Conference Transcript - EXYN 2026-06-23

Operator

Good day and welcome to the iAccess Alpha Virtua Best Ideas Summer Investment Conference 2026. Our next presenting company is XM Technologies, Inc. If you would like to ask a question during the webcast, you may do so at any point during the presentation by clicking the Ask Question button on the left side of your screen. Type your question into the box and click Send. I'd now like to turn the floor over to today's host, Ben Williams, COO at Exxon Technologies. Please go ahead.

Ben Williams, COO

Thanks so much. Good to meet everybody. My name is Ben Williams. I'm the Chief Operating Officer of Exxon Technologies. A little bit about the company. We'll go through the background, the technology, and the categories we operate, obviously. So a little bit about us. We are a company that sits at the intersection of high-accuracy rapid mapping and autonomous navigation, specifically what we would call self-contained autonomy. That is, no GPS required, no communications required, no prior mapper model or external computer fiducials. So truly self-contained autonomous systems at the edge without all the infrastructure needed to operate. So we got our start in the physical industrial world. You can see great examples of this on the left-hand side of this slide, places where physical industries are trying to digitize, trying to gather information about their operating environments, but in many cases are still out there with handheld devices, watching, looking, getting on vehicles out in the field. So these are really difficult, dangerous, dirty environments, highly repetitive tasks that are very costly, obviously great opportunities for autonomous systems to get involved. we actually got our specific start within the underground mining world you can see here some an example of an underground mine that had been shut down for many years the owners were trying to reopen the mine re recommence operations but they didn't know the state of the underground mine so they what they had to do was take one of our systems you can see in the upper right hand side where it says operator launch pad this is where we initiated the mission they're up they started from outdoors and below tree canopy, and then basically created a whole mission profile of search the mine, create a high accuracy model. But because they didn't know the state, they could not do low level mission planning. All they could do was the high level mission objective of explore and create a model. And so the system self-defined its own flight paths, created its own sub objectives, and then commenced the mission. You can see the actual, the white thread here is the flight task the system took throughout the flight. And at the end of about a 10-minute flight, a single mission, the system came back with a survey-grade three-dimensional model of this underground mine. Now, if you're doing the math on this, this is a 10-minute flight, maybe 30 to 40 minutes of setup and teardown. And so a couple hours, you've got a high-accuracy 3D model where if they had tried to do this on foot, it would have taken probably days or weeks in order to get safety clearances, put people underground with tripod scanners and scanning this entire environment, and it would have been very unsafe. So obviously a great benefit to the operators and a much more accurate model than you get through other systems. So a little bit about this. When I talk about autonomy, there's two main distinctions that I'll create here. So one is between automation versus autonomy. And then within the context of autonomy, there are a whole bunch of different elements as well. So when you think about an automated system, this is something that is human defined and machine operated. It requires high consistency, low variability in the environment. If anything changes, the system breaks, or you have to have a human reset or remake the model. An autonomous system, on the other hand, is resilient to these types of changes. Given a high-level mission objective, it will find its own way to try and accomplish that mission in order to work around changes in the environment. Obviously, in most of the real world, environment control is really difficult, and so autonomous systems become a really critical hallmark of operating environments within the context of autonomy we've used the the se models for self-driving cars to create the the aerial autonomy versions we did this this paper in coordination with ieee spectrum as well as a bunch of university partners trying to validate the structure but within this level 4b is where we operate the some of the critical hallmarks here is that the operator is not flying the system. You're also not doing low-level mission planning. You're not defining specific waypoints or flight paths or any of the sub-objectives. You're simply defining the high-level mission objective, and the system is decomposing those as it goes, determining best flight paths, best flight speeds, safe navigation corridors, et cetera. And within the context of the Ford B specifically, the B refers to a level of environmental classification where it learns and understands things about the environment and then takes action based on those understandings. A great example here is in a lot of constrained environments, a drone system is likely to kick up a cloud of dust. These dust clouds to a raw sensor stream will appear as though it's an object or an immovable or non-navigable wall. And so in order to operate successfully here, we have a filtration and classification algorithm that allows us to classify what would otherwise appear to be non-navigable as a cloud of dust. It navigates through it, although slowly, and can still detect millimeter-thin wires within that cloud of dust to navigate around. So a really critical element in how systems operate successfully in some of the harshest environments around. So a little bit about how we have gone to market. Our intelligence and all of our intellectual property lies in the software side. The suite is called XNAI. Within this world, we've developed a ton of different software elements that combined equal this sort of software suite. But because we operate out in the physical world, there's always going to be hardware involved somehow. And so the way that we've managed this is what you see on the left-hand side here, the XNN Nexus. This is a modular payload that provides autonomous navigation as well as 3D mapping. And this is the system that we then put onto third-party drones and ground robots in order to provide both the mapping and the autonomous navigation. You can see a bunch of the systems here that are commercially available worldwide. We've integrated on over a dozen airframes and are continuously adding more to the portfolio. And the idea basically is that we want customers to be able to buy whatever drones they like, put our autonomy payload on it, and enable those systems to be truly useful for them so in the context of our market dynamics i talked about mining being our first category it is still our largest market our second largest market is the geospatial data world this is our fastest growing market to date and we expect this to overtake mining this year as our largest category by revenue the huge opportunity we're barely scratching the surface but these are some of the addressable markets you can see here all of them on their own fascinating markets and you know we're we're really well positioned to take on a bunch a big category in each one of these so in terms of how we've developed product to meet these challenges on the very beginning we had a very targeted use case very highly integrated system that was focused on one or two very specific use cases in underground mining. That was the X and arrow. As we expanded the flexibility, the modularity, and the maturity of the system, we started to add different use cases and different capabilities. This led to us improving the modularity at point where we can build the nexus, which is the payload I talked about earlier. After we had the payload, then we started adding more and more and more integrations. You can see examples of these, but we've started doing a really flexible open model that allows people to integrate into all kinds of things. This has then led to the most recent shift for us, which has been to add an OEM category where we allow OEMs to build product on top of our core foundational tools. And so the two mechanisms here are either through the nexus and then adding an API structure to allow people to build on top of it, or to license the SDK or software development kit either as some of the parts some of the modules or in its totality and in those cases we don't have to see the hardware at all it is purely a software transaction and so both of those are the means by which we are tackling our third major market which is the oem world which leads me to our fourth category of the four so mining geospatial oem and government and defense On the government side, you can imagine that a GPS-denied and comms-denied system already has a huge advantage in contested environments because we don't have to develop specialized technology to operate in areas where GPS spoofing or jamming is omnipresent and communications jamming is very regular. We can operate comms-dark and GPS-denied from day one. We also are able to operate in a lot of different weather environments, darkness, dust, smoke, et cetera. These are areas that we are regularly operating in anyway. And so given the outgrowth there into a bunch of defense use cases, including intelligence, surveillance, and reconnaissance, tactical mapping, real-time digital twins, maintenance availability improvement, a bunch of use cases that the government has targeted as their areas of investment over the next few years. and part of why we have this advantage and why we've been so successful in these four categories is because of the depth of real world experience this is not a lab technology that has recently been spun out without any you know practical practical testing this is a fielded capability that has been out in the real world in some of the harshest environments operating autonomously for over six years our external users perform well over a thousand autonomous flights every single month. And trust me, they put it through the paces. We've developed all kinds of ways to deal with edge cases and microclimates and interesting things that you would never think of operating in the lab environment. But in order to make it work in the real world, it becomes a really critical piece of the capability set. So because we are already a product market fit for a couple of our core markets, this is not a technology development play for us. We're at the stage where this is market growth capital, a lot of focus on sales and marketing and growing the team, as well as doing some R&D development things at the forefront of capital buys into recurring revenue as a critical piece of this transformation as well. You can see some really great examples of customers that we have across some of our core markets, mining, construction, geospatial, a lot of big names here. You can imagine these are not folks that make buying decisions lately we've had to prove dependability of our systems and some of the harshest worlds and some of the most exacting customers because we are part of their critical path it took time to convince them that we were dependable viable and able to give them the right answer all the time and this is how we've now become what we believe is a market standard for data collection by autonomous systems so a little bit about our expansion mechanisms here. I talked about mining and geospatial as growth markets. Beyond that, through our channel partnerships worldwide, we're operating in over 30 countries. We've had systems operating on all seven continents, especially AEC and geospatial. These are major growth categories driven by channel expansion. And on the government side, we have, and the OEM side as well, we have a bunch of new partners and we're beginning market entry in earnest as of starting end of last year and growing quite a bit this year as well. So behind all of this, obviously, we've got a great team. My name is Ben. I'm right here. Brandon Torres-Beclete is also on the call here. Our CFO and CTO are both world-class and up and down the chain. The rest of the team is supremely capable. We've got some of the best minds in the world working on autonomous robotics. a little bit about the financial side we saw a from 23 to 24 we saw about a 20 percent year-on-year growth and from 24 to 25 we saw a similar growth in terms of orders we got a bunch of those orders towards the end of the year and there was a shift in in some of the nature of those orders to emphasize more recurring revenue and software oriented models as a result of that a lot of that revenue didn't get recognized right in 2025, but we had a backlog of over a million dollars going into the year 2026. And so that's a pretty strong position for us to be in, I think. And you'll see us continuing to focus on shifting some of the revenue types to more recurring revenue models, as well as higher margin software and partnership models. And then as something to sort of leave you all with a couple key points to make here we've got a technology mode in the form of our level 4b autonomous navigation and that is both in terms of the core technologies but just as important is the infrastructure that binds them together uh what what you might call the the tubing or the piping that connects it all and the ways in which we've optimized to emphasize survivability and dependability in some of these harsh environments um oh sorry These are mission critical systems for some of the harshest industries. We're part of their primary workflows. So if we go down, they go down. As a result, it took time for us to convince them, but they've been convinced they come to us first when there's an opportunity to do new use cases or to rebuy or re-up or expand the usage. We're proven at scale. There's well over 1,000 autonomous missions performed every month by our external users. This is a dual product business in the sense that there's the Nexus-led systems and the API and SDK-oriented OEM integrations, which means that we have quite a broad spectrum of ways to serve the customer. We've got a huge opportunity here. We're at the intersection of autonomy, digital twins, LIDAR, and robotics. Any one of those would be an interesting opportunity. The four combined is really huge. And as I mentioned, we've got a great leadership team, and we're happy to answer any questions you all have.

Natalia, Analyst — Moderator

Thanks, Ben. Appreciate it. Our first question is, how would you describe Xen's core technology and the difference between automation and true autonomy in GPS-denied environments?