Episode 7: Freight tech that solves real carrier problems with Don Everhart

Solve real carrier problems with freight tech

[00:00:00] Don Everhart: I trust the robot more than I trust a lot of humans on the road. The problem that we’ll see with autonomous, it’s going to be regulatory. It’s 100% going to be regulatory.

[00:00:10] Todd Waldron: Hello, and welcome to this episode of Behind the Freight. We are here at Fullbay’s headquarters in Phoenix, Arizona, in person. On today’s episode, we’re joined by Mr. Don Everhart, head of partnerships and strategy at Transflo.

Don has spent more than two decades in transportation and logistics with leadership roles spanning operations, pricing analytics, technology, and freight innovations at companies like Swift Transportation, Freightvana, and now Transflo.

He’s built a career at the intersection of trucking and technology, helping carriers modernize operations, improve workflows, and adapt tools that actually solve real-world problems.

Today, we’re gonna talk about freight tech for carriers: what’s useful, what’s hype, where the biggest opportunities are today, and how carriers can use technology to become more profitable and efficient. Welcome, Don.

[00:01:01] Don Everhart: Thanks so much for, you should just walk around with me sometimes just introing me. I love it when other people talk about me.

[00:01:07] Todd Waldron: Yes, I’ll do that. The whole conference, I’m gonna be your intro man.

[00:01:10] Don Everhart: Yeah. Before we kick off, can we just, like, acknowledge the studio that we’re in? We’re here at the Fullbay headquarters, and they have an amazing studio. I’m very appreciative that they’re letting us use that today.

[00:01:22] John Howland: Couldn’t agree more.

[00:01:23] Todd Waldron: I feel like a celebrity now being in this place. I’ve not been in such an advanced studio. Yeah.

[00:01:28] John Howland: Yeah. Cool. So, funny story about Don. You mentioned he’s been in the logistics world for a couple of decades, I would say going on 25 now.

I actually started around the same time as Don in this industry back in the Swift Transportation days, and I always knew that you were destined for something special.

Back in our day, we were planners and logistics coordinators, essentially, for Swift, and that was the green screen for the AS/400.

[00:01:54] Don Everhart: Oh, yeah.

[00:01:55] John Howland: And Don figured out ways to get into, I would say, the backside of the AS/400 system and manipulate things so that we could mess with internal employees, and they wouldn’t know who was doing it. It was the best. So, 

[00:02:08] Don Everhart: Yeah.

[00:02:08] John Howland: , the fact that you could figure out how to get into the AS/400 and do manipulations, I knew that you were gonna do something awesome.

[00:02:15] Don Everhart: I appreciate that. And, John, you’re right. We go back a long way, right? I think I was working as an extended coverage driver manager at the time. You guys were the daytime planners, so we did a lot of handoffs.

And I studied computer science in college, right? But I’ve got deep trucking roots and found myself starting my career at Averitt, right?

And as I spent some time there, you know, it was just like, “Oh, hey, this is solving problems. This is solutioning. I like this work.”

So I kinda set out to find the biggest company I could go to where I could have the most opportunity. So when I hopped over and joined you guys, it was a lot of fun.

I really got to lean in on a lot of interesting things, touched a lot throughout my career, and appreciate every minute I’ve had in this industry.

[00:02:59] John Howland: Yeah. You mentioned it pre-going live, but you had over 13 different roles at Swift. So they would bounce him around where they had a need or there was a gap.

They would say, “Oh, Don can do it,” and they’ll just throw him in the seat. So he was wearing a lot of different hats.

It was really cool getting to experience your journey at Swift and be part of it, and I was there for almost ten years. So, 

[00:03:20] Don Everhart: Yeah, I did fifteen total years there. It’s not a sentence. Yeah. For those listening today, you know, I wouldn’t trade that experience for anything. Got to touch a lot of different areas.

[00:03:30] Todd Waldron: With all that background and now with, like, this focus on technology, do you feel like that gives you a different lens that you view the industry through or view your role through than people who might have come straight into the tech side or the freight tech side? How do you think that’s shaped your view on things?

[00:03:47] Don Everhart: Yeah. I mean, that’s a really good question, Todd. And I think I have a unique view just in general. My grandfather was a driver. I don’t know that you guys knew that prior to this moment right here, right?

Yeah, in Tennessee. So I grew up in a trucking family, just in general. So I knew some of the challenges that truckers faced.

And then having that technology lens and recognizing the challenges that we were going to face, I think some of it was forward-looking, right? It’s because there’s the adoption curve.

And it’s, you can’t just go in and go, “Hey, I’m fully automating your job. Congratulations. Like, work done,” right? So being that bridge kinda helped pull people along to see the bigger picture, to make the connections, it’s certainly helpful. And I view it as a superpower in a lot of cases.

[00:04:36] Todd Waldron: Do you feel like people trust you more too because you’ve seen their roles or been in their roles, or they believe what you’re saying rather than just some tech guy coming in that hasn’t lived it?

[00:04:46] Don Everhart: Yeah, absolutely. It’s funny you say that because even internally at Transflo, one thing that Bill or Renee would say to me is, like, “I love that you’ve lived on both sides,” right?

“I love that you’ve been in the business, that you’ve built a business, that you’ve gone the startup path, and then you also have this technical mind that helps kinda see it and pull it together.”

But, yes, it does build trust a lot faster when you can walk into a brokerage and not show up as a sales guy and say, “Hey, I’ve solved this problem before, and I know the 15 reasons why it sucks to go through this.”

“And I can tell you exactly where we can help solve something and where we can’t.” So it’s more about being able to say what you can’t do in a lot of cases than it is even what you go in and promise. And people know that I won’t overpromise them because I’ve been overpromised before.

[00:05:32] John Howland: 100%. Yeah. Shoot, back in our Swift days, we thought Swift was so innovative in what they were doing with their systems, and yet they were only a few years past the T-cards where you actually get a punch.

They’d give you coins where your check call was actually going to the truck stop making a phone call, checking in, saying how far out you were.

[00:05:51] Don Everhart: I remember systems going down, we broke out the green sheets. Bar by bar, we’re calling drivers, right? Exactly right. Me too, I was there. Absolutely.

[00:05:59] John Howland: So the evolution from that, what you’ve seen from all of that friction-filled process for something as simple as tendering a load to a carrier to what you’re doing now at Transflo, what a crazy roller coaster you’ve been on.

[00:06:13] Don Everhart: Yeah, yeah. And speaking to the Transflo story, I think that’s kind of an interesting story in itself is you’ve got a company that’s been around for thirty years, right?

So I walk in, and I’m like, “Hey, we’ve got all these partners. We’ve got all this tech.” Guys, it took me probably six months to understand all the products we had that were touching the industry.

Whether it’s the TripPak system, right, which still exists, the kiosks still exist, ELD offerings, all of the in-cab solutions that we have. But kind of our growth engine has really been that automation and back office, right?

And that’s back office for not only brokers, but it’s for carriers. It’s for factors. We’re touching transactions, and we’re doing it at a scale that, you know, and I know this is offensive to some people, but at a scale no one else in the industry is doing, right?

So it’s fun, and then you get into some of our newer offerings like our LTL offering, and that’s where we’re really starting to run. Yeah.

I mean, like, stepping into an organization that’s been so prevalent for so many years and to be able to have an impact and to help bring that to the industry is pretty cool to watch.

[00:07:07] Todd Waldron: Yeah. I’ve been following you for some time. I mean, we met probably four or five years ago, and I’ve just loved whether it’s your LinkedIn content or just hearing your name and stories. I think it’s been pretty exciting.

As you shifted into the tech side, what are some of the major lessons from working at a Knight-Swift or, you know, working at the organizations you have?

What are some of the major lessons that you’ve learned that kinda stand out as we here at Behind the Freight like to talk about, which is, like, the journey to today and what brought you to where you are today? What are some of those pivotal moments that kinda stand out for you?

[00:07:53] Don Everhart: Yeah. That’s a great question because I think it’s kinda the core of how I see the world now, right? When I look at tech, I used to be, like, the guy that got excited about everything. It’s like, “Oh my god, we’re gonna change the world. This is shiny, let’s go,” right?

And what I realized, as I have been in my career longer, is sometimes it’s not necessarily a shiny thing, right? It’s the one that removes friction. It’s the one that’s outcome-driven.

It’s the stuff where tech also moves so fast. And I think that’s one of the areas where I’m very fortunate is I get to slow down and look at the fast-moving tech, become a semi-expert in it.

You know, I’d never classify myself as, like, purely knowing everything, although I may come off that way sometimes. But as I look at something, I go, “Alright, well, this is the edge.”

So we can live on the edge, but then here’s current state. What’s a reasonable stepwise movement, right? I mean, we’re seeing that with you guys at Truckstop, right?

I mean, you’ve had all of this innovation over time, and I know Scott is moving at an incredible clip right now. I know because I get the texts from him, like, “Hey, how do we do some stuff,” right?

And as we look at that, you’re not, “Hey, how do I deploy more AI and call this thing AI?” It’s more, “How can I improve the outcome for the driver?”

The driver is central to everything, and that’s one of our core tenets is what problem are we solving, right? So it’s an interesting space to be in right now, primarily because I believe that we’re in an area of, and I’m gonna butcher a quote from someone.

I don’t know if it was Jensen or Elon or who, but, like, we’re living in exponential times, but it looks linear because we’re on such a short time horizon. So as we’ve kinda shortened up, it’s like, I don’t know what tomorrow holds in a lot of cases, right?

I don’t think any of us do. I do know that adoption’s moving a lot faster. I think you guys are seeing that as well with what I’ve heard from some growth stories there, but we’re seeing people, like, lean in on solutions, and solutions are solving real problems. Yeah.

[00:09:57] John Howland: For sure. I know you’ve been dabbling within AI for quite some time,

[00:10:01] Todd Waldron: …which is awesome, by the way.

[00:10:02] John Howland: Question for you: What is one area where carriers should or could be using some AI or some automation, in your opinion, to help mitigate and/or maybe eliminate some of that friction that you mentioned?

[00:10:14] Don Everhart: So it depends on the size of the carrier, right? Because different size carriers are gonna have different problems. There’s some players out there that are doing some things for the owner-operator around, “Hey, how do I post my truck and handle the 150 phone calls and make sure I’m getting the premium rate without answering 150 phone calls?” Right?

So we’re seeing that. So how do I call and negotiate with a bunch of brokers when I really don’t have time to, because I’m only making money when the wheels are rolling, right?

As you get into the mid-size carrier, I think that’s one of the areas, mid-size enterprise, that’s where we and others are starting to show up and go, “Why are you touching and invoicing so many pieces of paper?”

“Like, why is your process, like, filling out a Word document and printing it off, scanning it in, and sending it off to someone?” Those are areas where I think they have probably the most impact.

Outside of that, your larger carriers are finding things around optimization on routes, because we can just evaluate more at this point in time, right?

The times of, like, “Hey, we’re gonna let Manhattan run another cycle”, no offense, Manhattan, because they’re also working on things, but at the time, it was like, “Hey, we’ll wait till Micromap runs its next resequencing based on all of our planning here, you know, two hours later because that’s the sequence we have set up on.”

It’s like, no. Now there would be 100 new loads that were booked, and these 50 that got covered, what’s my now optimum network to roll with, right? And you see a lot of people playing in that space and doing a really good job.

[00:11:46] John Howland: So hypothetically, because I know you’ve been part of a startup and were helping as a managing partner: If you were to start a small, let’s just say a five-fleet trucking company today, where is one place that immediately you would say, “Hey, we need to automate this piece of the workflow,” if you were running a small fleet?

[00:12:03] Don Everhart: Probably primarily around my load acquisition strategy. So how I’m interacting with load boards, how I’m interacting with brokers, trying to get as much as I can into my hands and my decisioning. But to do that, I have to have the hands. So in lieu of people, I would be leaning in on AI pretty heavily in that space.

[00:12:22] Todd Waldron: I had to jump into the future. I wanna find out how far into the future and talk a little bit about autonomous. So we’re here in Phoenix, and I love riding in the Waymos here in Phoenix. So I rode one here.

Last time I was here, I left my cell phone in the Waymo, which makes it incredibly challenging to get your cell phone back because you need your cell phone to connect to the Waymo. One story.

Two story: I was on spring break down in Texas with my kids last week and returned my rental car the night before I was gonna fly out. I got an Uber to pick me up from the rental car facility. The driver drove into the rental car area and then could not find a way to exit, and drove over the spikes to exit.

[00:13:04] Don Everhart: Oh.

[00:13:05] Todd Waldron: I was looking at my cell phone, and all of a sudden, I hear the sound. I’m like, “Oh, man. All four tires flat.” And I share those stories because I think there’s pros and cons to both sides of this, right?

But as we look at trucking, I’ve always been a long-term, long-side autonomous in trucking, but I’m starting to hear and see more of that exponential advancement.

Where do you think we are on that, and where autonomous will really have a meaningful impact in the industry? And also, what’s needed to prepare the path for that from an industry perspective? I’d just love to get your take on how you see things from your purview. Yeah, it’s a lot.

[00:13:43] Don Everhart: Yeah. So it’s interesting because, one, when we look at autonomous, the incidents per million miles is an order of magnitude lower than a human. So in a lot of cases, and I say this from a place of privilege, right?, I trust the robot more than I trust a lot of humans on the road.

Now, I also haven’t been rear-ended or hit by an autonomous vehicle yet.

[00:14:04] Todd Waldron: Yet. Yet.

[00:14:05] Don Everhart: That might be the end of my story. That’s how we wrap, folks. So as far as, like, adoption and where we go, we’re seeing a lot of acceleration from the largest AI companies and compute companies, right?

So a lot of this is going to be driven by edge-driven AI, right? And the acceleration there is astounding. I can do stuff on a personal PC that, you know, is a nice PC, but that would have taken, you know, a rack in a data center some years ago.

So as we see that acceleration, I think we’re going to see better models, better decisioning, better inputs from sensors, smaller sensors, which means more sensors.

The problem that we’ll see with autonomous, and I would love for the autonomous guys out there to just call me up and tell me I’m completely wrong on this and that they’re going to take over the US widely, it’s going to be regulatory. It’s 100% going to be regulatory.

Like three years ago, you know, we’ve got, I think it was Frito-Lay in Chandler, or maybe it was Pepsi in Chandler, not sure who it was, but there’s autonomous trucks running between here and Tucson. They’re just up and down the road, right?

I’ve sat in the Aurora trucks, like, phenomenal product. And we’re seeing more adoption. So, you know, Texas is pretty friendly, Arizona’s pretty friendly, California’s friendly-ish, right?

I think as we see expansion and regulation in some of those heavier freight lines, we’ll actually see an explosion, the good kind of explosion.

[00:15:38] Todd Waldron: I’ve been curious about the litigation side of things and the liability side of things because now you’re taking in, in an industry where liability is already moving upstream or has been upstream and trying to get to the bigger and bigger pockets, you take out the driver, which could be looked at as a scapegoat in a lot of scenarios and situations.

But that’s where I’m interested to see how this shakes out: Yes, they’re gonna have a lot less accidents, but when they do have an accident, where does that liability lie? With the tech company or the person who decided to put the tech in charge of driving the equipment?

And how that’s gonna shake out from a legal standpoint is gonna be interesting.

[00:16:14] Don Everhart: That’s a Matt Leffler question all day long right there. I do think it’s interesting because there’s a lot involved in AI in general. Like, a lot of people are just thinking in terms of, like, LLMs or small language models.

And I use language model loosely, right? Because we have reasoning and decisioning that’s out there. But it’s really about the entire AI harness, right? So if I have an AI harness that’s consuming information, is making decisions, but I have tooling tied to that, is the tooling responsible?

What if we had latency on the tooling? Was it a model problem? The model’s largely a black box for us at that point. I think you’re hitting on one of the things, right? And I don’t know that any of us know the answer.

Are you gonna go after a frontier model company? Probably, because they’ve got all the money. And quite frankly, lawsuits follow the money. We all know that from having worked in carriers.

Doesn’t matter if it was the brokered truck, if it was a two-truck fleet. Whoever’s got the money, they go after.

[00:17:08] John Howland: Yeah. We know that from our Swift days. They showed up calling, for sure.

[00:17:12] Don Everhart: Yeah.

[00:17:12] John Howland: But I feel like in the same vein, these autonomous trucks will likely have, obviously, like, a lot more camera sensors. It’s gonna be easy to determine who’s at fault very quickly as well.

Do you feel like with the advancements of the autonomous world and autonomous trucks that maybe there’s gonna be less litigation and things happening from a legal perspective because of all of the advancements in what the sensors, or, 

[00:17:42] Don Everhart: , more, because you have more information, right? So, unfortunately, I grew up in a time where as a broker, it was like the less you know, the better in some cases, right? And that’s no reflection on the brokers I worked for, but that was just the industry, right?

[00:17:54] John Howland: There’s a reason they have a carrier-broker agreement.

[00:17:56] Don Everhart: There is.

[00:17:56] Todd Waldron: And inward-facing cameras is a perfect example of there’s pros and cons, but it potentially gives more information and adds liability when it’s not even the necessary cause of fault.

[00:18:06] Don Everhart: Yep. Now, all that clears you very quickly in a lot of cases, but I do worry about how much data ultimately comes together on the autonomous side.

Now, if you’re a driver out there that wants to defend actions because now we can actually see the action, I think that’s a different story. And by the way, you can call me at Transflo. We’ll take care of all of your camera and ELD needs. Shameless plug.

[00:18:27] John Howland: You can work as though you are autonomous, but not with a real…

[00:18:31] Todd Waldron: So I feel like there’s a lot that’s overhyped in the industry and has been overhyped, but what do you look at that’s overhyped right now when it comes to trucking technology?

[00:18:40] Don Everhart: Oof, you’re gonna get me in trouble. That’s the point, Don. I don’t know. I think… Pass. He says, yeah, hard pass. I think it comes down to what your actual moat is, right, as some of the providers in the space.

And I have the pleasure of working with, like, several, and I’m partnered with several different players in the space that are doing different things with AI, right? We’re primarily an AI company when it comes to our workflow and all our stuff.

So we also have years and years and years of data that others don’t have that allows us to make different decisions, just like Truckstop, which is why you guys are a great partner for us as well. Like, we get to do some very interesting things.

I think when I talk to or advise a newer AI entrant, one of the first things I ask is, I go, “What’s your stack? You just walk me through your AI stack, you know?”

It’s the simplest question to ask someone, and I encourage anyone to do it. And one, if they’re hesitant, or, “Oh, it’s a proprietary model.” Okay, like, proprietary models, you can do fine-tuning on them, that’s great.

But what’s truly proprietary about your stack? You don’t have the history, so you don’t have the data moat. So what’s your moat? And someone should be able to answer that.

And a lot of times, what I’ll hear is, “We’re using”, and I won’t name the platform because that’s just rude, “but we’re using this platform for our voice. We’re using this LLM for our guidance. We’re using this LLM for our reasoning. Here’s how we’re doing our communications.”

And it’s like, I can go sign up for all of those things while we’re sitting here, and we can wire them up in an afternoon. What’s your moat, right? So I think that’s one of the areas where I’m skeptical is, again, it has to be outcome-based and has to solve a problem. So it’s cool that you can do certain things, but what problems are you solving?

[00:20:26] John Howland: Maybe one more question, and then we’ll get into the lightning round.

[00:20:29] Don Everhart: We got lightning rounds? Oh, yeah. Uh-oh.

[00:20:31] John Howland: This is my favorite.

[00:20:32] Don Everhart: Okay, I love it.

[00:20:34] John Howland: So, ask kind of a two-part question. One is around: What does really that next generation look like for just back-office operations for carriers? And then two, with that being said, how can brokers better work with carriers to leverage and utilize that back-office work?

[00:20:53] Don Everhart: Yeah. So when we think about the back office, it has been a not-so-glamorous job for a long time, right? So it’s tedious. It’s looking at paper. It’s comparing to other information. I would even say not next-gen, but current-gen is: Why are we looking at everything, right?

Like, we have the information. We can get the extract at high, high extract quality. We can compare it to the information, and we can do it across a lot more than, like, one or two fields, right? So if we can look at all of it and evaluate and flag, it’s like true exception management is kind of where it’s at.

And then, so that’s current state. And if you’re asking about next state or next-gen, it’s more around what that agentic resolution looks like. So if I’m going to have a person look at something from an exception perspective, is it very difficult work? Do I have to go do a bunch of different stuff?

Or is it really just I need eyes on it and I need a knowledge base I’m comparing that against? It’s still difficult work, but it’s not the most difficult. And I think you saw that, saw in notes that you saw that about kind of our LTL platform.

It’s like, or something I post on LinkedIn, it’s, hey, it’s one thing to take it down to now you’ve got, you know, 10% of stuff that you need to look at instead of 70 or 80%. What if we cut that further to 3%? Now you’re doing meaningful work, right? And you’re not just moving things around. So that’s one of the areas that we’re seeing a pretty big lift.

Beyond that, I think a challenge that we have, because I love presenting solutions, but a challenge that we have as an industry, is then we believe pretty heavily in reallocation of resources, not replacement of resources. So what upskilling are we doing?

Like, what other value are you going to seek in your organization? How should you redeploy those resources to better work, you know? And on the broker and carrier side, I think relationship is key, right? I think we all believe that.

And it’s an easy thing to say. It’s a very difficult thing to execute. So if you’re going to remove the tedious work, spend that work with human time. Let’s let software be software. Let’s let agents be agents and agentic happen.

Let’s not depersonalize it to a point that you’ve already got a driver that’s locked on the road, and most of his or her interaction for the day is staring at the next sign that’s upcoming and being away from their families. Let’s make it more personal. Let’s make it more personal for the driver.

[00:23:29] Todd Waldron: Yeah. That’s something I’ve been talking a lot about is the incredible importance to evolve the way that we handle relationships with the evolution of AI. 

The other thing is, when I was running a brokerage and running an asset-based company, I think it was so easy to look at the next shiny object and thing, and it was hard to make decisions over what technology to utilize, and there’s so many different options.

But at the end of the day, technology was not going to replace or have success without a solid process and solid people. And so it’s like, you can’t expect if your process is broken or you don’t have the right people for this to be successful or all of a sudden be the magic bullet, it’s like you have to have that foundation first.

And the other thing I saw is involving the people rather than forcing it down. I saw a lot more buy-in when we’d involve the team and get them engaged, and the excitement would come from that involvement.

[00:24:22] Don Everhart: Some of our biggest advocates are the end users. Like, hey, would you much rather spend your time, like, focused on the stuff that actually gets something done? 

And to that end, I think AI actually drives us to a place where we are a more personal society, not as cold as I think some folks are struggling with the adoption. I think that’s end state.

[00:24:42] Todd Waldron: Do you say please and thank you to your AI?

[00:24:44] Don Everhart: I do, but just because I wanna waste tokens.

[00:24:42] Todd Waldron: You probably don’t, do you? You’re a sales guy.

[00:24:48] John Howland: Yeah, no. You’re not gonna, I go fast. And if they don’t give me the answer I want, I go out…

[00:24:52] Don Everhart: …of the game.

[00:24:53] Todd Waldron: I’d say that’s about right, yeah.

[00:24:54] John Howland: Lightning round! This is my favorite. Alright. Hopefully, you didn’t cheat and look at these.

Don Everhart: I’m not looking at this. Good. I refuse to be prepared, John.

[00:25:02] John Howland: Yeah, I love it. Love it that it’s gonna make these better then. Okay. If animals were to jump in the driver’s seat of a big 18-wheeler and drive a truck down the road, what animal do you feel would be the best driver and why? Oh. Uh, now you wish you were prepared.

[00:25:17] Don Everhart: I’m gonna give you two answers. I know I only really get one. Hyena, like, they’re running miles, man, right? Like, let’s get it done. Look at that, look at that. Now, from a safety perspective, maybe, maybe an elephant, like, we’re never gonna forget anything, like, we have our information. But from a getting it done and getting down the road, 

John Howland: That’s good.

Don Everhart: , getting that paycheck, hyena all day long.

John Howland: There you go. Love it.

[00:25:38] Todd Waldron: Finish this sentence: The freight industry will be meaningfully better when?

Don Everhart: When we drive respect for our drivers throughout the industry and the job that they have.

[00:25:47] John Howland: Yep. Well said. And then last one: What is one metric, number, or one thing that a carrier should focus on weekly?

[00:25:56] Don Everhart: Their health and them personally, right? Like, it doesn’t matter how many miles you drive. And, John, I’ll hit on something that we used to say at Swift, right? Nothing matters if we don’t make it back to our most important stop.

[00:26:08] John Howland: Damn. Yeah. Deep, dude. I love that.

[00:26:10] Todd Waldron: And he lied, it wasn’t the last one. Who’s someone in the trucking industry doing great work that people should follow or learn from?

[00:26:17] Don Everhart: Follow or learn from? I’m really impressed with the team over at MyMechanic, right? So Alex Bizovitz over there, CEO, sharp guy, really shaking things up. I think he’s one to watch for sure.

[00:26:32] Todd Waldron: That’s awesome. Don, it’s been an absolute pleasure. Where can people find more about you? Can they reach out to Transflo?

[00:26:41] Don Everhart: Yeah, absolutely. Transflo.com for Transflo-related. [email protected]. I also organize the FreightTech landscape at FreightTechToday, and my number is floating out there everywhere. So I also encourage people to just call me. I’m a talkative person, as I hope was evident today.

[00:26:58] Todd Waldron: Yeah. Man, it’s been a pleasure, and, 

[00:27:00] Don Everhart: , thank you for joining us.

[00:27:01] John Howland: Thank you. Going back in the day. Love it.

[00:27:03] Don Everhart: Back in the day and into the future.

[00:27:05] John Howland: That’s, oh, good. Lots of nuggets today. Thanks, Don.

[00:27:08] Don Everhart: Yeah, no problem.

[00:27:09] Todd Waldron: If today’s episode helped you think differently about your operation, share it with someone in your network who needs to hear it.

[00:27:16] John Howland: And if you’re looking for tools to help keep your truck rolling, from finding quality loads to getting paid quicker, well, Truckstop.com is here to help.

[00:27:24] Todd Waldron: Go visit Truckstop.com to explore the load board, rate insights, and risk management solutions built specifically for carriers and brokers. Thanks for listening to us at Behind the Freight. Until next time, keep the wheels turning and the bad loads burning.