Kevin Ruelas: From Service to Calling — Building AI That Serves Justice

Intro: Broadcasting live from the Business RadioX studios in Houston, Texas. It’s time for Houston Business Radio. Now, here’s your host.

Trisha Stetzel: Hello, Houston. Trisha Stetzel here bringing you another episode of Houston Business Radio beyond the Uniform series. Today’s guest is Kevin Ruelas, founder and CEO of RAPTR Analytics, a geospatial intelligence and AI company transforming how law enforcement analyzes complex data. Kevin is a seasoned serial CEO whose career spans global operations, national security, and advanced analytics. Early on, he helped scale a major Middle East contracting operation from 0 to 4 billion in just six years. Operations across Iraq, Turkey and Kuwait. He later founded Synectics, developing cell phone tracking technology now used by US federal agencies. RAPTR analytics was spun out of that work. An AI driven SaaS platform that helps law enforcement analyze massive data sets, identify patterns in real time, and turn intelligence into courtroom ready evidence. Kevin, welcome to the show.

Kevin Ruelas : Thanks, Trisha. I’m happy to be here.

Trisha Stetzel: I’m so excited to have you. And I would be remiss if I didn’t mention that Derrick Zoller was the one that introduced the two of us. And by the way, if you haven’t seen his podcast, you guys, it dropped December 2nd. So go out and take a look at that. All right, Kevin, before we even get started, I’d love to if it’s okay, just ask you to tell us a little bit more about you.

Kevin Ruelas : Sure. Well, I actually grew up in California until I was 12, when my dad, who had retired from the Foreign Service and retired from the Foreign Service, and we went to live in Honduras and El Salvador and got to start my international life, I guess, at an early age of 12. Um, and then later, uh, came back to California and went to school, where I met a bunch of guys playing with this thing called Army ROTC, decided it was the right choice for me and jumped right in. Uh, became an infantry lieutenant. Many, many moons ago, uh, and unfortunately blew out my knee and only served for six years in uniform. Uh, had, uh, well, three knee surgeries and eventually separated. Uh, in the early 90s. I went off to do logistics for ten years in the private sector, uh, until the second Gulf War kicked off. And somebody asked me or a CEO at the time that I was working for, to go to college And figure out what was going on with port as it was melting down as the cargo couldn’t get in. So I went over and I started working with a local Kuwaiti company, and eventually they asked me to join them and started division working on military and logistics and and defense work. And to be honest, you know, I worked at that logistics company for about ten years and was getting really kind of tired of the corporate grind and the growing of a company or not growing a company, but being part of a cog in a company and the opportunity to start a new company that was focused on military and defense was super exciting and super, uh, back to my roots. It really made me understand that I was missing being in uniform. I missed the sense of purpose.

Kevin Ruelas : I missed part of being part of that bigger, uh, brotherhood. And so leaving that company after ten years and joining basically a company with no employees and starting from scratch, as you said. And we scaled. We did, you know, two guys and I had 20 then I had 200, then I had 2000 and I had 20,000. We just kept growing and growing and growing. We’re the right place, right time. I mean, the Gulf War obviously right at the beginning in oh seven or sorry, oh two. Um, and we’re the boots on the ground that needed to be there. And I was supporting, like I said, the military, not just Army, but of course Navy and Air Force. And we started supporting international partners. We had contracts with UK, France, Japan, etc.. And so that’s how it scaled and it grew and it grew and grew. Uh, unfortunately, I didn’t I didn’t own it. Uh, I was working for the Kuwaitis. Uh, after a number of years, I took that company global, uh, as you said, over a it was actually a billion and a half in revenue and moved the headquarters to D.C.. I got kind of frustrated and decided it was time for me to move on. And it was then that I took over another company for another, uh, family business and eventually sold that for them. Bought my own company, which you referred to as synthetics, started another company called Defense and Government Services and eventually spun out what is now RAPTR Analytics from all of that. And we can get into that again in a minute, uh, as I connect the dots for you. But that’s kind of how I ended up here after, uh, I guess 20 now, 30 years, uh, since I was in uniform. Wow.

Trisha Stetzel: Yeah. So, Kevin, you really have led, like, some of the most complex environments imaginable. Uh, how did those early experiences shape the way you think about leadership and risk today?

Kevin Ruelas : I think the thing that really stuck with me the most was that rocket ship ride and growing of that company in Kuwait, in that I had to kind of imbue my little cell. Like I said, I literally had two guys to start and then I had 200 and eventually it just, you know, kept scaling. But in order to properly lead that organization and, and make it into what I wanted it to be, I had to really create an ethos, a dedication, and then empower those employees at the time, um, to take what I was trying to create and take it to the next level and then create another level and then create another level. And you know, the the typical kind of like pyramid hierarchy structure is pretty typical, where it all eventually bubbles up to the top, but you still have to push down through all those layers, you know, two reporting to four, four, reporting to eight, eight, reporting 12, whatever that number ends up being, and getting them all to understand what we stood for and what we stood for was military, defense, logistics. And that’s what our mantra was, and that’s what we had everybody kind of rowing in the same direction to do. So the the early scaling really taught me how to lead by example, lead through others, and lead all the way to the bottom line or the bottom of the where the rubber meets the road.

Trisha Stetzel: It’s so important. So how do you think your military experience. I know that’s what led you back to do this. Was that that want or need for the brotherhood that you were missing? But how did your military experience and background really teach you or give you the skills that you needed to get that rocket, that first rocket ship off the ground?

Kevin Ruelas : I definitely think, um, I was actually at a kind of a crux when I got out of the Army as an infantry officer. You know, a lot of the your listeners are ex-military as well, and they can probably relate, depending on what their MOS or what their branch of the service was. A lot of those have a civilian counterpart, for example. Had I been a transportation or logistics officer in the Army, that would have been a natural transition for me to go into transportation and logistics in the civilian sector or if I was an MP. A lot of those go into law enforcement, etc., or I have a cousin who got out of the Navy as a radar technician. So now he works on radar, right? Unfortunately for infantry, there’s not that one for one. Like, what do you do with infantry? Well, I learned how to shoot guns, and I learned how to shoot mortars and a lot of the security type stuff. So there’s that aspect. But more importantly, what I learned most was how to lead troops. I like to say my favorite job ever in the army was an infantry platoon leader.

Kevin Ruelas : Those 40 guys, they were my, you know, wake up every morning and go to bed every night. Team that I that’s all I thought about. How to lead them, how to motivate them, how to get them to go the extra mile. How to get up at 4 a.m. when I didn’t want to get up at 4 a.m.. How to do night operations after night operations after night operations when I didn’t want to do it either. But you had to leave. You had to motivate and you had to inspire. And I think it’s that aspect that I was able to put into my resume as a, um, I guess, first lieutenant that I’m getting out of the Army saying, you know, here’s what I bring to the table, I bring leadership, I bring, uh, inspirational leadership, and I and I can motivate. And that’s how I got my first job. And I think it was that that eventually led me to keep going and become a ever bigger and bigger leader of of people. Um, it’s going all the way back to that infantry training I had way at the beginning.

Trisha Stetzel: Yeah, absolutely. I like to say all of us veterans, we just get stuff done sometimes the middle s I use a different word, but today we’ll say stuff. We know how to get out of bed. We know how to GST.

Kevin Ruelas : Yeah. And you know, you referenced Derek earlier and I gotta give Derek kudos because he’s always been that get it done kind of guy. And that’s why we get along so well because I know if if we’re on the phone and he says I’m going to do something, then he’s going to go get it done and vice versa. It’s get stuff done.

Trisha Stetzel: Yeah, absolutely. Gst, GST. All right. I want to roll a little forward if that’s okay. And let’s really jump into uh, RAPTR Analytics. It was born out of real operational needs as I mentioned earlier. So what problem were law enforcement agencies struggling with that really pushed you to spin this out into its own platform?

Kevin Ruelas : Yeah. So I actually acquired synthetics 11 years ago, and I was very attracted to it because it’s a very unique technology. There’s no other company in the world that does what synthetics does, which in a nutshell is find and track cell phones in real time. So Synectics has devices that we can’t get into all the technical aspects of it here, but essentially they’re honing in on the cellular, uh, radio frequencies or cell signals and allowing the operators to track that cell phone to its origin. Uh, over the years, we’ve now gotten to the point where we can integrate that into our mapping systems. Uh, some of the veterans may be familiar with attack, uh, for example, where we can put dots on a map now and we can say, okay, that’s where the phone is. If you have two of our trackers where those lines of bearing intersect, that’s where the phone, uh, target is. And so when, when I acquired it and based on my military background, I really focused on my military customers. So special forces, whether they’re Army or Navy Seals, uh, even a, uh, afsoc. They all use our equipment to find bad guys. And so that’s what I really delved into or dove into, because that’s what I knew. Right? That was the uniform I had worn. And at the beginning, it was very much a hey, law enforcement, if you want some of this, you know, we have this for for your use as well. It’s, you know, military rated. It’s, you know, used by our brothers in arms in the military side.

Kevin Ruelas : But you’re welcome to use it on law enforcement side. And I didn’t really focus on them as a customer initially, but over time, they obviously are a lot bigger in terms of all the police departments around the country. There’s 8000 different police departments, sheriff’s departments, agencies, federal agencies. And once you start to aggregate all those and they’re all looking for bad guys too, it starts to become a very large customer set with a little bit different problem where they’re prosecuting the people that they’re pursuing. They’re looking for, uh, the legal aspects of what they’re doing and making sure it’s admissible in a court of law. They’re building up a case against somebody who did something wrong, and they need to know. Where was the phone last week? Where was it when the crime was committed? Where was it when or what are the phones were near when they were doing their bad deeds? So the use case started to shift to not just today’s intelligence. Go find the bad guy today, but more of the historical information that we can derive from cell phones now. Um, so we started working with them to help them get essentially with a warrant that data from AT&T, Verizon, T-Mobile, etc. and get the information that is available from the carriers about the cell phones with their time, date, stamps and locations and all these important aspects. But it’s a lot of raw data, raw data that needs to be analyzed, raw data that needs to be then overlaid over a map, and then start to look for those industry dependencies and similarities.

Kevin Ruelas : And the more we kind of went down this rabbit hole of how do we connect the dots for law enforcement, the more I started to realize, okay, this is a totally different solution. We’re not now creating a box to find a phone. We’re creating a software solution that is geospatial intelligence. It’s looking for dots on a map and looking at them over time and then looking for inferences. And how do they interrelate and what can we glean from all of that? And then the more I started going down that road, the more I created or started thinking, okay, we need to create a separate company that just focuses on this because it’s a different problem. And once I went that way, I also started thinking as AI became the new buzzword of the day, how do we apply artificial intelligence to this? And the more I started to understand that, the more I realize that, well, what the police are doing is doing the same analysis over and over and over again that a computer can do faster and more efficiently looking for those inferences, looking for those probabilities, looking for all the dots that connect. That’s what artificial intelligence is really all about. So I said, okay, let’s create RAPTR analytics with AI as its base. Let’s get all the data into it from the, um, AT&T and Verizon. And then we start adding in Facebook and metadata and all the information that’s out there. And then let’s start applying artificial intelligence. And RAPTR was born.

Trisha Stetzel: Wow. Well, we could sit here for like another hour and talk about all of the stuff that’s so exciting. We’re about halfway through our conversation, and I’ll bet that people are very interested, either in connecting with you or learning more about what it is that you’re doing. Where’s the best place that folks can go and find out more? Or read more about the work that you’re doing? Kevin?

Kevin Ruelas : Definitely, yeah. As as most companies, we have the typical WWE analytics or analytics. Com. I’m in LinkedIn, of course, and we also have the other companies that I have which is synthetics. Com. I think I’m actually wearing a synthetic shirt today. Um, so um, synthetics is where again we have the hardware wrapper analytics is on the software. And then my name, Kevin Ellis at LinkedIn. Uh, all those three are great places to go looking for more information. And all of those websites will have info at. Or you can always reach out to me directly. You can say, you know, I saw you on Trisha’s show and I’d like to connect with you and that would be okay. At Synthetics Cross at RAPTR Analytics. So I’m also like like I said, LinkedIn where you can connect through there.

Trisha Stetzel: Okay. Fantastic. And as you guys know, I’ll always include, uh, the links in the show notes so you guys can point and click if you’re sitting in front of your computer. If you aren’t, then you’ll find probably easiest. Kevin rules on LinkedIn. His last name is spelled r u e l a s so that you can find him there. Okay, so, Kevin, um, I want to talk a little bit more about AI because you led to that. The base of, uh, RAPTR Analytics is really wrapped around this idea or this this real thing. It’s not an idea. This real thing called AI. I’d love to know how that really plays into, um, our our law system. Uh, accuracy. Transparency. Accountability. So how is that working now inside of. Our law system?

Kevin Ruelas : Yeah, that’s that’s a great question. And and I really have to kind of be careful to when I’m explaining how AI is being used for our law enforcement customers, that a lot of the customers and a lot I guess the public first go to the movies like Minority Report or some of these other things where like, oh, AI is going to start trying to predict who’s who’s who’s a criminal, who’s doing bad things. And I have to say, no, no time out, time out. We’re not we’re not doing that. We actually are using it very methodically to look for, as I mentioned earlier, dot connections or connecting the dots or look for inferences or look for similarities. Ai is not going to be saying that’s the bad guy, or at least my, uh, use of AI. So for RAPTR Analytics, what we are creating is the. I like to think of it as a detective that is going to give suggestions by saying, go look over here. You know what this actually is, is a cause for concern because we see a pattern or we see AI. Ai sees a pattern, or they see or we have seen this pattern enough that we think that there’s something that you should go look for further. And allowing the detectives to be, um, the decision makers in the process of what they’re going to, uh, get more information about what they’re going to dive deeper into. So, uh, so within RAPTR Analytics, there are, uh, color codes, uh, you know, your typical red, yellow and green where, uh, if something pops up red, you want to go and get more information about what the what’s going on with the red? Yellow? There’s some connectivity here. We’re not quite sure if that’s going to be relevant. And then of course, green is like 90% of the data is going to be not really relevant to what we’re looking at.

Kevin Ruelas : But that’s going to save law enforcement time because they’re going to spend those 90%, uh, error minutes not wasting their time. So there’s that aspect of it. Um, but that’s I say that’s kind of the middle tier. There’s actually a pre tier, which is the investigation side. And um, trying to figure out all of the, um, the warrants and the information and getting that data in and out. A lot of that can be automated through artificial intelligence. Um, where, like I said, you have 8000 police departments. Each of them are trying to figure out how to do a warrant to AT&T or Verizon or now Tesla and all of the other data, uh, vehicles that we can get. All of them can be automated using AI for the warrants. Delivering warrants. Receiving the warrants. Receiving the information. So there’s a whole front end of the investigation that can be artificial artificial intelligence. The middle part of the investigation I was referring to. And then on the back end, which is the court and the admissibility aspect of it, where, um, within RAPTR, we’re creating reports, standardized reports, where artificial intelligence can pull out, um, data that is court admissible to show charts and graphs and pictures and, and by using the computer system to do everything. You’re now also having a chain of custody. All these things you hear about on, you know, the FBI files, etc., you’re connecting all the dots for the law enforcement customer from the initial investigation, through the actual investigation to the courtroom delivery of the information. And all of that can be done within RAPTR Analytics and all. Sorry, all of it as part of artificial intelligence.

Trisha Stetzel: Wow, that is amazing. And picturing as you’re talking through that, uh, you know, in the movies when they’ve got all the photos and the strings with the tax in between, like, the AI is kind of helping put those strings where they go so that they can go and take a look at all of these other options. Right. Uh, based on the data.

Kevin Ruelas : Yeah. I’m going to start using that analogy, because everyone’s seen one of those boards with the strings and the pictures I love it.

Trisha Stetzel: Yeah. Great. Look. Look how good I am.

Kevin Ruelas : I like it.

Trisha Stetzel: So thank you I. Well, and I love this conversation. It’s so, um, it’s really interesting. And I think it’s also important to know that we’re able to use technology in such a way that we’re saving time, uh, in the law enforcement space, right, where the our first responders can go and do the things, and detectives can go and do the things that they need to do without sitting in front of stacks and stacks and stacks of paperwork. Uh, like we see in the old movies.

Kevin Ruelas : And you hit the nail on the head. That’s the last part of the equation that that I didn’t really, uh, hit on, which is, um, part of our sell to law enforcement is time savings. And how much more time they can get back and be out doing police work versus the analysis, report writing, creating the charts and the graphs on the back end, the writing of warrants on the front end and the analysis in the middle. All of that takes time and energy that law enforcement obviously cannot spare at this juncture.

Trisha Stetzel: Yeah, absolutely. So maybe a hard question, but just thinking into the future, looking five years ahead, how do you see AI and geospatial analytics changing law enforcement and public safety?

Kevin Ruelas : Well, I like to think that it will become smarter and it will start to learn more and more. One of the things that we have to be very careful of, again, with, with, you know, chain of custody and court records, etc., is we have to be careful that we’re disaggregating the data that, you know, Trisha’s phone is this phone number. I don’t necessarily need that for all the police departments to know, but they need to know the inferences of what the phones do or what the data does. Um, so we have to be very careful to separate that and make sure artificial intelligence is using only the, um, disassociated data and looking for the inferences and then learning from each other so that LAPD can learn from NYPD, for example. And again, it’s not Trisha’s phone number. It’s the data’s, uh, intelligence that we’re learning off of. So it can get way smarter, and it can learn way faster than we can. And it can learn from each other over time. We just have to be careful how we set that groundwork. And, you know, create those platforms to to do it properly.

Trisha Stetzel: Yeah, absolutely. I know our time has flown. And I have one more question for you. And it’s about the responsibility that comes with this kind of power. So talk to me about or talk to us about leaders for leaders building technology that carries real human consequences as what we’ve been talking about here today. What responsibility comes with that kind of power?

Kevin Ruelas : Well, I think most people now are very wary of artificial intelligence or are learning to become very wary and not taking everything that they get out of the computer. When you ask Google, Gemini or ChatGPT or all these different platforms for an answer, everybody’s starting to understand that you’re going to get ghosts. You’re going to get references to data that’s actually false or I’ve seen them, you know, give you this report says this and that and said, okay, well tell me more about that report. And that report was actually made up by artificial intelligence. So everybody has to really understand that no matter what the detective or the analyst needs to be reviewing everything and making sure that there is not a ghost in the machine, there’s not something untoward in there. Um, all throughout the process, they can’t just press a button and boom, we have the bad guy. Uh, I don’t think we should ever get there. We need to be, like you said, very wary, and be very careful of what the future could bring so that we don’t end up in that Minority Report movie that we were joking about.

Trisha Stetzel: Yeah, absolutely. Kevin, this has been such an amazing conversation. I appreciate you joining me today. What would you leave? You know that most of my listeners are veterans, and a lot of them are in the entrepreneurship space. What would you leave them with today, just based on your service and the success that you’ve had in, um, outside of the service?

Kevin Ruelas : I like to say that, um, well, there’s a very interesting book that I don’t know if you’ve ever heard Chip Conley describe it as a, um, a pyramid or a hierarchy where at the base you have a job. And then for most people, there’s a career. And then the pinnacle of it is called is a calling. And I feel like a lot of us who wore the uniform and continue to serve had a calling. And if you can marry your calling with a job or with a company, then you’re going to hit. It’s not work as they say, right? Then you don’t feel like you’re working every day. You’re you’re satisfying your calling and hopefully making some money doing it, and that that’s all you can hope for.

Trisha Stetzel: Yeah, absolutely. What beautiful advice, Kevin. Thank you again for being with me today and sharing your time.

Kevin Ruelas : Thank you. It’s been a pleasure.

Trisha Stetzel: That’s all the time we have for today. If you found value in this conversation, please share it with a fellow veteran, entrepreneur or Houston leader ready to grow. And be sure to follow, rate, and review the show. Of course, it helps us reach more bold business minds just like yours and your business. Your leadership and your legacy are built intentionally at a time. So stay inspired, stay focused, and keep building the business and the life you deserve.