pretty good. Um, it defined, it did a few things well, um, and one thing I don't agree with. What it did well is it defined, uh, a modest data retention period of 21 days. I think that's fine. I like 30, but tomato, tomato, it's fine. It wasn't, I think the ACLU was lobbying for three minutes. It's a little tough. It's like hard to swallow. Uh, I think, you know, seven, 14, twenty-something days is like enough. There's a trade-off there. Um, they mandated, uh, formal auditing, which I think is great. Enough of our, not enough of our customers audit themselves on a regular basis. We can build software to make that easier, but we need to be pushed to do that. It was like, customers don't want it. They need to be told to do it. So I think that was good. Um, it also validated that this can only be used for criminal investigations, which I think is really good. Well, that's, That's obvious. It's helpful to write it in law. I think the only thing that I disagree with is they did say, you know, effectively, there's no participation with the federal government. And I think that's just, it's their choice. I think it's their choice. And that's the beauty of the country is like, Virginia should do what feels right for Virginia. But I worry about the types of cases that you, you don't want to read about on the news that tend to get so…

AI assessment note: “I think Virginia's bill last year was pretty good.”

Q That's very interesting. Last question, you know, so you guys have grown with cameras out there, uh, in cities now getting into drones, uh, building the software OS. To help law enforcement agencies and others kind of synthesize all the information they have. Just what comes next? What future product ideas are you playing with? We're doing it now.

A So I think about it, um, we talked about this earlier, um, failure for flock is prison population goes up. It's actually like really bad. Um, and we look at, you know, the products today are very much focused in the middle of a crime. A crime has already happened and therefore we should solve it. And that's really good. And I think we're, We're definitely 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? Um, and that actually doesn't necessarily look like software. It's like one of the interesting things that we started last year is what we call our Thriving Cities Fund. It's probably an analogy similar to your, like, Stripe Press, which is like, it's never going to be the core of your business, but like, you feel really good that it's a part of your business. And so when we go in places like Greenville, Mississippi, we also commit to deploy capital as, as growth partners to those businesses. Because if we want to convince that sixteen-year-old to not be a criminal, there does need to be jobs. Jobs that like a sixteen-year-old can get. And so we deploy capital in, you know, restaurants, nail salons, like, pick your business that you can be 16 and work at easily. And like, we want more of those to exist. Um, you kno…

AI assessment note: “what we call our Thriving Cities Fund.”

Q um, uh, 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 want to say super controversial, but it ends up controversial from a privacy point of view. And so, I don't know, is, is that take too generous? Is there a steelman of the other side? Why is it?

A There 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 gonna be controversy of some degree. Like, I, I'm sure people, 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, people hate every company. Um, maybe they hate us more. I don't know. Um, I, I think there's a few things that make it for the, for the steel man argument. One is you can see it. All right, 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 to 30 years ago and said, imagine these private companies tracked your location in real time and sold out to advertisers, we'd be like, that is unacceptable. But because we can't see it, we kind of let it go. Um, we have this perception of anonymity or being anonymous.

AI assessment note: “I think there's a few things that make it for the steel man argument.”

Q Um, okay, I have so many more things to, um, to go into kind of jumping around, but I like this. Um, how's the business evolved? So you're now, you said around five hundred million in ARR, uh, selling to both law Enforcement agencies and, uh, corporates. Just have there been interesting changes in how you monetize? Is it just a question of scaling up?

A Yeah, I mean, I'd say the, the biggest challenge is, you know, two, three years ago, we were single product, single customer. Like, we had our neighborhood business. It was growing 20, 30% year over year, but it was kind of operating, and law enforcement was, was going over there really fast. We had one product, and then maybe made a mistake, uh, I, I know, um, Uh, RJ from Rivian was here, uh, some story, like probably built too many products for too many customers really quickly. Uh, and in hardware, that's really expensive. Um, hardware tends to follow this J curve of like huge capex investment up front to get the thing going, and then you monetize and it actually winds up being.

AI assessment note: “two, three years ago, we were single product, single customer.”

Q Yeah. What else has made, what else has gotten worse from an offense perspective?

A Um, I mean, this is one that's like a, you know, I don't know if I have strong feelings on this, on this topic, but this, this concept that we, we appropriately hold local law enforcement to a very high standard, um, of accountability and audibility, and I think that's very good. Yes. The downside is like, we don't with criminals, and so as a citizen, you don't be the victim of a crime, you get really frustrated that they're not working hard enough, and it's just very, really that. It's that they don't have the tools, they don't have the data, or they're not legally allowed To get to the data. And the warrant system is a very, 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? Um, and the example of the, the framework that we use is, I don't know how you land this, is that the severity of a crime should be commiserate with the sophistication of technology. And I'll give you an example. Facial recognition. Hot topic. There are thousands of cities in America that have banned law enforcement from using facial recognition. John, facial recognition is not bad. That's the 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, uh, crimes…

AI assessment note: “thousands of cities in America that have banned law enforcement from using facial recognition”

Q That's right. How do you measure very online?

A Oh, let me give you an example. Um, 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 of years ago, right? Like during, during COVID. And she was like, Garrett, These kids are just killing each other. I was like, what? She's like, yeah, they're, they're literally getting in their car and just shooting each other. I'm like, why? I'm like, oh, because this guy posted a picture of him with that guy's girl on Instagram. 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. Like, that's not normal. That's not normal behavior, and it wasn't normal before COVID, and it happened a lot during COVID, and then it's largely gone away. But it was a very specific social phenomena where the, the race to violence was so dramatic. It was so scary.

AI assessment note: “let me give you an example... this guy posted a picture of him with that guy's girl”