Jake Aaron Villarreal: I'm Jake Aaron Villarreal, born and raised in Silicon Valley, and here to take you behind the scenes to share what it's like to be a startup founder, the journey they're on, the problems they face, the products they build, in an effort to make our lives better. I'm excited to have with us today Ryan Joyce, co-founder and CEO of GenLogs. Ryan, welcome to the show.
Ryan Joyce: Hey, thanks very much, Jake. Great to be here.
Jake Aaron Villarreal: I'm excited to have you. Ryan is not just a CEO. He spent 15 years in the US intelligence community conducting counterterrorism operations throughout the Middle East. He likes to joke that he used to track terrorists, but now he tracks trucks. So, what is GenLogs? It's a freight intelligence platform that applies AI to a nationwide network of sensors, commercial, and open-source data sets to track commercial truck patterns. GenLogs unlocks dark carrier capacity, combats fraud and theft, and unveils coast to coast freight lanes. So, we're excited to have you here today, Ryan, and also excited to learn more about how your company is applying AI and helping the industry in general. Before we jump in here, uh, where are you calling in from today?
Ryan Joyce: Today, I'm right outside of Washington DC in Virginia. Our company's based in this area.
Jake Aaron Villarreal: Hundreds of AI startups are launching every month, battling to build their founding teams. As a leader, your job is to get results. When it comes to hiring, that's where it gets tough. So, you go out and you try a recruitment firm, but they don't understand your story. They're off target. And when they send you candidates, it's a waste of time. We believe you should never have your time wasted. That's why we launch Match Relevant, because your story is more than just an open role. It's your founder's journey, the problem you're solving, the product you're building, and why it matters. When we work with companies, we make sure we understand your whole story. So, we go out and do a search. We're on target. It's worth their time. They're interested. And more importantly, it's worth yours. And when it comes to hiring engineers, we work to make sure we get it right. By deploying a team of seasoned CTOs that have built some of Silicon Valley's best companies that can collaborate with you in the technical interviewing process, they can be a sounding board or they can run it for you. When it comes to building teams, there's no time to waste. Let's make it count. If you have a role that needs to be filled, book a time with a hiring guide at matchrelevant.com and learn how we do it.
Very cool. I love that area. I used to live on the east coast in New York and got up there quite a bit. So hopefully it's not too cold. I know it's uh getting cold out here on the west coast, but um...
Ryan Joyce: No, we actually have a beautiful day today, so I think I'll go for a run later and take a little bit of break from the emails.
Jake Aaron Villarreal: I love that. Very cool. Well, um before we talk about your company, let's talk a little bit about um you and your origin story. How did you, how did you get into the entrepreneurial focus of your career and maybe take a step back and, and kind of growing up as a kid? What type of kid were you? Were you a business kid? Were you selling things to your friends? Like walk us through that a little bit.
Ryan Joyce: Yeah. Well, I grew up a Navy brat. Uh my dad was an F-14 uh backseater. So, he was flying the same jets you'll see in any of the Top Gun movies. So I was born on the west coast, moved all over. And by the time I was kind of age, let's say in that sixth grade to eighth grade range where you're kind of formative. We were living right on the US Naval Academy. And it was there that one day my dad uh took us all... I have three siblings and we all hopped in the car one day and we went to Costco and he bought us a large cooler, some lemonade, and a few cookies and brought it back and we opened up our first lemonade stand. And I was kind of addicted to this idea that you could take some raw inputs in one side and out the other side. People would come along and actually pay us money.
And we got to the end of that first day that we had this lemonade stand up. We made about $20, let's say. And he said, "Look, you can either split it among the four of you, so you each get five bucks, or you could take that $20 and reinvest it back into the business, and I'll drive you back to Costco. We can buy some more supplies and you can do it again." And even back then, we kind of did the math. We're like, "Let's reinvest." And so that's what we did. We put it back in.
Fast forward into high school and uh I had this whole kind of underground ring that I had set up where I was buying pizzas for half price from Papa John's and then flipping it for like, you know, 2x uh multiples uh on the open market there at lunch and started out by like one pizza. By the end of my junior year in high school, I was clearing like, you know, 200 pizzas a week out of there. School officials were trying to find where it was being delivered and I had to get the Papa John's guys to go to different entrances and fortunately was able to do it without getting shut down. But I just always had that uh that element in there I think from a kid. Um and we can get a little bit more of my background. It kind of went dormant for a little while while I was in the government and then kind of reappeared in recent years. So it definitely goes back to childhood though.
Jake Aaron Villarreal: Yeah. Yeah. Yeah, we oftentimes hear that with founders is that they started out but it was intrinsic in their character, their personality to figure out ways to, to, to generate money or make friends or ultimately solve problems. So uh as we look at you know technology and this huge wave of AI companies coming into the market and looking at taking industries and optimizing them or changing them to, to improve efficiencies. We're seeing just a lot of incredible innovation. I know you spent time in the military and um if I can say that, if it was counterterrorism I'm assuming it was military. Um, but kind of walk us through that because that seems to be a fairly good part of your career. What, what was it that inspired you to get into that space and, and, and in there? What specifically were you doing when you talk about counterterrorism and kind of some of the things... kind of enlighten us a little bit.
Ryan Joyce: Yeah. So, just to be really clear off the bat, I wasn't personally in the military myself, but I worked very closely with those that, that were and we supported them. A lot of times would be co-located. I myself spent time in the US intelligence community for a number of years and specifically some of those latter years were spent in the Central Intelligence Agency. My specific role was as an operations officer, also called a case officer, and my job was to recruit and handle foreign sources. These are foreign, they're humans that have access to information, secret information that the US government wanted to know. And my job was to go befriend them, develop trust, and then bring them to a point that we could essentially recruit them to give us that information.
And then we were able to deliver that to our really smart analysts who could write up either type analytic reports for policymakers or some of it was just very tactical in nature that we would deliver it directly to our military colleagues to either prevent a terrorist attack from happening or we would be able to bring down a terrorist network by doing some capture operations in, in foreign battlefields. So that's the background that I had and it really stems back to I, I mentioned early on that my dad was in the Navy as a fighter pilot and later in his career he was at the Pentagon and that's where he was on the morning of September 11th when the plane actually hit his office and he narrowly made it out that day. Uh literally had just evacuated from his floor. He was on the fifth floor. Uh the third ring in of the Pentagon has three concentric rings and he was there when the whole floor collapsed into the inferno below. And uh and I you know for hours my family and my, including myself, did not know whether he was safe. Heard "Okay, I knew exactly where his office was and I knew that that's where the plane had impacted." And it wasn't until later that night that he made his way home, combination of hitchhiking and buses, and walked in the front door. And man we were just so overjoyed that he was alive. And you know sat around as a family and said a prayer of thanks.
And then unfortunately he had to go out that night to go to a few of the families of people that he knew had been killed in the attack and tell their, their wives or children that "Hey, your husband or your father is never coming home." And when he came home that night I was, I was just kind of like, "Man, it was such a crazy day," and I just decided then and there that I was going to do everything I could to learn about the history, culture, language and religion of the people that would do that and make sure it never happened again. So fast forward many years, I ended up studying abroad in the Middle East, learned Arabic, and when I finally did join the government and, and then eventually the, the CIA, that was my job was to essentially be there on the front lines uh to ensure that we had the information that could prevent the next 9/11 from happening. And I think what I'm proudest of is, you know, years went by and we have not had another similar attack. And there certainly have been many attempts. And yeah, that's the background that I, that I have and that's that I bring to the table now when I kind of entered the startup sphere with a very unique and different background.
Jake Aaron Villarreal: Yeah, very unique and different but also nicely tailored into what you're doing and the problem you're looking to solve. You know, we look at companies, we always talk about, you know, what problem are they solving that you're willing to pay for and then who are you helping in that process. So give us a little bit of a background of, of the inspiration around GenLogs and where did it come from?
Ryan Joyce: Yeah, what I'll say is when I was in my government career, I had a rule for myself that I always wanted to serve in a country that was listed above the fold of a newspaper, the front page, meaning it was important. Like policymakers knew about it, the White House cared about it. Uh when that was Yemen, I spent time in Yemen. When it was Iraq, I spent time in Iraq. Uh and and some other places that I was able to serve. So when I finally decided to leave the government in around 2020 and took a leave of absence to go join an early stage startup, I was learning a ton there. Uh we were focused in the computer vision space, specifically on putting computer vision models on cameras to monitor people's movements both around cities and that ended up pivoting into the retail analytics space.
But I was looking for what I was going to do next. I remember looking at the top fold of a newspaper, above the fold. And this was during the post-COVID era where we just saw "supply chain, supply chain, supply chain" in the news over and over. We had ships stuck off the coast of Long Beach. We had delays getting something to your, your front door whether it was PPE equipment or something from Amazon, toilet paper even. I mean, it was just delays across the board. Supply chain was suddenly the most important thing that people were talking about uh outside of COVID itself. And I just said, "There has to be something going on here. I'm sure like, let me dig into it a little bit more."
And the more I dug into it, I realized that a lot of the elements involved in a supply chain, whether you're bringing something on ships or even on planes, the tracking that occurs that way is kind of a solved problem these days. We have these AIS beaconing capabilities that can track ships all around the world. And on the plane side, we can kind of track a plane's movement via these ADS-B monitoring systems. The, the equivalent didn't exist for trucks. And I just kind of realized one day when I woke up and was eating cereal and thinking, "How did the cereal get here? How did the clothes... I how did the, the furniture I'm sitting on all get here? What, all came by truck at some point?" And it, and I just thought it was crazy that we didn't have a ubiquitous understanding of where all trucks were all the time.
So when I started to engage potential customers in the space, I did ton of customer discovery. The bottom line is I realized that there was just a lack of data on truck movements. We have almost four million Class 8 trucks in the United States from about 500 to 750,000 different truck carriers that are on the roads any given day and they're criss-crossing all around and no one knows where they are. Both when you have your own shipment on there, but more importantly for the freight brokers and the shippers in our country that are trying to find "who is a truck carrier that can carry my very unique load that needs a unique equipment type from Atlanta up to Chicago." They struggle finding that, they're on the phones. It's a really analog process.
And I just saw this parallel of what I was doing in the intelligence community where we would go out and collect data and whether it was large data sets, we would put satellites up in the skies, we would put sensors out, we would do whatever we had to do to get data so that we could dissect that data and then deliver these, these insights to policymakers or military, you know, tacticians. And so that's really what it came down to is I realized, "Huh, like we, you know, said at the beginning of the episode, well, I used to track terrorists. I think I can track trucks." And we just took the entire playbook that we had learned throughout the Global War on Terror and took all that methodology to apply it against trucks on the road using different satellite sensors and other data sources to bring it all together and then ubiquitously track all truck patterns in the, in, in the entire United States.
Jake Aaron Villarreal: And so it sounds great. It sounds like a lot of work too. I mean putting sensors all over and having satellites in the sky. I don't know how that works if you contract or you actually have your own satellite. Maybe you're proposing to get your satellite up there. I don't know. But at the end of the day, um, is the problem you're solving helping the truck brokers to make sure they can find the right trucking companies that they can believe in, trust, make sure they're doing the right things. What's in the truck with their goods isn't narcotics or other stuff that shouldn't be. Like what's, what, what, what are you sharing and selling to them that they're saying, "Oh, this is something that we want to talk about."
Ryan Joyce: Yeah. Our, our initial customer profile was really the freight brokerages around the US. So, there's around 25,000 of them and they handle about $160 billion of revenue driving. So, they're handling about 20% of the freight on the roads at any given time. Their problem, especially in the post-COVID era, was there, there was this rush of new truck carriers to kind of enter into the market. Well, a lot of them were actually posing as truck carriers, but they didn't actually have any trucks. And so, when a freight broker needed to move a load, if they didn't, if they couldn't find someone to do it or they didn't know someone directly that could do it, they would post that load on a public load board. Essentially, if you kind of think about it like old school, it literally was like corkboards in truck stops. And then it became like uh you know you dial in and tell someone and they would put your details of where you were or had a truck or where someone needed to move something. That's how the matchmaking kind of occurred.
And that worked okay until these fraudulent actors sat there saying, "Oh, I have a truck. I can take it." And that load would get assigned to them and then that load would be stolen when someone else would go pick it up that wasn't that truck carrier. And so what, what really was needed from the industry and what freight brokers were kind of craving, what I would say is the equivalent of the Multiple Listing Service in residential real estate. You have buyers and sellers and they're trying to find each other and for a while it was realtors that knew who was selling or buying in markets and they would kind of call each other and then the Multiple Listing Service and Zillow and Redfin and everything came online and then you could see all of the capacity in one place. And that's what GenLogs is doing. We are shining a light on where all truck patterns are with the right equipment types. We're shining a light on the capacity so that freight brokers and shippers can go directly to truck carriers without having to go through these fraud-laden load boards.
Jake Aaron Villarreal: Gotcha. Makes a lot of sense. As a company, you have technology and people. You got to raise capital. You got to manage the company and scale it and grow it. Where are you at as a company today in terms of funding, people, location? Walk us through that a little bit.
Ryan Joyce: Yeah, happy to. And uh by the time this episode comes out, I'll be really happy to say that we actually just closed our Series A recently, which is actually kind of incredible given it was only about a year ago that we raised our initial seed round. So when the three founders, me, Joe, and Blake, decided we were going to do this together, uh it took us about six months to figure out some of the technology, put the first sensors out in the road, starting to collect the data on passing trucks, bring all of that together with some other unique data sets that we have, and then finally got it to somewhat of a minimal viable product status so that we could go get those initial customers on board while we were simultaneously raising our seed round. And a- fast forward a year later, we went from three to over 45 employees. Um, bringing on about 60 different paying customers. And uh, and not only did we raise that seed round a year ago, but we just closed a Series A last month led by Venrock and Hoff Capital. And now we are, you know, fairly well capitalized with a really clear product market fit that we're seeing from those initial customers.
We're seeing customers that will get onto our platform and within the first 30 days see 150% ROI annually on what they agreed to pay in the platform. I mean it's just, it's kind of mind, mind-boggling what we've been able to, to unlock for these freight brokerages. And yeah, so we're using the uh the capital that we have to quadruple the number of sensors that we have out. Not in the United States, but we're going to be expanding down into Mexico, eventually Canada. We're also putting our sensors now at some of the ports and the intermodal rail terminals so that we can go beyond just looking at what's the truck activity in the middle mile like along major freight lanes and interstates and highways, but where do they actually go. And looking especially when you look at ports, like what are the imports and exports and who are the truck carriers to carrying those different cargo containers and what does each cargo container uh what's in it and where is it going? And so that's all that we are now investing into to go beyond just finding truck carriers, but actually tracing those trucks all the way from their origin to destination.
Jake Aaron Villarreal: So is the, is the sensors actually connected to the truck? It's a little bit different. Connected to the container or is it on a camera?
Ryan Joyce: Yeah, so we, ours are... Yeah. Statically in place that we are putting out along all major interstates. So they're not actually connected to the trucks. And what the advantage of that is, is instead of like if you go down that road of, "Hey, we have you, you can either collect on trucks two different ways." You can go to four million trucks and say, "Hey, can you put this little tracker on your truck so we can track it?" You're going to get no headway there. We decided to take a different route, which we were going to build this network ourselves that could passively truck uh track all of the trucks as they pass by. So each one of our sensors has three HD cameras that focus on the front, side and then rear of the truck and piece of equipment as it passes by. And then we'll use computer vision models at the edge to pull out the different types of identifiers like the, the actual Motor Carrier number which resolves back to who is that truck company. Uh then we'll look at what is that cab number or what is the VIN number on there. What is the equipment type? And that's a really important part because if you need to move uh let's say a tractor, the tractor is not fitting in a normal trailer or even a refrigerator trailer. You're looking for a very specialized equipment. And so we use computer vision models to look at all of the different equipment types, hundreds of different equipment types that are on the roads.
And so when you say, "Right now I need to find in real time a truck carrier that's in Dallas that has a 13 axle lowboy removable, removable gooseneck that can hold this really special equipment," we can actually find you that. We can tell you who is the carrier that's in that area. Show them the equipment that's paired with them and then their contact information so you can reach out directly to them now to see if they can haul that load for you. And it's all done via this network that we are spending millions of dollars and a lot of like mind-boggling painful hours to get out there, but it's worth it in the long run.
Jake Aaron Villarreal: Yeah. Well, you know, I'm on the highway quite a bit. Like where would the sensor be? Is it like on a post, on a l- light post looking down at the highway? Is it...
Ryan Joyce: It really depends. We, we, for a while we just went down the road of only working through private partnerships. So, if you're like uh if you happen to have a barn that was sitting on the side of I-80 that fit our right requirements in terms of proximity and the right, you know, internet speeds and connection to bring the data back and all of that. If it fit the bill, then we would probably have already knocked on your door to see if we could sign a long-term lease by putting our sensors up there. And therefore, and then really anyone that drove by, frankly, would not be able to differentiate between security cameras or these GenLogs cameras. And they're going to look very similar. In fact, we are on the sides of warehouses where the warehouse keepers, they, the landlords, they love it because our cameras look like security cameras. It's actually deterring crime and theft for them. And yet, we're taking advantage of it by looking at truck traffic on the roads.
Um, and only recently did we get the green light from now public partnerships. So, think of like actually state governments, uh, the actual ports or some of the, the rail operators themselves are saying, "Hey, we like what you're doing and we want access to that data, too. Can you put this on our infrastructure?" And you mentioned it earlier, Jake, about the, you know, counter the fentanyl and some of the more nefarious uses that are unfortunately that trucks, they're big, they can carry cargo, and there's been times where they've carried methamphetamines. There's been times where they've carried guns and others, unfortunately, where they've carried humans. And we're trying to get ahead of all of that different type of smuggling. So some of our partnerships with the state governments is to tackle those use cases. And we're also tackling with some of the nonprofits in the space like the Polaris Project and others who are using our data actively to prevent the human traffickers, to prevent the fentanyl traffickers in the United States. Keep frankly America safer and stronger. And at the end of the day, we love it because our mission, if we can keep the bad actors out so that the good guys can flourish, then that's a win for everyone.
Jake Aaron Villarreal: Yeah, I love that. Yeah, human trafficking, that's incredible that you can actually help solve that problem. I know it's a big one and really no one, it doesn't seem like no one knows how to solve it. So, it looks like this is at least another opportunity to do that. Um, what's the business model? I'm hearing data. I'm hearing, you know, visibility for brokers to find the right good actors. What do they, what, what's the pay process?
Ryan Joyce: Sure. So, what the user actually experiences is just a straight software subscription. So, we're, to them, we're just a SaaS product. I mean, there's a lot that happens under the hood with hardware and AI, but when they get the platform, they can log on and literally put in origin: Atlanta, destination: Chicago, a few things about what they're looking to find, and we'll give them the data right at their fingertips, including real-time images of these trucks out there in the roads. So, right now, we're on an enterprise annual subscription. Uh, so it's unlimited seats, unlimited searches. We're doing that to really learn uh from our customers about what do they need.
And this uh, this week we're actually unveiling our intermodal insights, meaning you now can select any shipper in the United States and then filter down to say who actually has drayage movements or basically movements of containers between a shipper's or distribution facility and a rail intermodal ramp, and then find the actual truck carriers that are running those lanes that have the right equipment or that they specialize in kind of running these containers short, shorter distances. Uh that's something that we're including for all of our customers. I mean that in itself would be a product, but we're kind of like making it just embedded in our larger freight intelligence platform. And so I would say since we actually launched the product in August of 2024, we've added so much value for our customers and they're paying the exact same rate. And we're doing that throughout the first year so that we can maximize the returns they're getting and we can maximize the understandings of, of where can we go with this product and what can we, else can we do with this data.
Jake Aaron Villarreal: I love that. Yeah. Oftentimes when you're selling a product or getting that into a new market, whatever the product happens to be, you want to sell something that's going to be worth paying for. That if you have a irresistible offer, something that is much more value than they expect they're going to get for what they're paying, then you really get clients for life and they talk about it too, which is a way to drive more awareness of your product and your brand. So, that sounds like you're, you're really getting there on the irresistible offer stage. Um, talk a little bit about AI. How is this being applied to your platform and what's the benefit for the, for the customers?
Ryan Joyce: Yeah, I would say the, our, our AI is kind of two stages and I would say we're in stage one right now. And stage one is more of just kind of like elementary machine learning tasks using computer vision, building models. I mean something I say elementary, I mean it's really difficult to do um but it's really uh it's not unlocking the true potential of the AI. So we use AI with regards to building computer vision models, deploying those on our sensors that are out at the edge so they can classify what is a truck or a commercial vehicle versus a private vehicle. For us, that's really important from a privacy perspective. We filter out all private vehicles at the edge. So you cannot get into our data if you're driving a minivan or, you know, a Tesla Model 3 or whatever it might be. We're just going to filter you out because we've trained a classifier of trucks or commercial vehicles or not. And then when you're in our data as a commercial vehicle, we are then pulling all of the different data types out from you. So it's a lot of on, heavy on the computer vision space. Um there's some work we do using like leveraging AI to look at correlations with other data sets.
Really where the big uh, the big unlock's going to be, and this is something we want to focus on the rest of 2025 here, is using our data to be predictive. And using our data to actually predict when a truck might be available based on all of the past data that we've seen, that we always seem to see that truck on Thursdays but based on some other data sets we believe that in the mornings it's loaded but in the afternoons it's likely to be empty. And then using that we can kind of rank our recommendations of the right truck carriers at the right time and place and with equipment and backhaul needs and really drive more efficiency with freight matching for our customers. So once we collect the data, and right now we're collecting about 40,000 truck images every five minutes, and that could probably is inching up even more. That was the last time I at least sampled how much data we're, we're pulling. Um you know, millions, hundreds of millions of different truck images that we now have stored and over a billion records of trucks at a time and place. When you have that data, and I, and I'll just say like if you're trying to start an a- AI company today, do it in an area where you have unique and proprietary data. Because we now have the largest holdings of truck images in the world and all... and the largest repository of data that we've derived from those images, which now allows us to use that proprietary big data that no one else has access to, to make incredible predictive uh decisions or, or suggestions for our customers.
Jake Aaron Villarreal: You know, I used to drive trucks. We talked about this a little bit, which is kind of crazy to even say that and think about it. Um, as, when I was in college, it was for university kids. And, you know, it was $1,000 a week at the time. And like for a kid that's in, 18 in college and you know, you do that for a summer and you make 15 grand and you walk back to college and you're like, "Okay, now I could do whatever I want this year." And it was a great experience. Um driving those trucks down Highway 5 in California. I mean, we did that, you know, 12 hours a day hauling tomatoes and oftentimes we'd see lots of cars and who knows, maybe there was cameras there too that were capturing us. How do you address the privacy concerns of this type of technology for the drivers, for the public?
Ryan Joyce: Yeah. Well, I can tell you like if you were to go on right now to Flightradar24.com, you could literally pull up every plane that is in the sky and it'll tell you by the tail number that it's there. What you don't know is who is the pilot and who are the passengers right now. And we've taken a very similar approach when it comes to GenLogs with trucks. I will tell you that a commercial vehicle is at a time and place right now, but I have no idea who the driver is. In fact, we therefore treat every truck as if it's autonomous. Meaning I don't know if there's a driver and I really don't care if there is a driver. And frankly we've already seen autonomous vehicles, so there are, there are trucks that we see that there are no drivers. And I kind of uh I tell this anytime it comes up like, I will show you an image of a truck and challenge you to tell me who the driver is. And if you can, I'll give you a thousand bucks. And to this day no one has been able to do so because we're resolving the truck to the larger corporate entity. So it'll be like Werner or US Xpress out there on the road, but not knowing that you, Jake, were the driver at that time on I-5.
Uh, and I think the thing that it's important to keep in mind, um, is we definitely comply with all local and state regulations. And there are, at the end of the day though, from a Supreme Court perspective, there's no expectation of privacy on a public roadway. I mean, you're out in public, people see you, and, and if you think about it, every Tesla on the road has eight cameras that are recording 24/7. Tesla's using that for a whole lot of different uh types of training that they do. And if you go to Google Maps and you go to that same spot on I-5 and go to the street view, you're going to see trucks there as well, especially trucks with the side panels uh not occluded, very clearly be able to read their US Department of Transportation number, which publicly you could look up who owns that truck. And so we just do that now automated by, with a nationwide network of sensors. But we really take that, that privacy really important, and we, we filter out any data that could shed light on who the truck driver is themselves. There are other platforms that deal with driver and, and carrier onboarding. We've purposely decided to not. I think we're collecting enough data as it is, and uh, and we want to make sure we don't cross that line where we have truly Personal Identifying Information (PII) to be able to associate back to this truck. So that's my uh maybe short, maybe long answer to your question.
Jake Aaron Villarreal: Oh, that's good. I think you answered it correctly or at least from my perspective well. Um you know, you've raised capital, you've hired people, you're building a network, you're in the market, you're generating revenue. What are your clients telling you about your product so far in comparison to what they've used in the past? What's the feedback been like?
Ryan Joyce: Yeah, I would say the greatest feedback we probably heard even last week was uh there was a few sales folks, both on the carrier sales side and we also provide data on shippers around the US, that had been using our products for about six months now. And uh there was some financial issues going on with the, the customer that predated us being involved. But after these folks had used our product, now as they're making these decisions about where they're going to go elsewhere in the market, they came and told us like, "We will only go work for another freight brokerage that is a GenLogs customer." Because like why would you, that, you know, the way that they were kind of expressing it is, "You have forever altered the way that a freight broker does their work. Like I can't imagine being a, a realtor without having access to the Multiple Listing Service or to Zillow. So why would I want to go back in time?" So they're like, "I will only go to freight brokerages that are using this product."
Conversely, we've heard from shippers who are actually the customer of freight brokerages. And some of those shippers have come to us and said, "We love what you're doing so much that we are going to mandate that freight brokerages use your product in order to work with us." Because we are preventing on a daily basis from, from their own product that they're trying to ship from being stolen. We're preventing it from them, from being defrauded. And at the end of the day, we're using data to make predictions that "who are the best carriers that have likely backhaul needs that will be willing to haul that shipment for potentially less than market rate because otherwise they'd be going what's called a deadhead." They wouldn't have anything uh that they're carrying, but they're going home, let's say, for the week. Um, and we provide that ability to say, "Hey, this carrier is in this market right now, and they probably need to get back to home. So, why don't you call them directly and try to broker that load?" And in doing so, you could probably do so for under market rate where that carrier now makes money where they were otherwise going to be driving empty. And so we've heard from, you know, freight brokerages, they, they never want to let it out of their hand. Individual users, same thing. And then shippers saying that now we're going to mandate it.
And, you know, all of that is just uh I think shows the team that, that GenLogs has built here. Uh and the 45 folks that have come and said like, "Hey, I want to build this really exciting platform." Um it, it just shows that we've hit product market fit now. But I think it also shows that there's a lot more uh blue sky ahead of us. And as we look about, you know, right now we focus on the roads and we like to say, you know, "We're owning the roads." Soon it's going to be rails and it'll be rivers and then we say, you know, "seas and skies and space." And so that's where we want to say like "anything that, anytime that, that an object is being moved um we want to be involved in understanding the tracking of that, understanding the best ways that, that, that can be moved most efficiently from point A to point B." But I think most importantly, making sure that it's done safely and without um fraud and theft being infused into the process.
Jake Aaron Villarreal: Yeah, that's great. As you look into 2025, it sounds like you've got a lot on the road map. What's the biggest challenge for the company currently?
Ryan Joyce: I think our biggest challenge endures, which is we have a really stringent requirement for where you need to get a sensor setup to get the ideal collection, and it's truly like uh finding a needle in the haystack. When we do find it, it's awesome and we, we will sign these leases for decades with exclusivity so that you know we have that now very, very precious spot with no one else being able to come on and also collect on trucks from that same vantage point. Now, the fact that we want to quadruple the size of that network and now expand into Mexico and Canada, we certainly have our work cut out for us. So, we are uh, that, that team, our sensor deployment team, has actually tripled in size over the last few weeks, and we're going to continue to invest heavily into that team because we've just noticed that everything flows from having that data up front.
And so if we can get that network set up first and get it, you know, ubiquitous everywhere covering every stretch of the, the major stretch of the highway, and then we can expand beyond the borders of the United States, then we're in a really good position to use the, the really smart data science and engineers to take that data down the line and unlock incredible insights for our customers. So that has always remained the hardest part of our job, uh and it probably will remain. But we're making sure they're resourced uh efficiently and effectively in order to do that because that's really what differentiates us in the market. When people think GenLogs, they think about that ability in real time to look at an image of a truck at a time and place. And you can spoof GPS, you can do a lot of crazy things in other data sets. What you can't hide is that truck is either there or it's not. And that's what GenLogs is able to show with our sensors.
Jake Aaron Villarreal: Yeah, that's really cool. Well, I love the story. I love the problem you're solving. Um, you know, as you head into 2025, you've talked about what's, I think, kind of on the roadmap. Um, what specifically can your customers expect to see, if you haven't already mentioned it, that they'll be able to use or get access to based on using your platform in 2025?
Ryan Joyce: Yeah, I think one of the things that uh you... we really listen to our customers all the time about like, "Hey, what else would you like to see?" And, and sometimes we even show them things that they wouldn't have expected or didn't think was possible. And I think uh when I, when I mentioned that we're sitting on over a billion records on trucks right now, we're now at that point where we can actually show a lot of trends over time. So, it's possible that carriers that might haul produce in certain seasons might be operating a certain part of the re- uh, the United States during a few months of the year, but then might be in another part of the United States with different type of equipment in different months of the year. And if you don't know that, then you, you might be spending a lot of time inefficiently trying to contact these carriers when they're not even in that market and they don't even have that equipment.
And so now that we're sitting on all this data, we're actually going back to our repository and pulling out year-over-year, quarter-over-quarter, month-over-month type data, and then now making that available right at our customers' fingertips that when they either search on a origin to destination or search on a specific carrier's name, then we're actually showing all of that kind of trends over time data right there and then giving them recommendation of what they can do with that data right away. That's what I think uh our customers can expect now is that we're going to use the past data we've now accrued to really supercharge what they're going to be able to do in the future.
Jake Aaron Villarreal: Wow. Well, enough said. I'm sold. If anybody wants to find you or find GenLogs, where do they go?
Ryan Joyce: Yeah, you can go to our website, genlogs.io. Genlogs.io. Uh you can book a demo in the upper right if you just want to see what the platform looks like. Uh we anytime we have job vacancies, we're going to go ahead and be posting on the website, too. You can also follow us on LinkedIn, X. I'm also on X Twitter. RyanJoyceVoice uh is where you can find me. And uh otherwise, yeah, please love to stay in touch with any of the listeners. And Jake, thanks so much for uh having me on today.
Jake Aaron Villarreal: Yeah. Well, I appreciate you coming on and appreciate the listeners for listening today. It means a lot to me that you spent your time with us. I'm your host, Jake Villarreal, signing off for now, but can't wait to catch up with you all in the next episode. Until then, Ryan, the world, take care. If you like what we're doing, don't forget to subscribe, leave a review on Apple Podcast or wherever you listen. Follow us on YouTube where we go behind the scenes to learn what it takes to be a startup founder.
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