Latest / Exit Algorithms / How to Cut $5K to $15K Per Truck in Idling Costs | Steven Antalics, EkoHaul Founder (#108)

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How to Cut $5K to $15K Per Truck in Idling Costs | Steven Antalics, EkoHaul Founder (#108) · Exit Algorithms

• Pete Vera, Exit Algorithms: Welcome to Exit Algorithms, the podcast where we decode what it really takes to unlock growth, streamline operations, and prepare your business for a high-value exit. I'm your host, Pete Vera, and today I'm joined by Stephen Antalix. Steven worked for nearly 20 years in commodities trading, shipping, and IT at large multinationals. He did everything from work on the second largest corporate merger in history to implementing software platforms. Used by hundreds of agencies globally. He worked in a Silicon Valley startup that was automating general assembly using AI-backed robotics. And today he it works as the founder of EcoHall to reduce eliminate unnecessary diesel consumption in long haul trucking during idle periods using solar array and batteries. Steven, great to have you here. Welcome to the podcast. Steven Antalics: Likewise, great to be here and thanks a lot for having me. Pete Vera, Exit Algorithms: Yeah, excited to get into this. how about Steven? Do you mind starting off? Can you share a bit about your your journey, your your business background and yeah, what led you to EcoHall? Steven Antalics: Well, to do that, I'll you know, I've done this a lot in my life because I've had quite a quite a varied career, but I'll start back in college because that's the the core of what what drove me to to Eco Hall twenty plus years later. So I was at university, I was studying engineering, and I realized quite early in my studies that I was a pretty mediocre engineer and I was much better at the business side of things, like putting ideas together, you know, having like basically like team building or business development, things like that. And I joined a project called the University of Michigan Solar Car Team. So we would build and race a solar car from scratch every two years, and we'd race it in North America and Australia. at the time, this is back in 2004, 2005, like my dad was a truck driver with JB Hunt, and he'd been driving for 20 plus years at that point. And one of the things you learn on solar car is that one of the key races in Australia goes north-south, right? So in the early days, they would curve the solar array because the more power you get is when the sun is perpendicular to the array. So the idea was you're going north-south. So the sun is going basically, you know, across ⁓ You know, you're from left to right or right to left, depending which way you're facing in in the race. So the idea was as the i as the sun tracks across the sky, you get the most power. Very soon, after a few races, people realize that actually when the sun is at its peak between ten AM and two PM, you get so much more power that that stuff on the sides is irrelevant, basically. And I thought, hmm, that's interesting. A flat surface makes more power than if it was, you know, you know and I was like, Well, what's a flat surface that we're not using that could generate this power? I'm like, Well, the trailer of a truck. It's elevated, it's you know, you're not getting road debris on the top. If you have it on the sides, it's irrelevant, like in terms of how much power it's generating. And that's back in like 2005 is when I first had this idea. But the the real limiting factor back then was battery technology, as I'm sure most of us are aware, was nowhere near the kind of quality, power, and price that you can get today. So that just was a non-starter economically. So anyway, I had that idea. I was on a solar car team, we were sponsored by some big name companies, ⁓ BHP Bulletin, Shell, Ford, GM, like you know, a lot of these these big companies. We had a budget too. We had like a two million dollar budget. so it was not a it was more than just a student project in that sense of like, ⁓ let's just build this thing. Like we had the car insured for like over a million dollars, like whatever. So after the project ended, like I moved into one of our sponsors as a job working at VHP. I originally started working in supply-demand logistics, and my had been in the merchant marine. So he was like, ⁓ hey, if you want to understand, like All the different places the company sends its commodities to China, to you know, things from Brazil, from Australia, whatever, you should get into shipping. So I started working in shipping a bit, and then I got a call from my boss saying his former boss was in London working on this merger. So I got pulled into this, what was at the time the second biggest corporate merger in history between BH Built in and Rio Tinto. So I worked for almost a year in London on this. I've got a story about that that I'll get into a bit later. Merger fell apart because of the financial crisis. And so I was looking for a job in London. There wasn't really anything on the market at the time. Just like today, it's a bit the job market's pretty, pretty rough. And ⁓ so I moved back to to Holland where I'd been based, and I'm I started working full-time in like ocean shipping. So I worked in operations for K Panamax handy vessels. then I spent a year ⁓ Avery in also in Holland working on European trucking logistics, so looking at the The cost of you know shipping goods from this postcode to that postcode, and you know, optimizing these and reporting up to management. then I got an opportunity to move to Geneva ⁓ I got a job at Cargill working as I never thought I'd be in IT because I left my engineering background behind, but I ended up working in IT, supporting shipment operations, quite specially just for the operations side. So we also had somebody looking after the chartering and someone looking after the finances. Pete Vera, Exit Algorithms: Mm-hmm. Steven Antalics: And then I very quickly got an opportunity to move to Trafficura where they had me doing basically everything from you know dry bulk operations, chartering whatever wet bulk, so oil shipping and things like that. And I was responsible for the whole system end-to-end. I was there for five years and then I had a chance to move to MSC and do a similar role, but with slightly both lesser and greater scope. Like greater scope in the sense that you at Traffic Euro, we had a couple offices, we had like I don't know, maybe 80 people or something using the system. At MSC, the system I working on was ⁓ under their compliance like rubric, ⁓ like 500 different agencies around the world were using it. So we had a massive user base. and we also had a lot of different stakeholder groups in the company because a lot of people, you know, for for the container shipping business, it's all about documentation. Like you you have no insight, containers locked and sealed at the customer. So you're 100% reliant on how that good has been described by the customer. and so the volume of documentation was massive. And so we had different types of groups. You had the legal team, you had the operations teams, you had documentation teams, you had the agency teams. They all needed to have access to this documentation and that all flowed through our compliance tools. So it was quite a a big step up in terms of of responsibility. I left that job not like my a friend of mine that I'd met way back at university back on SolarCar was Pete Vera, Exit Algorithms: Mm. Steven Antalics: working on this startup in Silicon Valley and he had been pestering me for quite a while to join it. And I'm like, look, mate, I've got a house, I've got a kid, like I can't just go work for no no salary in literally a garage in San Francisco. We we ⁓ the office is garage. It used to be a motorcycle repair shop. So ⁓ he'd been pestering me a while a while. and then unfortunately my parents died within seven months of each other. So my mom passed in November of twenty twenty one and my dad passed in June of twenty twenty two. Pete Vera, Exit Algorithms: Mm. Steven Antalics: And that was really the catalyst where I said, look, I've got this opportunity to work in Silicon Valley. ⁓ he had a massive first round. We raised 12.25 million, which in the Valley, this is 2021, was probably not all the funding is publicly available, but from what we could tell, it was like top five, top ten in the valley that year for first rounds. And the fact that we were doing hardware was unusual, let's say, and also the the focus was on manufacturing was another Pete Vera, Exit Algorithms: Starting. Steven Antalics: unusual factor because Silicon Valley is not known for this type of stuff. So anyway, my buddy had been pestering me. I had I'm an only child, so I had to deal my parents' estate such as it was. And didn't have Europeans have a lot of holiday I didn't have that much holiday to deal with my parents' stuff. It was a lot. And so my parents are Eastern European. I'm both I grew up in the US near Detroit and Hungarian. So I have dual citizenship and my parents if anyone knows Eastern Europeaners they tend not to ⁓ Think about, talk about, deal with their health. And so my parents had not prepped at all for dying, even though my mom knew she was terminal many, many months ago. She still had an active gym membership. My dad was driving a car that was still registered in her name, like after I'm just like so I had to deal with everything. So anyway, I took the job in Silicon Valley thinking like, you know, this is gonna be amazing, it's gonna be whatever. And it was good and bad. It w it was good because it's, you know, I got to do a lot of different things that I hadn't done in my career, you know, preparing investor decks and Pete Vera, Exit Algorithms: Mm. Steven Antalics: working on business development, you know, in a totally different industry. And there's a lot of overlap between logistics, warehousing, kind of manufacturing. They're all very in kind of intimately tied together in terms of how people think about stuff. Cost is a massive driver. How things have been done is also a massive like driver that sometimes gets in the way of adopting new tech. but yeah I mean Sil Silicon Valley has its pros and its cons. And I definitely, you know, having been out there, it's it's There's there's a lot of it that's very kind of clicky. So you're inside, if you're in the in-group, it's very easy to raise money. And if you're on the outside, it's you have to find a way to get into the in-group. They call it the PayPal Mafia. You can look it up online. It's not not you know, it's an open secret. But the guys that made the money off PayPal still like a lot of the capital flow flows through them or their company. So I'll give you an example. Our first ⁓ backer was Lenovo, like a corporate VC, right? And so we went to the likes of places like, you know, the the big names, the Sequoia's, the Arth Andreasans, whatever. They wouldn't even do a meeting with us. Because from their perspective, a corporate VC is a dinosaur. They're slow, they're outdated, they don't understand, like whatever. I had left by that time, but like we ended up getting Coslaventures on board. And all of a sudden, these same guys that wouldn't take a meeting with us are offering term sheets. So ⁓ Pete Vera, Exit Algorithms: Mm. Yeah. Steven Antalics: There's a lot of FOMO, there's a lot of like clustering around if you get the right person backing and all of a sudden everybody wants to back you. If you don't have that kind of seal of approval, it can be an uphill battle. but my family's here in Europe, so I moved back to Europe and the job market for me was just a complete nightmare. you've seen a lot of the tech layoffs like Google, Facebook, all those companies, and it's been tens of thousands of people since the pandemic ended. and being like a mid career kind of IT professional background. trying to find a job, it's been a nightmare. So I've started casting about for different ideas that I've had over the years. And I came back to this idea that I had about the solar panels. So I shoved it into Chat GPT and said, hey, like, is this a viable idea? Right? Like I know it's viable from the sense of like, here's some numbers, you could run the auxiliary systems or whatever, but you know, I'm not up to speed on the latest battery tech. You know, and Chat GPT ran numbers and insofar as its math is accurate, which I've checked many times, it came back with quite legitimate figures and said, look, not only is it like economical, Here's a list of companies that are doing it. And I was like, ⁓ man, come on. Like, you gotta be kidding me. Like, I waited too long. I had I'm sure a lot of people have felt this. Like you try and time the market, so to speak, and you just miss, you feel like you've missed the boat. And that's what I felt. Like really gut-wrenching. Like, But then I scratched below the surface. I started looking into what these companies are doing, and I'm like, these guys don't don't get it. Like either they don't understand the potential of solar or they don't understand the logistics industry and how it works. Because the kinds of stuff they were doing, it was like Pete Vera, Exit Algorithms: Mm. Steven Antalics: worst of both worlds and they didn't quite see it. So yeah so that's I decided anyway to start ecohol because I was like, look, these guys are missing the low-hanging fruit. They're not understanding like what the key drivers are in these industries. And I can give a couple examples if you're interested. But like that was the impetus where I said, look, I think this idea has legs. And think the people that are doing this, they're not quite seeing it from the perspective where I worked on a solar power car and I worked in logistics for more than 15 years. Very few people on those teams and those companies have that kind of background. Pete Vera, Exit Algorithms: Yeah. Awesome. So then Eco Hall was born. Steven Antalics: Yeah. Pete Vera, Exit Algorithms: Yeah. Wow. ⁓ that's awesome. Love love your your journey and and your story. Thank thank you for sharing that. yeah, how about we we start off and we can go a little a little backwards in time. you know, when you were part of that that second biggest corporate acquisition in in history. yeah, how that experience? Do you mind sharing any, you know, any takeaways from that that might be useful for for business owners listening? Steven Antalics: Yeah, look, I mean, some of it was very, very specific. actually had a kind of unique insight because I was so my my role was I was basically doing the grunt work underneath the VP that was responsible for getting the the clearances from all the different regulators and there were thirteen different jurisdictions, the US included, but also the European Union, China, Australia, Japan, like all the all the main countries that bought the goods that we sold, right? So I had an insight to the commercial side, and just by happenstance, I got Be friends with the chief legal counsel at the time. And like, so I got sucked into some of the lawyer stuff too. So I got to see kind of both sides of the deal. I would I would say the most interesting thing was is that you know, can you can look at all the facts and figures and stuff, right? Like you can say, ⁓ this is the the the economic rationale of why this this merger makes perfect sense and or doesn't or whatever. But nobody's to things like the sunk cost fallacy, nobody's immune to things like perceptions of momentum, right? So like sometimes the deal becomes An end in and of itself, even if it's not particularly optimized, right? So I'll give you, I'll give you an example. We we spent quite a lot of money hiring economists and different kinds of consultants to explain to different regulators why we needed to merge the companies and why we couldn't just do a joint venture, for example, right? Because you know, people people have this idea that regulators are really, really kind of dumb, right? And that was not my experience at all. Like the people that I spoke to. no matter their background, whether they had direct industry experience or not, these guys were super sharp. Like they came prepped. they had very, very like precise questions, questions that were not easy to answer. And the joint venture thing was was one of them because in VHP's instance, unlike most mining companies, they also all owned oil assets. I don't know if it's still true, but they were the largest leaseholder in the Gulf of Mexico at one point. So they, you know, we we spent all this money trying to convince people that like we had to merge the companies and not just do JVs, right? And so the merger falls apart, and you know, it like financial crisis basically made it. So at the time that the merger was kind of at its peak, you had a company that would have been worth more than $300 billion, and the debt of the two entities combined would have been like $90 billion, right? So totally normal for corporate world, whatever. When the financial crisis happened, the cap like the stock market values of the companies had declined to like, I don't know, it was like combined value of the companies would have been like $100 billion, and the debt was only reduced to like eighty-eight. billion so you're almost insolvent from the day the merger completes so the merger was called off but the thing the thing that was that was where I talk about like the mindset right so like management was very very focused on getting this deal through and there's a difference between kind of being being gritty and being bullheaded right and for me it veered on the other side because you know these mining assets you get a copper mine or a gold mine or coal mine they have lives of 10, 20, sometimes even a hundred years, right? So like you're managing truly for the long term. But the financial crisis, like the impact of that, for the commodities at least, huge dip in like November, December. Pete Vera, Exit Algorithms: Mm. Steven Antalics: March, April, things were already kind of picking back up quite substantially. Like, even though the financial crisis happened, like people still need food, they still need air conditioning, they they need they need buildings to live in, right? So, like the population, like things don't shut down even if the economy grinds to a halt. Just like with COVID, like people were still ordering things and toilet paper got, you know, the stuff stuff moves, right? The economy describes human behavior, it doesn't dictate it. And so six months later, they went back to the same European Commission and other commissions like the US thing. And they tried arguing, well, hey, you guys didn't reprove the merger, but how about we do a joint venture? so, like within six months, the same people that they had spent literally millions on consultants to explain why the joint venture doesn't unlock enough value to make it economical, they go went back and asked for approval for a joint venture. So you can imagine the regulators again, six months, nobody's changed rules, and they were just like, No, no deal. ⁓ not we're not letting you go. So it was it was interesting because like, you know, the people involved, like they're all super sharp, like. Top of their game and things like that. But you can, you can, you can lose sight of like what's the most economically valid rationale for something, right? Like what makes the most sense kind of universally. you can get caught up in egos ⁓ you know, I know there was a factor of like at the time in build-up to the financial crisis. If you look at the commodities industry, China comes online 2000, 2001, like in a big way. And you had what we called the commodity super cycle, where you had these, you know. Three, four, five-year business cycles, and this one had gone on for almost a decade. And so people were like, it's never gonna end. You had a lot of the commodity traders either going public, combining, just as BHP and Rio wanted to combine. And so there was kind of like this, I wouldn't call it an asset bubble per se. It was it was that old kind of irrational exuberance of like this is the you know, the the music is never gonna stop, or we're least gonna get in before the music stops, right? And turns out you know, mergers are. Very intricate dances. They usually take a very long time to complete if they're done properly. yeah, the market conditions can change quicker than, you know, if you if you come on if you come into it with one rationale, but you're not willing to update kind of your your priors and then things change, you're unprepared, and you end up pursuing something that that doesn't make as much sense. And there's a whole bunch of like little anecdotal stories in there as well. But I'll I'll keep it at the high level for the for the time being. Pete Vera, Exit Algorithms: Yeah. ⁓ yeah. Interesting. you know, have you has were able to take any lessons learned from ⁓ that or maybe just your other other times along your business path about what what is what is it that makes a company most valuable when it when it comes to close? Are there maybe a few things, you know, that you've picked up on that you're you're now implementing, You know, eco hall to to for to maximize value over the long term. Steven Antalics: Yeah, I think I think like so when the economics change, you have to change, right? Like, and that's that sounds kind of basic. And I know truckers know this. Like, you know, i if it's not economical to do a route, unless you're trying to like break into a new market, like there's usually more rationales than purely just money in in one sense when you're when you're kind of big enough, but when you're starting out it's it's just money. It's like that old thing, like Best Buy used to sell CDs at a discount to get people in the door. So they buy other products. And there's a lot of logistics companies that are moving to a model where like shipping the goods is just a service they provide, but they're making their money off of the back end of the warehousing, logistics, and things like that. So you that that's an adaptation, right? Like the market in in road freight from when my dad retired to today, retired back in like 2015, like it it's shifted a lot. Like as an owner operator, you used to be able make a really good living. And we talked about this a bit before the the the show. But like you could easily make six figures if you were diligent, you know, you were Had the right kind of background, whatever. And nowadays that's becoming more and more of a rarity. So for for how to build the business, like you know, at BHP, at one point during the super cycle, we were making a billion in profit per month, which is enormous, right? Like, I mean, it's just it it's the kind of money that you're just like, wait, what? And like, but even then, you know, one of the projects I worked on in Mozambique, it was like You know, we've got this titanium. I worked in titanium supply demand. And one of the things was we had this really rich titanium deposit, and it was maybe, I don't know, 20 miles from the coast, and there was a river. And the previous company we we acquired this project. And so the previous company was like, We'll build a jetty into like the Indian Ocean for ships, and then like we'll just move it down, whatever. we were looking at this project, like, dude, you want to build a jetty into a place with like massive currents, like huge. ⁓ title swing, like all this stuff, it it doesn't make sense. We boss called it gold plating, right? And so we we stripped a lot of that away. Even though we were making a billion dollars a month in profit, we were still like, you don't go spending money that's unnecessary, right? That's that's true in business. And again, it's something that you can lose sight of because of some cost. You've already spent this money acquiring the asset. What's easiest? You take the person who had it before with their plans, you assume they're competent. And it's not that they're incompetent, they just have their biases and they have their, you they might not have expertise in that area. Pete Vera, Exit Algorithms: And Steven Antalics: For for the startup and for my own startup, like the one that I worked on in Silicon Valley in here, like in the Silicon Valley startup, we made a lot of use of interns and kind of, you know, low cost labor wherever we could. We we we hired a project manager that was kind of like you pay, pay as you go almost arrangement. you know, obviously in the startup you wear a lot of different hats. And so like we we tried to stay as lean as we could. and that's something with EcoHall I'm really focused on as well. Like there's a double edged sword to getting investor money in. Right. Like a lot of people are like just avoid it as long as you can. And so I'm trying to build the business where it's a sustainable business on its own. But then conversely that also makes it more attractive to investors. Right. So like if you're not chasing that money, the money tends to follow you more easily because of that. Now I'm not saying I've had a lot of success in fundraising yet for you, Paul. It's really early for us. We've, you know, we're we're you know, we're ⁓ we might incorporate in Delaware in the US first because we I think the value proposition is bigger in the US, but we're you know we're trying to stay really lean. we've already got suppliers lined up, we've got quotes for the parts, we just need somebody to install like that is willing to install the system. Because like I could buy the comp components, but like the battery weighs almost 200 kilograms, so I don't have a forklift, my garage doesn't have that much space. So I really need a partner to you know test out the system, even maybe a scale-down version. but we're trying to stay super lean. Like the idea is well, I touched on it before, is early days, we're just gonna sell. Pete Vera, Exit Algorithms: Hmm. Steven Antalics: The units, right? Here's a battery, here's some solar panels, that's going to cut your idling, and here's the money, and then you get a return after you know two, three years, you're saving fuel, and that's how you pay back for the system. That's fine for starting out, and that's the way that any like very early hardware company can work because we don't have scale. But I very quickly want to move, you know, I'm using off-the-shelf components, right? And that's part of the reason I'm doing that is one is that they're all kind of validated as working in the real world, like the solar panels we found. Well, there's actually multiple suppliers now, but like one of them has a six year guarantee, the other one has a 15-year guarantee. Like so, you know, panels have come a long way even the last 10 years in terms of their like robustness. Batteries have become almost a commodity. Like you can build a pack in any size and shape you want. They're super robust. You know, there's plenty of trucking companies that are already using lithium packs, even for diesel trucks, not electric ones. And so the point I'm making here is that we're just like we're we're a bit like Apple. We're designing the system, we're assembling the components in a unique way, in my opinion. but we're not developing new solar panels. We're not developing a new battery technology, right? We're using what's available, putting together in a new way. What that means is we can be very asset light. So as soon as we get to a sufficient scale, like I want to offer leases and I don't want to keep that on my balance sheet. I want to make sure that I can get scale where I can go to a bank or someone similar and get financing for the lease. So we have the benefit of offering to our clients, hey, listen, you don't have to worry about two or three year paybacks on this system because you can just lease it and we'll price the lease so that you're making money from day one, right? You you pay less for the system than what you save in in fuel costs. And that type of stuff becomes almost like a recurring revenue model, right? Because a lease and a subscription are two sides of a very, very thin coin. and then we'd also have some recurring revenue like paying for telem telemetry. Because one of the other benefits of the system is that, you know, one of our advisors has a company doing telematics and he's got his technology already in quarter million trucks in in the US. And so ⁓ You know, he has very generously offered that we know we can just take the data on like fuel savings, engine time, engine cycle times and things like that right away. And then we'll build our own reporting and data sets on top of that around, you know, how much fuel have you actually saved? How much power is the system produced? And the idea here is also that like we help starting managing the energy because the the way I look at this stuff is that the sun is as many people say it's free energy, right? So you're you're already hauling the trailer. Why not have that trailer benefit you? Like it's not just weight, it could also be providing some power for the auxiliary system. Pete Vera, Exit Algorithms: Yeah. ⁓ definitely. and you mentioned telematics. I I'm curious, is along telematics or data in general, how are you leveraging AI these days? are you able to use ⁓ too much as I know ecohol's a a hardware company, but ⁓ I am curious your thoughts on it and how how are you applying it? Steven Antalics: So I'm using AI more for myself at the moment. It's it's kind of a like a sounding board or a partner. I mean, for anyone that's run their own business, it can be a saying it's lonely at the top. I'm not saying I'm at the top of my game. I'm just starting out, but it's still I don't have, you know, in my personal network, outside of my advisors and stuff, it's not like I can just like sit with my partner and chat about trucking, right? Like she's a teacher. Like it's not, it's not stuff that most people can like just riff on, right? So like finding people that actually understand the industry. It can be it can be a bit hard. So I'm using AI a lot to like do research, validate assumptions and things like that. And and and for me, not I'm not a big AI proponent, honestly. Like there's a lot that it can do, but for me, AI is a mirror, right? And there's a lot of people talking about how you can use it for coding and data analysis and stuff. If your data isn't good, your AI will not fix that problem, right? Like that, there's there's no magic for a giggle, garbage in, garbage out, right? And AI very much is a mirror. Like if you ask a poorly structured prompt, you usually get poorly phrased or poorly researched data back for you, right? And that also includes the hallucinations and stuff. So from my perspective, trucking is is really data thin. Like I know the whole like my dad was there when it was transitioning between the paper log books and more electronic logging and things like that, but still the industry, like it's not a homogeneous, you know, even something more advanced like medical records that have been around for much much longer still really struggle to get different types of data and different things in a way that one system can actually read it. So I'm not I'm not super keen on I on AI day one. what AI can help a lot with is things like predictions and and maintenance and stuff. So like you know I was telling you earlier like the the system is the I'm selling it, it's safe school. That's the bread and butter. Depending on your duty cycles, it can save anywhere from five to fifteen grand per truck per year just on fuel. Now, in addition to that, every hour, if you're one of the people that's idling your main engine overnight to provide that cabin power, the AC, the HVAC system, the lighting, and all the other electronics, like also causing wear and tear on the engine every hour that it's running idle. So I don't know the exact duty cycles or the maintenance intervals for your business, but I can tell you that there's going to be some savings in the sense that you're gonna, you know, maybe you can increase your maintenance intervals by a month or two on the engine or things like that. AI is a much better tool for helping predict that. Like, you know, you input here's all the stuff that happened before. If the system removes X number of hours of idling, then what would you expect the maintenance thing? And that's something where it might not be a hundred percent precise, but it's gonna be directionally correct and it's gonna at least give you an add, you know. ⁓ it's gonna save you a thousand a year, and it turns out it's eight hundred and ninety-five or it's eleven hundred and twenty, right? So it's gonna give you a a a better rough estimate than you know just taking a taking a calculation by itself because it can research and pull from whatever there is publicly available that that has looked at stuff like this. And it can also pull in some of the you know it it it's very good at making inferences, right? Like that's one of the reasons people use it for writing, because you can you can very quickly get to the gist of something, and that is where AI is very useful. And also for things like, you know, here's the average, you know, solar expo irradiance on these routes, right? What happens if we have El Nino? What happens if whatever? Like not a computer programmer, so I'm not gonna like model El Nino or whatever. But there's smart people out there that have it, and a lot of that is publicly available. So AI is a very good way of homogenizing what's available and making those kinds of predictions of like you're probably gonna get more or less or whatever on these routes for these days or these reasons. And you can always check that, but at least it gives you the Pete Vera, Exit Algorithms: Mm-hmm. Steven Antalics: You know, you're not in consultant speak, you're not trying to boil the ocean anymore. You have a much more narrow and focused kind of idea. And I used AI for that as well, like straw man, steel man, like here's my argument, poke holes in it, right? Or here's my idea, doesn't make sense based on the industry, and things like that. And when you when you use it in a very focused manner, it's extraordinarily helpful. Like it it blows away search in many ways because it it can contextualize what you're asking, right? It doesn't just go, here's a list of the top 20 trucking companies. But it can pull together lists and say, here's the list of the top twenty green or innovative trucking companies, or here's companies that actually care about their fuel more than others, and things like that. So it's it's very helpful in focusing my research and my thinking. and we're definitely going to deploy it on some level, but it's yeah, it's still in its infancy. And it ⁓ like said, I'm more concerned about getting the good hard data for our system first before running any kind of AI over it because I really think that that's Bigger, I mean my my advisor, his whole company that he's been running, he actually has two, and that's all they're doing is trying to increase the quality and the the the breadth of data that's being collected in the industry because it's often quite limited. Or it's inferred, right? Like we're gonna infer from how many hours we idled, you know, the range is like it's between twenty-five and forty miles of highway driving for every hour. That's a pretty big range, especially if you're a Pete Vera, Exit Algorithms: Yeah. Steven Antalics: smaller carrier, right? Like, or I guess even if you're a bigger carrier and it's extrapolator over a thousand or five thousand vehicles, like is it twenty-five or is it forty? And that's gonna depend on your truck model, you know, all your maintenance, your your whether it's in-house, outsource, things like that, like how much control you have over the intervals and things, all that stuff is very nuanced. And that's where AI can help like pull in all these different variables and make a more coherent focused argument rather than like either Pulling something, know, just randomly off the web, like a study that may or may not apply, or going only by what, you know, no disrespect to people that have, you know, 20 years of experience in industry. But you might have only like my dad worked at JB Hunt. He worked at JB Hunt. He doesn't really understand how Kunanagle, DHL, FedEx, these companies are running their business because he had his JB Hunt hat on, right? And so if you've spent 20 years in the same industry or same routes or same kind of cargoes and things like that, you might not have that broader perspective to say, Pete Vera, Exit Algorithms: Okay. Steven Antalics: Here's how we could take that lesson and apply it differently, or here's a different way of looking at it. And that's what I can be really good at is pulling stuff in that's more kind of adjacent to your industry, but still relevant. Whereas you don't have to do that intellectual work of like trying to figure out, well, I don't really get why a container shipper or you know drayage at Los Angeles port matters if I'm doing, you know, if I'm running up the coast from let's say, you know, Jacksonville to to New York or something like that, and I'm doing, you know, dry bands. Why, why would I What could I possibly learn from these guys? There might be some things that are that are correlates that you haven't thought about. And that's where AI can be really powerful. Sorry, that was quite long winded, but I think the still such early days for AI. It's it's it's you know, there's very few use cases available right now to say this is how AI has made money. People are still trying to figure that out. And that's my best guess as to how I'm gonna use it for the business as as a partner and as an optimizer for a lot of the different metrics that we're gonna we're gonna help people. Pete Vera, Exit Algorithms: Yeah. Yeah, no, definitely. No, I pr I love your insight. I think it's really valuable to use as a a thought partner too. I think it's a area not everyone's taking advantage of. yeah, you know, per really really good insight here. We're we're up Steven Antalics: ⁓ it's it's it's crazy, it's crazy good at some of that stuff, really. Like it it blew me away. Like in some of the things it was able to pull out from what I fed it, I was just like, I never would have I never would have found I would I wouldn't have known to look for this on my own had it not pulled in some random website or whatever. And like I said, if you're focused with your queries, it can be quite powerful. If you're kind of vague, it can kind of go off in the la la land very quickly. But yeah, you just have to know enough to be dangerous, I guess would be the way to the way to put it. Pete Vera, Exit Algorithms: Yeah. Definitely. Yeah, well, we're up on time here, Stephen. one last question I always ask guests is if you had to leave listeners with one practical takeaway for building a valuable business, what would that be? Steven Antalics: Yep. I think the biggest thing is like don't lose sight of like what makes your business good, right? Like don't don't chase returns or I wanna sell this or I wanna flip it or I wanna get investors interested. Because I think it's one of those things like it's it's like a it's like that old saying about like if you do what you love and then like the success will follow. Like if you make the business good. You make money, you have a you have a a robust understanding of your customers, your your things, that's what matters most. And if you try and build a business and say, ⁓ I'm gonna make it, you know, AI first, hyper successful, and then all these investors, like that's it's a double edged sword and it can lead to difficulties down the road than if you just built that good, stable business. And that could be in any industry, not just trucking, I try to keep abroad. Pete Vera, Exit Algorithms: Yeah. love it. Awesome, Stevens. Really good insights today. A lot of great takeaways. If listeners enjoyed it as much as I have, where can they go find find you, find more and learn more about your business? Steven Antalics: Yeah, so ecohol.com, it's quite bare bones, but you can email me you can find me on LinkedIn. So Stephen Antholix, I'm pretty open on LinkedIn. that's the easiest way if anybody is interested to get in touch with me. Pete Vera, Exit Algorithms: Sounds good. I'll leave that in the show notes. Thanks for your time today, Steven. It's great talking to you. Steven Antalics: Yeah, thanks Pete. I really appreciate you having me on.