“Every Burro turns on with 12 eyes … and if one robot makes a mistake in a train depot yard in Australia, or an airport in South America, or doing vegetation management alongside a road in Pennsylvania, the entire fleet learns from that lesson.”

For years, autonomous robots largely stayed indoors, confined to the predictable aisles of warehouses and factories. Leveraging his experience growing up working on a farm, Burro Co-Founder and CEO Charlie Andersen sought to develop rugged autonomous robots that work safely and effectively alongside people in the messy, ever-changing conditions of the great outdoors.

In this episode of Manufacturing Matters, TECH B2B Marketing’s Jimmy Carroll sits down with Andersen and Burro marketing coordinator Shelby Allen to explore how the company went from “three guys and a dog named Meg” working out of an unheated barn to a fleet of roughly 750 robots that haul, tow, mow, spray, and patrol across agricultural and industrial sites worldwide.

The conversation covers why building autonomy that works near people outdoors is far harder than automating big machines or indoor warehouses, and how “physical AI” adds a crucial third leg — training data — to the traditional hardware-and-software stack. Andersen explains how a larger fleet means more “eyes on the world,” compounding learning across every unit, and why the company’s surprising surge of industrial demand (now roughly a third of its fleet) prompted its first appearance at Automate 2026. Additional topics include the Burro Grande 44, the “Swiss cheese” model of safety, the role of large language models and voice commands on mobile robots, user privacy and data sovereignty, and why Andersen believes the U.S. has a major opportunity to lead as physical AI meets outdoor work.

Jimmy Carroll: [00:00:07] Hi everybody. My name is Jimmy Carroll. I’m the vice president of operations at Tech B2B Marketing. And welcome to this episode of the Manufacturing Matters podcast, where we discuss the trends and technologies reshaping the manufacturing industry and beyond today. So I’ve got the pleasure of being joined by Charlie Andersen and his colleague Shelby. Charlie is the co-founder and CEO of Burro. So I’d like to stop right now and ask you, Charlie, to kind of kick us off with an introduction to your background and a little bit about Burro and maybe what Shelby’s doing there.

Charlie Andersen: [00:00:35] Absolutely. Yeah. So sitting here with Shelby, who leads all of our marketing efforts, and again my name is Charlie Andersen. I grew up on a working fruit and vegetable farm, and my dad growing up had two businesses. One was our farm. One was a construction business, and I just grew up running machines. So think bulldozers, track loaders, tractors, skid loaders, etc. And literally from the time I could walk and talk what I really loved doing was sitting in an air-conditioned bulldozer cab pushing buttons. What I didn’t like doing was getting out of that cab to do something by hand. So fast forward a bit. I got an MBA and got out of business school and I went to go work for a company called Fiat Industrial, which became Case New Holland. And what I saw there was that we loved building larger machines for our best customers. And there was an underserved portion of the market where there wasn’t a lot of mechanization, and there was a lot of need for autonomy. And so 2017 I quit my day job, found a couple of co-founders, Vibhor and Terry. And since then we have literally gone from three guys and a dog named Meg working out of an unheated barn to today we’re a team of about 60 folks, and we’ve sold about 750 robots to date that drive about 110 days per day across the fleet. And just to describe what the product is, we build a robot called called Burro, which is literally Disney’s Wall-E or R2-D2 from “Star Wars,” for work outdoors in a version 1.0 format, which is a small vehicle that drives near people in the ag and industrial segments and does the five most basic, boring, ubiquitous tasks to being outdoors, which are hauling, towing, mowing, spraying, and patrolling or scouting. So that’s us in perhaps two paragraphs, not in two sentences as was originally requested.

Jimmy Carroll: [00:02:10] No, it’s a really good background, and it’s really inspiring. And when you mentioned robots from Disney and “Star Wars,” you were absolutely speaking my language. So I really appreciate that. So Burro, in your short time as a company, you’ve spent a lot of time looking at how autonomous mobile robots can perform in really harsh outdoor environments. And now you’re bringing this battle-tested physical AI. And that’s a term I want to circle back to later. It’s a really hot one in the industry right now, obviously, and it means a lot of different things to different people. But anyway, before we get into what that transition looks like, I wanted to go back to your start in agriculture and ask specifically what sort of problems did you set out to solve beyond kind of what you’ve already mentioned?

Charlie Andersen: [00:02:55] Yeah. So I think the biggest problem that we have been tackling as a company, it’s one part technical, one part user. It’s how do you solve people working in conditions that they don’t want to work in? The weird thing is that a lot of the jobs to be done in the great outdoors that already have machines doing them are actually the cushier jobs. Like everyone wants to sit in the cab of a big Case Magnum tractor or a Case backhoe and like push buttons and air conditioning. Nobody wants to get out and dig a ditch or move grapes around in 110-degree heat. Like no one wants to do that work. And building autonomy that can do that work that people do in the great outdoors is a lot harder than building autonomy that works on big machines. Because when you work near people, people tend to work under canopies, so you can’t always use GPS. And it’s a lot more difficult to build vehicles that travel safely near people where all the labor is than it is to build vehicles that don’t work near people. And so we started in some really, really niche-y areas of agriculture about nine years ago, literally hauling fruit around in fields. And then as we got better and better and more capable, we started doing a bunch of towing of things. And now today we’re about two-thirds ag, one-third industrials. And we have one system that can haul, tow, mow, spray, and patrol or scout safely near people across a ton of different operating environments, and anybody can run it. And that’s been a very “no silver bullet” kind of journey. A lot of lead ones, basically, to get it working.

Jimmy Carroll: [00:04:38] Yeah, that’s really interesting. I have a lot of different questions there based on that that I want to ask about. One is when are you going to be offering a household model? Sounds great. And another good point too that you mentioned, I’m glad you did, is that these are jobs that people don’t want to do. Not robots replacing people, which is not totally an idea that has gone away. But I think people are starting to realize that robots now are being used for these jobs that people no longer want to do, or they’re too dangerous or dull or just whatever. For whatever reason, they don’t want to do them. So like you said, it’s different, right? Like an industrial robot that has been programmed to pick and place or whatever or pick up car doors or whatever, it’s a different level of learning and programming and kind of understanding the conditions. And of course there’s safety fences in a lot of cases too, right? So what I’m getting at here is like farming environments are difficult. The terrain is uneven. It’s cold, it’s hot, it’s wet, it’s muddy. How did AI come into play when it came to building a robotic autonomy and what do these conditions teach you about building robotic autonomy?

Charlie Andersen: [00:06:02] Yeah. So I guess to tackle that relatively succinctly. I’ll do my best here. So most robotics companies have not been successful thus far, for a long period of time. The only success in autonomy thus far has mostly been in warehousing and factories. I think warehousing is about like 10% to 15% automated today, which is pretty small. If you think about — like 10% to 15% of warehouses have robots. That’s kind of nutty if you think about it. It should be a much higher percentage. And that’s one of the most penetrated segments. I think historically robots have been a fusion of hardware and software. So like something that is doing a repetitive task away from people that’s pretty simplified in a way. And new robotics, which has been coined I think with a very good term, in my opinion, which is “physical AI.” It has three legs of the stool, not just two. And those are hardware, software, and then training data or physical AI in some form. And the implications of that are that the bigger the fleet of robots you have, the more eyes on the world you see. The more you see, the smarter you become and therefore the more you can do.

Charlie Andersen: [00:07:10] And we as a company have reached a stage where with 750 robots turning on every day, I guess I typically say a spider has eight eyes, I think. I think the spiders, eight eyes. Maybe I’m wrong on that. Every Burro has 12 eyes. So every single day, every Burro turns on with 12 eyes. Each one processes six terabytes of data per hour per unit. And if one robot makes a mistake in a train depot yard in Australia somewhere, or in a airport in South America, or doing vegetation management alongside a road in Pennsylvania, the entire fleet learns from that lesson. And that’s really, really accelerating and compounding. And so I think what we effectively at Burro have learned is that if you start small and build a very data-acquisitive platform, you eventually reach a stage where you can build something that’s pretty generalizable, and that generalizability may start just around movement, but eventually it’s going to be movement plus all the other stuff that people don’t want to do outdoors. And then the final thing I’ll allude to, you mentioned before the notion of people not robots taking jobs, that whole realm and to get like a little bit weirdly personal in a way that might sound a little bit intense.

Charlie Andersen: [00:08:24] And I’m not intending it to sound intense, but my dad was probably one of the most successful I know personally. Had a farm, had a construction business, and he grew up spraying, spraying a lot of herbicide. He passed away at 66 because he was spraying a lot of stuff that got him very sick. And I think that today for me, we build robots that haul, tow, mow, spray, and patrol or scout, and there’s not a single one of those particular jobs that people grow up dreaming they want to do. Like no one wants to sit on a mower all day long and high heat mowing. No one wants to spray herbicide all day long, whether they’re in a vineyard or an airport. Nobody wants to be walking around in a depot yard at night, scanning for thieves or trying to count things. So we tend to do jobs that nobody wants to do and nobody really aspires to do. And I think we’re actually supercharging a workforce to do more and to do things that are fun, not boring and dangerous.

Jimmy Carroll: [00:09:23] Absolutely. Yeah. And I wouldn’t say intense. It’s incredibly poignant. And it makes your backstory that much more interesting and inspiring for me. And you know, I was going to ask you about idea of how the field data that you acquire globally can make these robots smarter. But instead you sort of already answered that, but I just think it’s interesting too, because AI is such a hot topic for a lot of people. And in some cases people are saying, well, you don’t really need AI here. You don’t really need AI there. What you’re describing here, you really need AI. And this is a real-world proven test case of like, here is how AI is making these things better, like by the minute. And I just think that’s great because a lot of times AI is the most hypothetical, and maybe we’re moving a little bit past that now as it settles into becoming more of a regularly used technology. But again, just a really cool example for me.

Charlie Andersen: [00:10:19] Yeah, and just to relate that to the AI stuff too, kind of industrial uses in specific, maybe to make it less abstract and more specific. I think when people talk about AI right now, they tend to think a lot of like large language models and Gemini and Claude and all of those great tools. And those are literally trained on the higher-level thinking of human beings, right? You know, reading, writing, like all of humanity’s knowledge that exists on the internet. And unfortunately, all of humanity’s knowledge that exists on the internet doesn’t include a lot of what a Siemens train depot yard looks like or what is a Weyerhaeuser Nursery or forestry nursery look like. That dataset doesn’t actually exist. And so the challenge for autonomy companies is how do you build something that can work today and create value and also become smarter over time to do more things? And I think that there’s a bunch of things. Let’s build a humanoid. And I think there are a lot of different ways that people are approaching it. The approach we have taken is build something that works and that creates value right now and ROI for users and also something that over time becomes the collaborative coworker of the 21st century. And I also think that alluding to science fiction, to me, the robot that is Wally or R2d2, that’s a cool thing. Like that’s going to be fun, right? And I also don’t think it’s one company. I think it’s a platform which is Burro and it’s an ecosystem of other companies building specific peripherals to count cars in a train depot in the yard or to count inventory and replace a yard jockey or to do multiple companies. And Burro is the layer for movement alongside people and a fully integrated stack that later will have an app store and a bunch of other functionality as well.

Jimmy Carroll: [00:12:00] Yeah. And you know, the one thing I want to ask about there in particular is, as you mentioned, the idea of it being a robot that can collaborate with people. And I know the term “collaborative robot” has been in a lot of discussions lately about whether or not robots are actually collaborative and what makes them collaborative, and obviously you don’t want to get in too deep on this, but I would be interested in knowing a little bit about those 12 eyes, the sensors that you have on board. So I’m assuming you’ve got like some time of flight, some laser range finder type things for working alongside people. But what other sensors do you have on there for not only navigation but for safety.

Charlie Andersen: [00:12:42] Yep. Yeah, totally. So each robot has 12 cameras. I guess actually let me describe this in more detail. We’re in process on some new kind of exciting things to come. So I think what I describe is going to be current state, not necessarily what’s ahead, but the current product has got 12 cameras, 3D lidar, big Nvidia GPU, big CPU, then bumper bars, emergency stops. What else? Speakers, a touchscreen RTK, GPS, at least 5 or 6 IMU. So things for your pitch, etc. as well as wheel encoders and a bunch of others. I think the average robot has about 25 or 26 sensors and processes, about 6 terabytes per hour per system.  What those are designed. And then we practice what we call — I think it’s what’s typically called the Swiss cheese model of safety, which sounds less authoritative than it probably should, as I’m saying it. But that’s the principle of many, many, many layers of Swiss cheese. Need to have a hole aligned to have any sort of thing that’s creating any risk whatsoever for a user. And so we go pretty slowly, like 1 meter per second, about 2 miles an hour, 2 to 3 on average. We have bumper bars on the front, which are for us like airbags on the front. In the back, we’ve got a 3D lidar that sees out about 40-plus meters around the vehicle. And then we’ve got six cameras on the front and six cameras on the rear.

Charlie Andersen: [00:14:10] And old robots or robots indoors can practice, can do some relatively basic things that once you go outdoors, you really can’t do. And I think what is unique about us is we can go indoors to outdoors and back or outdoors to indoors and back. And most robotics companies today that are really good at indoors can’t go outdoors and vice versa. And what changes if you’re indoors, if it’s short or nonexistent, you drive right over it. If it’s tall, you stop for it. You can rely on things like tape on the ground. You can use 2D lidar to know where you are. Once you’re outdoors, do you drive into a ditch? Well, it is free space, but you probably shouldn’t drive into it. Do you drive through reflective water? Was it deep? Is it shallow? And then how do you localize? Sometimes you see this guy and you have good GPS and other times you don’t. And those are very, very, very difficult questions to answer if you need to do it day in, day out in a really, really boring way. And we have reached a stage where we are really boring in the most positive sense because we have seen, I think at this point, more or less anything you could possibly imagine, although as we’re driving 110 days a day right now, we constantly uncover new random, crazy things.

Jimmy Carroll: [00:15:23] Well, that’s a good thing. And what’s really cool to me about that is, and anyone who has listened to the podcast before, I apologize because I say something similar to this so often, but it’s true. And it’s interesting to me personally is that like eight or 10 years ago or so, your product would either be not quite possible or just way less capable because of all these advancements in different technologies like lidar. I don’t think you could use lidar indoors or it was prohibitively expensive. X amount of years ago, 3D cameras were fairly expensive. GPUs are more affordable — well, I don’t know if they’re more affordable but more accessible than they were, more powerful than they were, which just kind of opened the doors to AI and the proliferation of 3D imaging. And it’s just a really cool example to see all these technologies in one robot doing things that really wasn’t possible not that long ago. So it’s cool.

Charlie Andersen: [00:16:15] I got my first digital camera I think in like 1995.  And I think that this space is very similar to a digital camera from 1995, right? Like you push the shutter and it’s like, Am I a pencil sharpener? Am I a microwave? Oh, I’m a camera. I need to take the picture. Like it’s slow, it’s laggy, it’s low resolution. And we are right on the precipice of this unbelievable journey where stuff goes from 320 x 240 pixels to 80 megapixels and instantaneous. And you can see every single thing in high fidelity and where that’s matriculating itself in mobile robots is robots are shifting from kind of dumb things, working in warehouses and factories only, to dynamic, flexible, AI-empowered data, acquisitive platforms that can go into the great outdoors and move, see everything, and eventually do manipulation-type things. And so I think today we are mostly movement. Today we move around, and then we look at some things and count them. And in the not-so-distant future, we move around, look at things, and count anything you want to possibly see and a code where you actually can talk to, and the ecosystem where someone wants to go count some exotic specific thing. They can jump in and install another application by giving a Burro a voice command to count that dynamic thing they’re after, and eventually you have something that is probably similar to a Disney Wall-E type thing, where it’s able to pick and place and move around in the great outdoors, which I just think is really exciting.

Charlie Andersen: [00:17:44] And finally, the voice with a large language model on a robot is just really, really cool. Like, Hey, bro, you stopped. Why’d you stop? Hey, go to bed. Hey, you were driving around last night. Did you see a car on-site? What was your license plate? You saw a couple faces. Who was on-site? You can start doing all these weird things once you have a mobile vehicle with a big GPU and a lot of cameras on it. And the final thing I’ll say as an American or as someone in the US, like, I don’t love the premise of having a lot of vehicles running around in US agricultural and industrial sites that are not somewhat, you know Western oriented with respect to privacy and data and where stuff goes. And I think that there are, in my opinion, for great brands that do work outdoors, which are Deere, Cat, Bobcat, and Toro, and those are all animal brands across construction, forestry, industrial, and so forth. And I think Burro is the autonomous animal brand for the 21st century that’s obsessed with user privacy. And how do you make AI empowering not scary?

Jimmy Carroll: [00:18:44] I love that. That’s a great that’s a great analogy. And yeah, I mean, I could totally see like at some point, like you’re talking about, like it’s feasible and maybe there’s not a particular use case for this with your customers, but you could see it, right? Like even using square cameras or hyperspectral cameras to do like precision weeding if you needed to. And it’s kind of like a lot of different things you could do. And it’s really, really cool.

Winn Hardin: [00:19:07] Everybody, I just want to take a quick second to thank our sponsor. Manufacturing Matters is sponsored by Tech B2B Marketing. They’re a full-service public relations and marketing agency that focuses on technology companies, especially in the energy and automation markets. They provide full-service media relations, investor relations, employee relations, full end-to-end content development, video services, animation, full IT stack development from website integrating with ERP systems, CRM, marketing automation systems. And they bring a whole lot of knowledge and experience about technical markets since they’ve been servicing those markets for over 30 years. So if you have any questions, you want to learn more, go to Techb2b.com. And now let’s get back to the show.

Jimmy Carroll: [00:19:48] Early on when you were first selling these robots, what are some of the applications that kind of helped push things forward and were there any surprises? I guess maybe you talked about getting into industrial. Is that a bit of a surprise or was it all part of the plan?

Charlie Andersen: [00:20:05] Yeah. Well, so early on, we started literally as the most single-purpose kind of dummy robot you could possibly imagine, which was a robot to haul around grapes and berries in a field. And the analogous thing I might point towards if you’re familiar with a Bobcat skid loader, you’ve ever seen that product,  they’re probably the one of the most ubiquitous, like outdoor ag, industrial forestry commercial products that really is used in construction a lot as well. That started out as a manure removal device for turkey barns. So it starts out super single purpose but over time establishes effectively a standardized platform that can do anything in the great outdoors. And for us, we started very single purpose in vineyards and berries. And what we discovered over time is that if you just do one thing and you’re indoors, in most cases when you’re indoors, the scene is the same and the job to be done exists year-round. Once you go outdoors, you’ve got winter, spring, summer, and fall. And so the seasons change. Oftentimes the job to be done changes. And if you only do one thing in the great outdoors, you can’t be big because you can’t be used year-round. And so in 2020, 2021, we were growing pretty quickly. But then we had a bunch of customers trying to take these little robots and do things like towing and mowing and spraying and scouting, and we weren’t quite big enough to do it. And so 2023 into 2024, we built a larger form factor robot, which we are now launching in an even more powerful format called Granite 44. And that is one robot that can haul ho mo spray patrol across all agricultural and industrial segments. And it really has evolved almost exclusively from people pushing us beyond our limits of what we could accomplish and thus then building the solution that they needed.

Jimmy Carroll: [00:22:06] And so I wanted to talk about this because a lot of this was leading up to me saying, I’m looking forward to seeing this robot at some point. You’re going to be at Automate for the first time this year. Is that right?

Charlie Andersen: [00:22:19] Yep, yep. It is for sure. Looking forward to it.

Jimmy Carroll: [00:22:22] Is there a chance that you’ll be taking part in the AMR demo area or is your robot too large for that or are you not sure yet?

Charlie Andersen: [00:22:31] I should know the answer to that. If we can, we will and would love to. I should know that off the top of my head, I can’t say I do. Do you know? Actually.

Shelby Allen: [00:22:39] I believe it’s something we’re exploring. It is close to our booth. And if we’re not there, you can just kind of walk, I think, like 10 or 20 feet and find us. That’s where our robot will be. But if we do have the opportunity to we will be.

Charlie Andersen: [00:22:51] Yeah.

Jimmy Carroll: [00:22:51] Well, either way, I mean, I’m looking forward to seeing it at some point. Hopefully it’s there. And if it’s not, like you’re saying, everyone can go and learn more about it, but that’s not what I wanted to ask about. Being at your first Automate, launching this here — what makes this feel like the right moment for you guys to make this sort of expansion?

Charlie Andersen: [00:23:10] Yeah, that’s a good question. So I think I can’t figure out how folks in the industrial segment are actually finding us, but it’s like a third of our demand right now. And then I think externally we look like a farming robotics company and we know it. And suddenly we have this platform that’s a third industrial. And so how does Siemens and CSX and Weyerhaeuser and Carvana and Koch Industries, how do those types of guys find us? And those are just a couple of many. We don’t quite understand it. And what we are being used increasingly to do is to replace small Cushman Tuggers and small Linda Tuggers and other vehicles that are towing things around. Pretty similar. We’re pretty similar from the size to baggage handling equipment or baggage handling tuggers you’d see on an airport. We’re roughly that size. And so we’ve got tons of industrial folks that are finding us to tow things indoors to outdoors and back and also that are using us to scan inventory in depot yards and car lots, as well as to do vegetation management. And we don’t know how folks are finding us. And therefore we’ve thought, let’s go to the biggest show in the world where everyone is to figure out why a third of our demand and a third of our fleet is solely in this space. And so it’s been a pretty big surprise to us, candidly, how much interest we’ve had. And then I think Shelby has got incredibly high EQ around marketplaces and so is helping leading the charge.

Shelby Allen: [00:24:40] Yeah. To add to that, I think like Charlie said, we have all these industrial contacts reaching out to us and saying, hey, we saw you on LinkedIn. We found your website. We think that your product could work in our operation. So from a marketing perspective, we’re then tasked with, okay, let’s look into this a little bit further. We’re actually in the wide range of industrial operations. Can Burro work? And as we’re trying to really grow into this industry and discover more and more that there are so many applications where our product can actually fit into industrial operations, let’s go and actually meet these people. Let’s go show them this amazing new product that we have coming, and let’s let them play around with it and kind of really make a big break into this industry by attending this major show, meeting with major players and starting to kind of tap into that market.

Charlie Andersen: [00:25:32] Yeah, yeah. Going to fish where the fish are, if you will.

Jimmy Carroll: [00:25:36] Yeah. Yeah. Well, and it’s kind of interesting too, Charlie, because you mentioned the idea of Bobcats previously being used for like manure removal. But then I think about the engineers and systems integrators and these the folks that are in the industrial space are very, very, very smart and very resourceful. Right? So you think of things like GPUs initially designed for gaming or the Microsoft Kinect, initially designed for gaming and being used for all these way out of the initial intended use.  And sort of almost like these technologies are not, well, not sort of like GPUs are, have certainly proliferated and 3D imaging, I would argue that that’s proliferated as well. And maybe this type of robot could be that next kind of thing. And it’s really cool.

Charlie Andersen: [00:26:26] Yeah, that’s one of my first jobs out of college. I was selling light bulbs. And the only reason I raised that is I think when people see a light bulb, they associate the image of a light bulb with an idea. And what was really cool at the point in time where I was selling light bulbs, we’re selling LEDs, and you’re taking this object that people have a vision of it in their head for the past 120 years and reimagining it in a new way. And I think what’s cool about a robot is when you say robot, the definition of what a robot is is so wide. Like is it the robotic arm? Is it a Roomba? Is it a humanoid? And I think what we are creating as Burro today is the form factor that becomes Disney’s Wall-E, which is an under 2,000-pound vehicle that drives safely near people, that does basic, boring, ubiquitous things, and that eventually becomes an ecosystem for automating all of the work done in the great outdoors people no longer want to do. And I think that in the industrial space, from what we’ve seen, there’s a heck of a lot of move around, look at something, pick it up, put it down, and what have you. And that ecosystem is what we are building today. Armed with 110 days of drive. We think we’ve driven 120 years to date with a vehicle that processes a ton of data in every hour, and that is just making us really smart and capable as a fleet, maybe not as people but as a fleet going into industrials in a big way.

Jimmy Carroll: [00:27:51] Yeah. And it’s like I hear more things like this, and you start to throw numbers out and it makes me realize, like, we went to a Schneider Electric event last year, it’s their innovation forum or innovation summit or something along those lines. And there were so many sessions on the importance of data centers down to the point where people are talking about innovations that have been made in cooling data centers. And obviously these data centers are at the heart of AI growth, right? They’re very important. And that’s a whole other conversation. But anyway, it is really interesting to see, and you see the growing importance of these data centers and the people that create and maintain and troubleshoot them as needed.

Charlie Andersen: [00:28:35] One thing you might be hitting on there is just some macro trends or like some things that are actually driving maybe adoption and/or headwinds on these things. So like data centers. I think the AI boom is very real. You also have — diesel is pretty expensive right now. Labor is pretty expensive. All these things are getting more expensive as well. And I think that what we can all see is that in 10 or 15 years, there’s going to be autonomy pretty much everywhere. There’s going to be a lot more things that are probably electric as opposed to fossil fuel powered. Labor, I think, is going to continue to get scarcer and more expensive, especially in hard-to-do jobs. And if your workforce doesn’t evolve as things get more capable, then you’re going to get wiped out as competition comes in that is more AI enabled and moves faster and does things at lower cost. And I think that for leaders of big companies and entities, how do you adopt automation or how do you adopt things that can get you ahead of that curve or with that curve pushing you in a positive direction? Not the other way, which is how we kind of think about it as Burro.

Jimmy Carroll: [00:29:44] Yeah, 100%. Like it’s at the point where pretty much across every industry. And of course, automation in the form of physical hardware robotics is not necessarily required in every industry, like in marketing, for example. But AI is, and all these companies that aren’t adopting these technologies will eventually get left behind.

Charlie Andersen: [00:30:14] Yep. Yeah, that’s certainly my opinion right now. I think that again, speaking a little bit as an American, not to get patriotic, but we as America, like we have a great opportunity today. And it’s also a threat. Like we need to modernize and kind of supercharge what we’re doing in this country. I think when I’ve been in Asia recently, other parts of the world, like some other parts of the world are looking more modern than us. And I think that automation — and actually I think about like something like an Apple iPhone, right? iphones are, I believe, 40% share of global smartphone revenue, but they are like 90% share of global smartphone gross margin. And that is an American company defining the category that becomes the smartphone that we all use and then embracing user privacy and everything else to deliver a great unified experience that everybody adopts. And I think that there’s an opportunity to do that as physical AI meets work in the great outdoors. And as AI just generally does, and we as Americans need to jump on it. And I’m not sure how much of your audience is American versus global. We as Western countries need to in my opinion.

Jimmy Carroll: [00:31:22] Yeah, for sure. I mean, we recently interviewed Congresswoman Jennifer McClellan, who is part of a bipartisan task force to introduce a robotics bill to help us remain globally competitive. It’s difficult with China, right? With their companies being government funded. And the other idea too is that that she left. She had a lot of good insights, but one of the thoughts was like, it’s great if we win the race, but then if we don’t also innovate on the back end of things like data centers and we don’t have food or water, what good is that? So there’s a lot of work to be done across the board. But she was all very excited, obviously, and optimistic about the increased adoption of automation and what it could do for our economy and reshoring and things like that. So yeah, there’s a lot there.

Charlie Andersen: [00:32:09] There’s tons of opportunity around it. So my great, I think great-great-grandfather ran a horseshoe nail company in the 1920s and kind of went insane because cars came out and things became pretty obsolete pretty quickly. I think we have the total opposite scenario here where you’ve got this rising tide that is going to lift a lot of boats and make and breathe  opportunity into a lot of industries. I think with physical AI in particular, any work that someone does in the great outdoors, that requires moving, looking at things, and doing some sort of manipulation that can be automated, and likely a lot of it will over the next five to 10 years. And I just think that’s a huge opportunity for many, many, many companies.

Jimmy Carroll: [00:32:50] Yeah. Dr. Andrew Ng said AI is the new electricity. So at first you’re not sure how are you going to use these things? But eventually you will. Anyway, I’m curious, I want to ask you, what are those conversations like when. So if you’re typically used to talking to folks that are more on the outdoors. Well, I guess some of these industrial companies are also outdoor, but more along the lines of like mowing and spraying, like you’re talking about. Those conversations look a lot different than companies that are more in the warehouse or dealing with, like you said earlier, like AGV and AMRs that use magnetic tape and reflectors and fiducial markers and whatnot. Like how do those conversations differ between the industrial customers and your traditional customers?

Charlie Andersen: [00:33:39] So let me start first with how they’re common. And then I can kind of bridge to maybe how they’re different. So I think what I’ve seen that’s very common for one, I find that there literally always like three tiers of people or three groups of people that you have to appeal to. First you’ve got people that are actually using things in ag and a lot of the industrial space. If you don’t speak Spanish, you can’t talk with any of the actual end users of product. So we have a Spanish-speaking customer success team. And I will talk with someone and be like, “Hey how’d you like it?” They’ll be like, “It’s good.” And then our field team will have like a two-hour-long conversation and be playing fantasy football together. You know around like — why the button’s the wrong shade of red. So you got to appeal to that group. The people that actually use the product need to love it. The second group I found is like the middle management team. The people that are actually setting up the operational flow, the folks who are the first people to get called when something is broken or down or not working. If it’s hard for those guys to set up, it doesn’t work. I don’t care where you are. If it’s hard for those guys, it’s just dead.

Charlie Andersen: [00:34:47] And then the final group is the kind of scenery. I don’t want to use the term muckety-mucks, but you kind of get like the people with C in the title. Who are CO, CFO, CEO, who may have a vision for physical AI and ROI and return but sometime may not be fully in the details. I’m saying this hopefully with enough self-awareness. I have this title also myself of you know it needs to work, it needs to have a payback. It needs to be in keeping with the overall vision of the company. We have found that in agricultural settings, we sell to big corporates — think like Driscoll’s wonderful. Any palm or Fuji water like that company. We sell to Costa Farms, Altman plants, these are $2 billion to $3 billion nurseries. So huge, huge, huge operations. Those types of sites have those three C-suite middle managers and users, and you got to appeal to all three to get stuff working. And we found in the industrial segment, it’s pretty similar. And what’s unique to us is we actually tend to enter industrial stuff. And again, think car lots, train depot yards, indoor/outdoor manufacturing, warehouse-type settings. We tend to enter those spaces today through the line guys, through the people that are actually on the ground. Those are the people that are finding us the most. We’re not talking with middle managers as much, and we’re not talking with CFOs, CEOs today a whole lot.

Charlie Andersen: [00:36:14] I think that that arguably is a really good sign. That means that people on the ground are saying, hey, I got robots that work indoors. I don’t have something that works indoors to outdoors and back. And I’ve got people doing these jobs they don’t really want to do or they don’t want to do. And why can’t we bring in automation like this? Because it exists in other sectors and we can pull it in. So that’s what I would say is common. I think what’s maybe different is in industrials from a product perspective, there are a couple of subtle things that people want. So if you look at like Deere’s product line, the industrial stuff is always yellow. So you can see it. Like it’s literally you go from green or blue to yellow. So it’s really, really visible. And then it tends to be slightly customized to be more functional in an industrial setting. And so we have an industrial version of our product line right now that is specifically customized to be safe near people, visible if you’re backing up a forklift,  and is set up for those specific uses. You know, just to give you some examples, I would say it’s probably 90% common, 10% different, not like the Venn diagram of crossover is actually quite significant.

Jimmy Carroll: [00:37:30] Well, interesting. I mean, obviously it makes the expansion in this space a little more natural for you then, so that’s good. Well, one thing I asked about early on was, and obviously we’ve both said the term a number of times since then, but physical AI. So it’s a term that some people don’t like because they think it’s misleading, but there’s been a lot of these terms over the years, right? Like embedded vision or whatever — that one comes to mind — but what does it mean to you? Like to me it means, well, I’ll stop there. How do you describe physical AI?

Charlie Andersen: [00:38:05] Yeah. Well actually, the first thing I’ll say, I don’t think the robotics community has been very good at marketing and branding historically. I think there are all these funny terms. Like I think a lot of robotics companies use the term “deployment,” like you deploy the military to Iraq. It’s heavy, it’s bureaucratic. Or you have a robotics team and they talk about humans as opposed to people. There’s just a lot of awkward jargon that I think hasn’t yet met its moment and is about to in a big way. Like I think we can build some great American brands right now that ship stuff globally and get it and get that like robots. Robots should be fun, easy-to-use companions and all that good stuff. When I hear the term “physical AI,” I really think at its most elemental form it means you can take a cheap camera and recognize anything. And to do that, you got to see a lot of it. And so the implications of that are enormous because it means that if you have a big workforce doing a lot of work outdoors, and if you can get robots to start working near them, those robots working near them can maybe start out with something basic, ubiquitous, and boring and quickly do more and more things that people no longer want to do. And so I think that’s the implication of it. And what we’re doing is we’re unshackling robots from the confines of not being able to work outside of a cage box in a warehouse or manufacturing element and letting them go safely in a highly data acquisitive way into the great outdoors.

Charlie Andersen: [00:39:33] And then finally from a — you may actually you have alluded to this earlier in your question about industrials, maybe the final thing is, I think in a lot of the industrial stuff, there’s a big element of security and privacy, which I think is really, really wise and vibrant and the right thing to ask things like soc2 and, you know where is data going? And I think we are going to confront is as, as cameras on mobile robots go from one megapixel to 2 to 3 to 5 to 50 and go from black and white to color. What you’re going to have are vehicles driving in these settings that can recognize things better than you as a human being can do and are able to pipe back novelty somewhere centrally to do more things. And if you’re a operator in these spaces, you want robots on your site now to enable that future, and you want to get ahead of it. You don’t want to be the laggard later down the road when all of your competition has it welcome in some form, in my opinion. Again, as a robot salesman, admittedly. So I don’t mean to be pushing what we do.

Jimmy Carroll: [00:40:40] That’s really good. I mean, there’s probably a million other questions I’d like to ask, but I’d like to be respectful of your time. Is there anything we haven’t talked about — whether it’s what you’re excited about for Automate or where you see this technology going in the next couple of years or anything like this that we haven’t talked about that you want to mention?

Charlie Andersen: [00:40:59] Yeah. The only thing I want to mention, so at Automate, we have this new robot we have have called Grande 44. And I’ve been doing robots for 10 years at this point. And when I say doing robots, I mean like in the field with people running, like living and breathing the product. And this thing is like just a phenomenal piece of gear. It’s a 44 horsepower vehicle, weighs about 1,500 pounds. The coworker of the 21st century, it is styled a little bit to look like Sid the sloth from “Ice Age,” admittedly. So we’re not taking ourselves too seriously. Hopefully that’s clear. But it just is a really, really, really good piece of gear. If you want to replace a small vehicle that is driving around doing boring work in an indoor/outdoor industrial slash setting. So we’re just really excited to talk about that. And then if you want to learn more about us, we’re burro.ai.  And we’d love to share more for sure. And looking forward to being there. Really, really excited about it.

Jimmy Carroll: [00:41:53] Awesome. Well, I’m looking forward to learning more about it and hopefully seeing it, but at some point I’m sure I’ll find a way to see it. If anybody has any questions for Charlie or Shelby or the Burro team in general, feel free to reach out to us at manufacturing-matters.com. We’d be happy to pass those along. Or if you have general comments or questions for us or want to be on the show, please reach out and let us know. And other than that, Charlie and Shelby, thank you so much for the time. It’s been a great pleasure and I really appreciate it.

Shelby Allen: [00:42:22] Thank you.

Charlie Andersen: [00:42:23] Yeah. Thank you Jimmy. Really appreciate it as well.