Hey, everybody. Welcome to another Banyan Technology’s Tire Tracks Podcast. I'm Patrick Escolas, and continuing our discussions on AI and logistics space, we're talking with Vooma and specifically their founder, Jesse Buckingham. How are you doing, Jesse?

I'm doing very well, Patrick. Thanks for having me on.

Hey, thanks for being here. Before we get started, you sound very, very fancy. Where's the accent from?

Yeah. As I say, not from Alabama, right? I moved to the US 10 years ago, that I'm originally from Australia.

Okay.

So, grew up there, but married an American woman and I got two little American kids over here now. This is my second home down here on the West Coast.

Now, did you come over before you met her, or after?

It was all intertwined.

I was going to say, my thought was she went to Australia to get out of some snow. Then you came here and now you – Why the US over Australia, when you could go back and forth and never have to deal with the season you don't want, right?

Yeah, it's true. It's hard to maintain a stable job with that set up. But maybe at some point in my life, I’ll be able to swing that.

That'll be the future. No, so you're the co-founder of Vooma here. Start off, what is Vooma and how did you come around to get to this idea and where you're at now?

Yeah, for sure. Yeah, so I’m co-founder of Vooma. We're a platform that enables logistics companies to build and manage their AI workers. We have –

A little more of that now than maybe five years ago, huh?

Yeah, exactly, exactly. There's a lot of heat around it at the moment. But we enable brokerages, forwarders and carriers to be able to build AI workers that can execute use cases all across the load lifecycle, so email, quoting agents that can operate, build loads, schedule appointments, handle inbound carrier calls, outbound carrier calls, track and trace, really with it to be able to orchestrate pretty complex workflows.

Prior to this, I was a CEO of a group of logistics technology businesses, backed by private equity fund. We had a fleet inspection platform by a lot of truck and trailer leasing businesses, good CMS platforms, not focused on final miles. These were used by delivery businesses, but full TMSs and then led the acquisition of trucker tools prior to recently, obviously sold to a team and carry-led that business and did an awesome job. I was involved there, and then stepped out to build them with my co-founder who comes from the world of self-driving trucks. He was a founding engineer with Kodiak Robotics, which is one of the leaders in self-driving trucks.

It's awesome.

They, yeah, announced that they're going public now, which is very cool. Then Mike was employee number two there. He built their motion planning controls and safety teams, which is a lot of the brains of a self-driving vehicle. What we really teamed up – 

He’s pretty smart.

Yeah. That's the other way of describing it. Yeah. He knows how to build difficult things. We teamed up really with this view to applying and similar principles to, you mean, you think driving a self-driving vehicle, it's like, you've got to make decisions in uncertainty and get them right. We're applying a lot of similar frameworks to –

Yeah. Maybe with a little softer edge, like you're not going to plow a car into the ravine and you might just be 10 minutes late on a pickup.

Yeah. Exactly. Errands are costly, but it’s like 100,000 pounds going down a freeway and then the records number is wrong on a bug, you know.

This is the relaxing of retirement from the high stress of how are we going to put these on highways with other people? Yeah. Oh, and for your sake, you were in the different logistics spaces before, where did that start with you? I'm always curious about why did logistics take hold of your life? I know for me, it was by accident. Some people were born into it quite frankly. Where does that start for you, Jesse?

Yeah. I mean, I've always been very passionate about technology and its ability to impact on the world, but I've also felt that I moved over to the coasts and that there's just a lot of important real-world industries that folks in San Francisco don't often have a lot of exposure to, and that you get a lot of very talented engineers that know their own developer problems. Then a lot of people that have a deep understanding of industries that power the physical world. It's changing, but historically, not often a lot of overlap. I've always just been passionate about leaning into those spaces where you get the opportunity to try to bring world-class engineering to bear on these problems that actually impact the real economy. That was always my motivating factor.

The way that it came into logistics was a little bit of a term, because I started running this fleet inspection platform. I was a CEO there. Then we saw this opportunity to start acquiring and growing other logistics companies and got into the full truckload.

They're like, “Why don't you go acquire some logistics company?” You're like, “Any more specific than that?” They're like, “No, you got this.”

Yeah. Well, I mean, it's such a massive and important industry.

It touches everything. What's ridiculous is unless you're in it, it's the unseen industry somehow.

Yeah, totally. Yeah, and –

Go ahead.

No. I mean, I fully agree.

With that, and it being unseen, and I think another part you said is pulling these pieces that generally might not be together. We're seeing a lot more of that. Hey, everybody's trying to do more with less since the COVID onset, but with AI popping up, it seems really to be this center focal point of every industry for everything. I've talked to quite a few people on AI within logistics, but you guys are doing it differently than I'm talking to, because it's not, hey, we're doing this background for our analytics. It's really more of this front end. We've talked about a chat box. But I'm not going to a web page to go to your agent. How am I interacting with it? Because from what I understand, that's the unique aspect, or at least one of the unique aspects for Vooma.

Yeah. Yeah, it means a lot of different things. Previously, often, when people talking about AI, they were talking about machine learning, which is about analytics. That's a very powerful type of AI for the right use case, but it's usually quite focused and narrow. It's very good to predict the price of a truck over the next.

But you couldn't ask it to describe a truck just from – You could, but it wouldn't be as good if you haven't lined it up and set it up for that one thing.

Yeah. Language models allow us to actually build. I mean, ultimately, it’s software that essentially, agents that can communicate, so it can understand human text, voice. It can perform actions. It really unlocks a set of use cases that were not previously addressable through predictive analytics. What are agents, like very practically what it looks like is if you are a logistics professional, the agent will sometimes be acting in the background. A spot quote request might come into your inbox. Hey, I will identify that that spot quote has hit your inbox. It will extract the relevant information and it will go and look up a bunch of different benchmark rates. It will help to draft a response to that and then fire that off to the customer. You could be scheduling an appointment.

That's awesome.

Yeah. The load hits your TMS and then that triggers the agent to look at the shipment and figure out what the right appointment times are, and then either call, email, or navigate to a web browser to be able to go and book that appointment. Could be that you post one of our agents on a load when you post it on DOT, or truck stuff, and you've got carriers calling in. The AI can handle that phone call end to end. Verifying the carrier’s MC by looking it up on tools like Highway or RMIS, or others, figuring out what load, negotiating, even issuing the rate con.

Then there's other use cases where you can dispatch work to the AI, right? Where it is a co-pilot, or an assistant that sits there to serve you. You might say, “Hey, can you check on in on this load for me?” It will go back and tell you what the latest update is. If that's not good enough, you could say, “Cool. Let's go and check all that carrier.” There's a bunch of ways. Some of these, like the actual logistics professional can drive. The others that AI is monitoring and observing and taking action in the background.

Is that more of it being an assistant, or my girl Friday, versus it's actually saying, “Hey, yeah, that's the price I want. Go ahead and dispatch.” You're sitting back with your feet up going, “Man, I wonder where my trucks are going today.” Where's the line between I want it automated, but maybe I should press the button. Where is that with Vooma, and what is your perspective going to that point? Is that your idea, or is that something you worked with brokers, carriers to get to that?

Yeah. This is a continuum and it's not one or the other. A lot of it is around what is the level of your confidence in the AI to make decisions itself in some environment. What is the AI's confidence in making the decision?

Fair point.

For example, you might say, “Hey,” for an auto-quoting scenario, you're like, “Hey, if this is a drive and load-unload lane that we move a lot when it's not a weekend pick up, or a Friday pick up and there's no tapping required, I feel pretty bump it in the air.”

Yeah, it's your bread and butter run. Right. Yeah.

Let that rip. Whereas, you'll have some scenarios where the AI will not have uncertainty. Facing it, you're scheduling an appointment and the facility comes back and says, “Hey, that PO is not in our system.” Well, that's probably a scenario where either you need to build an SOP for the agent to be able to figure out and resolve that issue, or maybe that's a situation where you kick it up to the human and say, “Hey, I run this issue.” A lot of this is a collaboration, right?

I had a great moment where I just imagined Hal from space is like, “Hey, Hal. I can't find the PO.” Yeah, being confused. Yeah. It's like, yeah, welcome to being a broker. You're not just a freight anymore.

Right. Exactly. Yeah, I love that. It's like a dystopian version of a pal. We try to think more about the her version of it.

Of course, that would be much more, because no one's taking this thing to space either. It brings up a lot of point that it has a confidence level. Then is it displaying? Walk me through, as you were saying, it sounds like there's probably two or three different ways that your system is helping and using AI. Tell me more about that directly into email aspect, because as if there's anything that I know about logistics, it's either you have software because someone told you you need it, or you begrudgingly are still using Excel and an Outlook and email and you don't see any reason to do anything differently. I'm very curious about how that works, because I would imagine that the second you go, you don't have a separate login, it's just your email, that's going to open a lot of people's eyes.

Yeah. I mean, you're picking up on something that I think is quite important. Logistics is very fragmented. There's something like 200,000 shippers, 20 odd thousand brokerages, 300,000 or 400,000 tracking companies. You've got everyone on different systems, right? Or no systems at all. The industry has ended up converging on these protocols around email and phone calls in a lot of scenarios, or EDI, which is not maybe the best way to transfer data, but everyone uses it.

It's the lowest hanging fruit, right? It's the lowest obstacle, or bar because everybody can open a Gmail account. You have a cellphone already and the banks are already using EDI, so get with it.

Yeah, exactly. I mean, I think it's been interesting over the last 10 years. I think there's been a lot of attempts in the logistics industry to try to get people on common platforms. The truth is, it's too fragmented. It ends up falling back, and a lot of these communications ends up happening in these channels. It was a problem, right? Because previously, you needed a lot of people that were doing quite tedious and transactional work to be able to sit and man those channels.

Absolutely.

That's what's powerful about AI is that you can have your cake and eat it, too, in a way. You can reduce the cost to being able to transact. You don't have to get set up with a shipper now, instead of saying, “Hey, I need a three or four month EDI implementation that's going to cost me thousands of dollars and need thousands of dollars. In the meantime, I'm not earning any business.” You can just say, why don't you just fire that off out of your TMS, or just send it over email, and we'll create it live. It turns your email into an API channel, where you can have the flexibility and speed and lower set up costs, but be able to get the same productivity benefits.

That's a great statement. Turn your email into API. With that, is this something that is more, and I know in your software past life, you talked about the TMS is being final mile specific. Is this something that is specifically targeted at truckload maneuvers, or is this LTL? Are there limitations? Are there specific better applied modes? What is what does that look like?

Yeah, today we work with folks really across multiple modes. Obviously, I mean, truckload being the biggest sector, we started there.

That'd be easiest for your AI to be like, “Oh, that much needs this cargo. There's the lay in. Can get pricing out.” Whereas, LTL is like, “All right, now I got to go check how much is going back and forth from there, how full is my truck.” 

For sure. We do do LTL locally and quoting today. It's a little bit more complex. There's a little bit more back and forth. For an LTL scenario, it's a perfect application, because what we see in LTL, especially in LTL brokerage, the margins are very slim. Maybe you're a truckload broker that does some LTL, you have any to spend three or four times going back and forth, clarifying the NMFC code.

You've basically lost your margin, because you spend all the time. Yeah.

Yeah. We're building agents that can handle all of that back and forth. Make sure you're getting, calculating what the break classes, hitting a bunch of APIs, helping to select a carrier that you want to present to your customer based on their preferences, being able to actually accept that and book it end to end. Pretty powerful. That changes the game there. There's good business to be done. A lot of this is figuring out how you reduce your cost to serve for these types of business that were previously challenging to do.

Plus, as I'm just thinking and visualizing it, it's 3D Tetris. A computer, an AI logic can do that math that cubic dimensions, how much space I have, can this be stacked, etc. Where's the best stops? It makes a lot of sense. We'll go into more benefits later, but I'm a glass half empty kind of guy. What kind of cons are there to AI, or does the customer have any negative feedback and probably a minority to your mass demographic? Do you see any pushback for the AI? Because initially, we saw a lot of pushback to AI. I think nowadays, everybody's like, “Well, yeah. I use ChatGPT to tell my sister happy birthday, because I really don't want to talk to her,” all the way from everybody's using a part of it somewhere in their lives for the most part.

Yeah. Yeah, totally. Look, I think it's rapidly evolving. On the customer side, there's a bit more sensitivity. Most of the time when we implement that, we're implementing as an extension of the person who is controlling the interaction. We're taking a bit of in a quoting scenario, we may not respond directly, but we'll do all the legwork. You don't want somebody going in and entering shipment data in four different sources to try to make sense of it and figure out what it did last time and what does the TMS say, right? You can automate all of that, present something, and then they can add their human flair and verify. That's dramatic improvements of their productivity, and ultimately, provide the better service to our customers.

We have a customer that we implemented, where they were using us to help accelerate their workflow, but their customers were like, “You guys are responding – used to take you half an hour. Now, we're getting these quotes back in three minutes. Is this a bot responding?” They were like, “No, it's actually not. It's humans doing this, but they're doing it –”

The bot's telling me all of the information that it would take me 30 minutes to go find.

Yeah. It’s like superpowers, right? That's a really awesome experience. A lot of people in logistics, they have something they want and they want their needs met. If it's done high-quality efficiently, that's often what matters the most. On the customer side, the human dimension is really important. Often, if you're posting on a loadboard and you've got a carrier calling in, some people it's a very small fraction that don't want to – what is that they often don't, can't tell that it's AI, right? Because the quality is really, really good.

As long as the email isn't started with, “I hope this finds you well,” because I don't know why every AI thinks that that is how humans greet each other.

Yeah. Yeah, exactly. You've got to control these things. For voice calls, most of the time people can't tell.

Really?

Of course, we recommend customers you should tell someone if they're interacting with AI. They want to know the load details, they want to know the appointment times, they want to know how heavy it is, and if there's any flexibility. These are the things that they want really, really quickly, so that they can make a decision about whether or not it's a good move for them.

It's me calling the old movie phone to see what the times are, and I don't want to talk to anybody, really. I just need these pieces of information and I'll go from there. Okay.

Right. They're sitting on hold most of the time. 30% or 40% of those calls are on hold for three minutes. That's not a good experience, actually.

No. That makes a lot of sense. That being a positive, as far as speeding up the workflow, being one of the benefits and one of the reasons somebody interacts with Vooma, what can you see from a rating side as I'm with a TMS company selling to logistics space. The rating process is always such an important piece. Obviously, you talk about confidence level, but in margins, what does this do? Is this going to have any effect on the overall logistics trend of pricing, whether it's your carrier, your broker, or your customer. Now that we have this influx of technology and it's making it easier, is that going to reduce the price, or is it just going to make –I would see it as a reduced cost, because I have less people doing it. But I don't know enough. Otherwise, I'd be a much better investor.

Yeah. I mean, if you think about what this presents is in logistics, if you are able to price aggressively with your customer, generally you're going to win and take share. If you implement technology that allows you to reduce your cost per load, then you get the opportunity to bid freight at a more aggressive price maybe than your peer, so you win share. You get this flywheel turning, because as you start to grow volumes, you're often able to then buy better on the carrier side. That's how you get this flywheel turning.

A lot of it starts though with like, hey, what is your cost to sell in the current market, where rates on where I think we want them to be, your main lever there is thinking then about, okay, what is your operating efficiency and how do you continue to scale your load volumes with the same team that you've got in place? That's a lot of what AI enables you to do. A lot of our customers, they implement this and they see dramatic improvements in their efficiency, but these are all growth-oriented brokerage, that they're not necessarily looking to let people go, but they've got ambitious goals to grow 20 to 100, sometimes even more percent over the next 12 to 18 months. They want to figure out how long can they delay hiring that next person, right?

Or how long is it going to take to find that next person, let alone onboard that next person?

That's a lot of this, right? Especially when you think about some of these jobs that are focused on order entry navigating portals to schedule. A lot of these are like, it's hard to train and retain people in these jobs, because they're not that – That's not the part that people love. When you talk to folks about why they love logistics, it's because you're always solving a problem. They develop a relationship with the kit. Those are the things that people like. No one's sitting there thinking like, “Oh, my God. I love –”

I just love TMSs. I just love TMs. I want to stare at this screen all day, because I want to press the button over. You're right. It's a means to an end. I like the industry. I like the paycheck and I like winning business. What kind of systems, because I would imagine that the AI agents aren't standing alone that you're propping up, what kind of systems are they connecting to on these brokers, these carriers that you're dealing with?

Yeah, it's a very wide range of systems. Obviously, the TMS. We integrate with a number of different TMSs through a bunch of integration methods to be able to retrieve and put data back in once the agent does some action. We also integrate with a lot a lot of the different rating engines, benchmarking tools, all across a lot of the big ones in the industry to be able to help power a quoting product.

Right.

Then, we integrate with carrier verification tools. Really, if you think about what a person does in a brokerage today, they spend probably 30% to 40% of their time in their email, 30% of their time in the TMS, and then 20% of their time in a range of different other tools, load boards, carrier verification tools, etc. Our agent needs to be able to interact with all of those systems as well. Some of those will have direct API connections. Other times, well, the AI can actually navigate to web pages and etc., to retrieve and put data.

I was going to say, you probably have an easier time with that than some players in the past, because you're already using AI that's good at crawling through data, so you can get these integrations in place. If we're in play and you have customers that you've been doing, and how long has Vooma been on the scene?

Yeah, we started business about two years ago.

Okay.

Are you still at a spot where you're trying to grab more ground, or are you already looking to the next level of what you can do with AI? If you are, I'm curious, what does that look like? Is there an opportunity for any of this to go customer facing, rather than on the forward, or brokerage carrier side? Even if it isn't, like you said, there's opportunity, a bound regardless. But from someone that has worked both sides, I'm always curious, is there something that makes this just one side of the coin?

No, there isn't. I think that there's a journey here, right? Today, a lot of our focus is helping logistics team perform their work better and more efficiently. Over time, we expect to see customers and carriers being able to interface with AIs that represent the business to a lot of these transactions. We're already doing that with a lot of these pieces, right? We’ve got carriers calling in on loads, add some variant of it. You could imagine extensions of that, where the AI can help a carrier with whatever their needs are. Maybe they want to check in on a payment status, or today you got a lot of people.

Our aspiration here is to be able to build a unified experience for both customers and carriers to be able to interact with a logistics company, AI representatives, where that makes sense, right? Where there's some functional interaction that needs to happen, that AI can do really well and really quickly for them.

Now, talking about AI and what it could do quickly and well, and probably something that you touched on that I went right over, we talked about dispatching, we talked about defining it, but on the auditing and the accounting side on the back end, is there a part of your product that's touching that? Is there a lot of value? How is that difference of a playstyle, too? Because obviously, we've talked about the front-end, how that can be different, how you could manage a team of agents to get you to the spot that you need as the human to get involved. What does that look like on the audit side?

Yeah. Today, on the back-office side, most of what we help folks with is the retrieval and collecting of documentation. There are folks in the industry that focus specifically on those cases that are really good solutions. I think it's an excellent application of AI, because there's such a – A lot of this is having a very nuanced understanding of what are your contracts, what are the requirements. Actually, if it's on the carrier side, what do we agree to? What are you going to charge us for? We approve that. Did we not? Is that part of our agreement? What should we be building back to the customer? With the right system, you can build AI that can handle a lot of that.

I guess, what is the – we're talking a little bit about the benefit here, but looking out to the landscape, if I'm a carrier, or broker that's not starting to utilize these technologies, whether it's AI, or just the integrated aspect of, even if it's some of the pre-existing software, what do I have to lose? Or, can I still carve out my corner and work with my Excel and my Outlook without getting anything new? What's your take on that?

Yeah, it's interesting. There's going to be exceptions to this. But in general, I think that some businesses that are fearful of adopting AI, but the dynamic that is going to play out here, in my opinion, is that the businesses that figure out how to effectively implement AI are going to be able to win and outcompete. That's not the business that you should be scared of. The business that you should be scared of is the one that is not doing this. Because I think we're talking about it, in just a few years, this will be table stakes for operating. If you're playing in a competitive market, you'll be going up against people that have radically different cost structures, because they're making these decisions. I think it is going to be challenging.

Now, there are situations where obviously, the higher the level of complexity and the more nuance that there is, then it's going to be AI today is especially effective in these high-volume, repetitive scenarios. Say you're doing over-dimensional, heavy-haul, extreme ticket sizes, massive permitting complexities, a few moves, but need to make sure that you nail every single one of them, that's going to be – it's going to be quite a while before AI is better than you at navigating all of those.

If you're playing in like trident reef at flatbed, where people want to be working with logistics companies that obviously provide great service, but competitive on cost. If you don't have the cost structure to be able to compete on a pricing perspective, it's going to be very hard for you in two, three, five years, in my opinion.

Along with that, like you said, that some of those pieces, it can't, it wouldn't necessarily be the right thing, what would have to change? What would AI have to learn? Would there have to be a jump in technology? Or there just needs to be more and more data fed to it? Where's the ceiling now and what's holding us there? Is it the cost of chips and the resources that AI burns through? What is that at the end of the day?

Yeah, it's interesting, because the models now are extremely capable. Currently, the state of the art is that we have AI that is PhD level intelligence in a lot of difficult tasks. I think the best AI is the 75th best coder by the end of the year. AI will probably be better at computer programming and math than any human that exists, right? Pretty wild. Now, that is not the bar that is required to move freight, right?

There's a reason we were the red-headed stepchild of technology, because at the end of the day, if you put enough time, or if you call enough people, you can make it work.

Totally. The question is more about context, right? Because freight is really hot. The challenge of automating freight has been that there is a ton of tribal knowledge and nuance that goes into it. As you work in it, you just develop a lot of these like, oh, I know that this facility, you've got to call this person, and it’s going to take four hours to unload, so make sure you schedule it. This carrier never runs across the mountains, so I'm not going to give them that load. There's just all of this stuff.

If you think about what's required for AI to be able to perform these tasks effectively, you need ways for the AI to have awareness of that knowledge. A lot of the barrier is not necessarily raw intelligence, but it's constructing systems that allow –

It’s how do we download the 35-year experience logistics worker brain into the computer is what you're saying. Obviously, an extreme example, because I don't think anyone wants a plug in there. Yeah. We're talking about AI within logistics. It's very much from my side looks like a vast improvement, or at least a hyper jump in some of these aspects, where you needed, like you said, I like that 30 minutes became a three minutes. It's still a person doing it, just having all the answers right there. I guess, the only question is, does anyone have any reason why they shouldn't use it? It seems strange, and I might have already asked this in a different way, but I'm not hearing a situation outside of maybe right now, you were saying the heavy haul and hyper complex. Even then, pieces of that administrative work could be AI use. I don't see any facet, or industry that AI isn't going to take part in. From your perspective, is there a black hole, or AI shouldn't touch? I always ask this one, is there any point where, as you talked about the coders, I think, when does the – that one scares me, because at what point did the machines start talking to each other in a language we don't understand. Does anything ever get past the point of pulling the plug? Or is that all just sci-fi nonsense that made really great movies?

Yeah. I think there are real – it is a worthy conversation to be happening about where this goes. There is some version of AI that could be very powerful, and I think it's important to take those risks seriously. I think people are, in general, taking those risks seriously. When it comes back to adopting AI in one's daily life, or in their business, I think we're in this transitionary period where that question is being asked. I think in three to five years, it will just be a deep –

Yeah.

It's almost, we see this in some domains, like being a doctor, or being a lawyer. There's a lot of these questions of –

I think right there is a great call out right there. When someone's saying, hey, we should see if this AI software can do surgery with the lasers, the robotic lasers we already have. That's when someone should go like, “We need 20 years of research on something like that before you throw a person in there.”

Yeah. There's going to be some scenarios, like for example, medical diagnoses. I think within three to five years. Today, it might be seen as negligent to rely on AI too much. I think we'll actually shift and it will be negligent not to be using AI for something, because the results are just going to be much better when you have human plus machine.

I like that. It's a move from, oh man, you don't have enough people, so you're just throwing software at it to, we wouldn't have a person do it, because this software, or the AI is going to pick up on it that much quicker and more standardized of a response out. That is a great point, especially from a question where I ask negatively. Way to turn that one around. No. Jesse, this has been fantastic talking with you. It sounds like Vooma is in a great place, not only with its current customers, but with anyone that would reach out to you specifically, not only because it's basically giving you a team via AI that you can work under you and then you take all the credit for. But also, it could be as simple as staying in your inbox.

Now that I've summarized that and I didn't butcher the Vooma description, what's something you have to say to anyone listening, whether it's on AI, whether it's on Vooma, or whether it's on the logistics space use? Use whatever platform I have here, what's your message other than hello, mom, as I've gotten from someone?

Yeah. My perspective on this is AI is a means to an end. If you're thinking about use cases and workflows in your business that are causing you pain, or you feel like could be done more efficiently, have a conversation about whether or not AI could be one way to solve that problem to unlock it. I think as always, this is a tool, right? The thing that matters is like a problem to be solved, and does the tool solve the problem better than alternatives?

Keeping a very practical orientation around it, because I think it is easy to get caught up in the hype that everything needs to shift to agents, and that's not an all-out posture at all. It's very much like, hey, what are we trying to solve? How do we make sure that we deliver the value that we're expecting and move very thoughtfully through that? That's our ethos. Yeah, welcome anyone who wants to have a conversation about their workflow and what it looks like and where there might be opportunities to take that first step.

That was awesome and well said. Just quickly, where would someone go to find out more?

Yeah. You can hit me up on LinkedIn. I'm at Jesse Buckingham. vooma.com is our website. Feel free to reach out there. If you submit a demo request, you might even get a call from someone that maybe is or is not a human.

He's got all the AI to sound just as smooth as him, so you won't know if it's Jesse or not.

Yeah, exactly. No, we would love to have a conversation.

No. Jesse, thank you so much. Thank you for being here and giving us some of this information, because someone's got to be smart here and it sure isn't going to be me. I really appreciate your time. Thanks, everybody, for watching or listening to another Banyan Technology’s podcast of Tire Tracks here, as we focus on AI and logistics. Jesse Buckingham from Vooma, thank you so much.

Thanks, Patrick. Appreciate it.

Hey, have a great one.