The Robot Report Podcast
00:47:24 · Aaron Nathan
[00:47:24] S2: Yeah. I mean, so we are... You know, the investor pitch is point ones in everything that moves. And we're we're trying to really actually make that the case. So when we look at our markets, you know, there is the traditional things you mentioned like survey. What we do is so at scale that we've started to disrupt that market even. So we have some customers there. One of them is MLID, and we just announced, you know, those survey polls that you see. They just come directly with Point One from the factory. So it's like you don't really need to do anything. It's like a batteries included experience, highly disruptive to that market. The other markets we see are in, like, consumer. So you're starting to see these autonomous lawn mowers that you'll be able to buy in, like, Pumbico and Lowe's. They're gonna have our technology on them, and it's gonna be mowing your lawn, like, next year. It's kind of a a wild capability. In agriculture, you know, we have lots of different customers doing everything from, you know, planting seeds to taking weeds out. One of the ones I I really like is Burro. They've almost built, like, a platform that is a physical platform. And so their robot, you know, will move around and do all kinds of different tasks on the farm, follow people around, and, you know, they use us, obviously, to make sure that that robot is able to stay right in between, you know, the rows of crops or wherever it is it's advocating. Drones is a big one. We see that in two major use cases. One is really in the world of public safety, so companies like Skydio to use our drones. And then in delivery, you know, we have customers there, several delivery customers. You know? People, I'm sure, heard of, like, Zipline, and they're using us for that delivery function. And it's... I think the coolest thing about it is just how many different markets we end up seeing this. Construction and mining is another one that we have lots of customers in, and the number of use cases just keeps growing. Production on motive, we're even gonna be launching motorcycles next year. Just... It's it's... I mean, that notion of everything that moves is becoming true.
00:49:47 · Mike Oitzman, Aaron Nathan, Steve Crowe
[00:49:47] S1: I mean, I'm curious. You talked about disintermediating the surveying. Does it mean that you don't need to deploy a total station on-site anymore to to get the accuracy you need? [00:49:59] S2: I mean, the total stations specifically serve, like, the millimeter market, which, like, that's a little bit, you know, beyond where we wanna go. [00:50:08] S1: So there's still a use case for for total stations? [00:50:10] S2: Stations. Yes. But but Yeah. What's funny is, like, people will actually use our technology with the total station because the total station technically is a [00:50:18] S1: Okay. [00:50:18] S2: Gives you millimeters relative to wherever you put it, and then, like, you know, now you get millimeters to that point. Right. But how do you know, like, if that point is correct? So as another example, we have a customer, Civ Robot, and they literally have a robot that runs around, and it just, like, puts a stake in the ground where they're supposed to drive a pylon to put building. You know? So, like Mhmm. [00:50:39] S0: You [00:50:39] S2: really wanna make sure you get that right. And those are the kinds of things where, I guess, technically, that's like a survey stroke construction application, but it's it's also bringing robotics. And I think this is really... We're starting to see a convergence of these these technologies, and I think it's super exciting.
00:50:39 · Aaron Nathan, Mike Oitzman
[00:50:39] S2: really wanna make sure you get that right. And those are the kinds of things where, I guess, technically, that's like a survey stroke construction application, but it's it's also bringing robotics. And I think this is really... We're starting to see a convergence of these these technologies, and I think it's super exciting. [00:51:00] S1: Now a lot of teams get it... Can get a pilot working and... But, you know, when they get... Start to scale... And we were we were... You and I attended the RobotCon last week. And so very, very interesting to to talk about situations with scale. What are some of the things that that that, you know, sort of need to happen when you go from that initial pilot to a production with with Point One Nav or or other sorta location technologies?
00:51:31 · Aaron Nathan
[00:51:31] S2: Yeah. I mean, there's, I'd say, two categories of things when you get to percussion. There's, you know, the relationship with your vendors. Like, if we're working with a robotic mower company, let's say, and what's the relationship between us and that mower company? We've designed the product around having these tools that let you make kind of observability decisions at scale because it's one thing to have a portal you log into and you can see one robot's health. But how do you do it when you have, like, a 100,000 robots operating and then you wanted to see, like, is there an issue in the whole of France? So these are these are considerations that, like, we've actually already built into our platform and then exposed APIs that allow our customers to now bring that into their dashboards. Because the thing that comes with scale is all those weird problems that happen, you know, once in a blue moon, they happen a lot because you have just a lot of things in the field. And so the customer service organization actually gets a ton of value by working with us because they can directly integrate into our system and see what we see. And that results in just having, you know, quicker ticket resolution, better understanding of, you know, the overall, you know, what's happening. And that's just one example. The other example is, like, when you are selling that many robots, you actually have to start thinking about how do I provision these things? Like, how do I build them in a factory? How are they tested? And so, again, it goes back to, like, being very thoughtful about the kind of, like, life cycle of this building of a robot and making sure that we have the correct APIs to support all that. And you know when a robot arrives at your customer, they're gonna turn it on, and it's gonna work. And that takes a lot of forethought. It takes vendors that are going to work with you very well. I mean, it's, I could tell you, like, just as a personal experience, we work with a lot of the cellular companies, and it is extremely difficult to put a SIM card in something and then know that it's going to work when you ship it to a customer and they turn it on.
00:53:45 · Aaron Nathan, Eugene Demetri
And a lot of these systems in robotics almost work the same way because it's like the physical world has a lot of variables, and so you just really have to make sure that you're arming the customer with as much information as you possibly can. The other part of scale I did wanna mention is just geographic scale. And so being able to show up to markets and have things work. And we've obviously built, you know, a ton of infrastructure. It's one of our core pillars of the business. But, you know, we still have places that don't have coverage. If you're doing an open pit mine in Northern Canada, we may not have coverage there yet. So we've actually figured out how do we work with customers to have deployable coverage where they can actually bring, you know, their own technicians to go and actually install equipment to make the Point One service work there? And it becomes managed. It's like a really amazing experience for them. And we've actually now had some customers come back and say, hey. Like, this is this is game changing for our business because we can completely take the infrastructure problem off the table for them too. [00:54:55] S3: Talking about building the business side of things, Point One Nav, for instance, to get our expertise across GNSS, networking, autonomy, robotics. Most companies are are good at maybe one of them. How did all this come together?
00:55:09 · Aaron Nathan
[00:55:09] S2: Yeah. I mean, I think... So generally speaking, I think this is true of most robotics companies is robotics requires you to be good at a lot of things, because it is a physical problem. So you have to have, like, mechanical engineers who know how to build and assemble and, like, have things not rattle apart. You know? You have to have electrical engineers that know how to build circuit boards and all these kinds of things. And then you obviously need software engineers who know how to actually write the code that makes these things work. And software engineering spans everything from, you know, low level microcontroller firmware up to at scale cloud software. And then on top of all that, there's all the operations behind it, which is often forgotten about. And so we very early, were able to assemble a team that were expert in doing a lot of these different verticals and had also experience, like, kind of, like, cross functionally working with those different expertises, like, in their past, you know, lives. And so I think it's the team. It's, like, the short answer of that. And it's very powerful when you can have a small team of people that know how to do a lot of different things because we don't have as many, things fall through the cracks. And so it's built... It's this very tightly coupled, organization, and I think it's part of why we've been able to build so much without, you know, needing to raise a billion dollars or something crazy. Well...