Ouster, Inc. (OUST) August 2026 Conference Transcript

Hi, everyone. This is Colin Rush. I lead the industrial innovation research practice here at Oppenheimer. We're thrilled to have the Auster team with us today, Ken Gianella, the CFO, and Chen Gang, the SVP of strategic finance and treasurer at Auster, long-term veteran of the company. And we may have Angus be able to join us here as well as CEO. But to get started, guys, can we talk about, you know, the fact that you've got 14 consecutive quarters of revenue growth and you're sitting at a $55 million, you know, plus or minus run rate. You know, as you bring Rev. 8 into the mix, how are you thinking about the impact to revenue and that product transition from Rev. 7 to Rev. 8 and how that's going to, you know, start translating through the P&L?

No, thank you, Colin, and thanks again for hosting us at the event today. It's been a great day. Q2 was really our first full quarter as a unified platform with the launch of Rev8, and we also announced the launch of Stereolabs Nano. It's a camera specifically for the robotics industry. Really pleased with how the quarter performed. When you look at ex-royalties, product-wise, we outperformed in Q2 than we initially anticipated. And our product revenue, quarter over quarter for Q3, will be sequentially higher in Q3. Rev8 has been very, very electric, the reception that it's gotten, multimillion-dollar orders already booked, some from new, some from existing customers, a lot of brand-new use cases that it opens up. So the bookings, we've been really pleased with that. And Rev8 is still in the early stages of its volume production ramps. So we said on the call that we're looking for that to ramp, really getting to scale in the September timeframe as we go through Q3 and then carrying that on to Q4 into the out years. We expect Rev8 to become the core of our sensing platform for the business over the next several years. But as product transitions go, this one's probably the longest tail that the company's had in its history. Rev7 was a real workhorse for us. It's built into a lot of existing company production platforms already, so we expect that one to have a long tail and be part of our product suite for a while to come. The key for us looking ahead, though, it's really about continuing to grow the full product suite, continuing to grow the platform, Rev8 being a big part of that. But what you're going to start seeing as that growth and potential inflection is that platform play of bringing in compute in the software for the individual applications over the next few years.

And, you know, it raises a good point around, you know, the early stages of growth that you guys are in and the individual verticals that are seeing real adoption. So, you know, the industrial vertical was the biggest contributor this last quarter was more infrastructure. How should we think about the durability, repeatability, and kind of, you know, mix shift from vertical to vertical as we go forward, you know, and thinking about repeat orders, you know, and, you know, the consistency of margins as you see, you know, slightly different dynamics in each of those verticals?

Right. Well, I think the one thing we've always talked about is the adoption and cadence, you know, is very similar across almost every vertical. You start with a prototype, you move to pilot, you lock into design, win, then you scale to production. And then once you land and you win that production, you're really expanding and building new use cases at a customer. And so we have several customers that we've been able to demonstrate that with even within the early days. I think the largest thing for us, just focusing on smart infrastructure for a second, is having that end-to-end play. Being able to be no-code, turnkey solution, think easy button for these customers is what we're seeing start to emerge, especially within the Department of Transit areas. For the industrial side, though, it's really about how can you get product to market that's durable and repeatable for the customer in a high quality. And the ruggedness that you need within these environments, especially in the outdoor environments, that's what really sets our store apart from the competitors. So, you know, I'm not going to make you pick, you know, which one we love the best.

But if you think about these deployment schedules, you really got to love the industrial side, because once they get into that logistical production mode, it really takes off and it smooths out a lot of the lumpiness. so you signed in you know multiple multi-million dollar orders right and and so i think um i would love to understand the significance of that um you know certainly um you know we've seen you know a lot of demonstration of the technology integrated into you know large capital equipment um you know top av providers as well as some of the the dot um you know applications but you know the the The history of LiDAR, you know, in some cases has been around sampling and smaller order sizes and prototypes moving into these larger awards signal something different. I just want to understand that from your perspective and what that means for maturity of the physical AI space and where you sit in that ecosystem.

Well, where we sit in the ecosystem has significantly changed with the acquisition of Stereo Labs and bringing the compute piece to it. So we've moved from a single point provider to expanding to a platform player within physical AI for sensing and perception. So being able to come to these companies and provide them not only just a point LIDAR solution, but be able to offer the compute, the software, and a camera, we're already seeing early indications of that really driving us, Colin. As you start looking forward with this, the LiDAR business is really going to be a big driver of their technology needs because the Rev8 brings such a unique component to it that people are starting to build into their platforms. And where before you had a LiDAR that was great and had the right resolution, bringing revolutionary, speaking of the perfect timing for you, Angus, speaking of the revolutionary Rev8 and the RGB that brings to the table, we're seeing these industrial customers, Colin, want to sign on now because they want to build that as part of their core platform to get that fusion right on the chip. Anything you want to add about the Rev8 launch, Angus, and how that does for industrial?

Angus, before you get started, let me refine the question a little bit. We were just talking about the significance of the larger orders that you guys are receiving. And as you get into answering the significance of that for the physical AI ecosystem here, I just want to understand a little bit more about why that's so important for folks, right, from a product differentiation and what that enables from a system level. if you could address both of those.

Yeah, absolutely. I mean, so it's important context to remember that we've been shipping a highly competitive Rev7 product line for the last three years. You know, we are largely regarded as having some of the best LiDAR sensors, if not in many cases for different use cases, the best LiDAR sensors on the market with Rev7 for the past three years. That's why we've built such a suite of high-end customers for our history. And so Rev8 is taking something that's, you know, already really a leadership position and making it, I would say, obvious that there's no other choice by bringing even more performance capability and now RGB into the mix. And so, you know, if you've ever done sales, and I do a lot of sales and talking to customers, there's a big difference between a competitive sale and an obvious sale. When customers are just asking and they're not even debating or comparing against a competitor. You know, Rev 7, you compare against a competitor, you think about it, you choose the Rev 7 because it has superior specs. Rev 8, it has native color. It's functionally safe. We have long-range, hyper-capable OS1 Max versions. It's an obvious choice that doesn't have a comparison at all in the market, and that makes the sale even that much faster, that much easier for us, and that much more confident on the customer to actually just place that order up front. So we've seen a series of long-term Rev7 customers immediately turn around. You know, they have confidence in ouster. They see Rev8, and they've signed on board with a major, you know, multi-million dollar orders. And just this morning, the Utah DOT is such a great example of this. Turned around 160 intersections with OS1 Max Rev8 sensors on them. This is a brand new product, you know, brand new hardware, brand new software. and it's not normal for traffic engineers to deploy this kind of technology at scale when it's this new but they have the confidence because it's built on the ouster brand the rev 7 reputation and it's got such obvious benefits with this native color and long-range capability and that's just one example of a use case with what i would call a conservative kind of kind of customer, not a customer that wants to take any chances on quality and capability, reliability, and yet they have the confidence in Ouster. So that's playing out across all of our industrial customers, all our smart infrastructure customers. They're seeing Rev8. They know it's got the capability and the quality that Ouster has become known for, and then they see native color performance, and it just becomes an obvious decision to adopt.

So I'd love to just follow up on that RGB discussion. Why is that so hard? And how long has it been in the works for you guys? You know, I think that's something that takes some explaining for folks in order to the story, but it's a very, very big deal. And it's very, very hard from what we understand. So we'd love to get your perspective on, you know, why it's so hard, what's involved, and what that enables for you from a leadership and ML perspective.

Yeah, for sure. And first, I mean, And the concept or the definition, what is this native color technology in the first place? So native color LIDAR is LIDAR data that has RGB or color information at every point. And the reality is you cannot, you and I don't perceive the world in just 3D. We also don't perceive the world in just color, 2D, you know, camera-like imagery. we actually combine depth sensing and color to describe the state of the physical world. You need both channels. And that's why historically, if you're a Rev 7 customer of Ouster, almost assuredly, you're buying a color camera in the last three years to pair with a Rev 7 LiDAR because you need both. You need to know that the blinkers are running on the car in front of you and the brake lights have fired and the stop light is green, not red. You get where all those things are with lidar and you know you you don't want to run into them but you still don't know the state of a lot of those objects without color information so our customers are already convinced of this fact and they're already they've been buying rev 7 lidars with with color cameras turns out that's not an ideal way to build most systems the calibration the synchronization the capability of today's cameras just isn't quite it's not at the the where it needs to be for you to have hyper safe, low latency, and incredible performance on the perception capability of these devices. It's much better if you could make one device that did all of it internally at a very, very deep architectural level that provided guarantees on the quality of the paired output, of the depth and the 3D and the color. And that's what Rev8 does. And it's hard because you have to do it right. you have to do it at the lowest level possible, which is at silicon chip level. And so the Rev8 has a L4 architecture silicon chip in it that has color and depth sensing combined for the very first time onto a single chip, all using the same optics that, you know, shared optics in front of this silicon chip that's doing nanosecond level timing, synchronization, and calibration of these these traditionally two different data streams so it's really powerful when you see it it's obvious this is a black and white tv to color color tv transition you're never going to go back from operating a color lidar once once you've started using it so it's a really big deal and ouster's been investing years on it and now we have this competitive edge because we're the only company in the market actually doing it and what do you think that does from a from a time perspective for you guys to go on sale if we're making an obvious sale how long do you think it takes before someone comes along with something that can you know present itself as even in the same bucket of uh performance well what's interesting is um there have been companies that have said that they're doing colorized lidar in various forms over the over the last couple years and it's made you know they've kind of been these non-events it was just at ces in january actually and there was a lidar company saying they had an rgb lidar and no one cared and the reason no one cared is because customers didn't care is because it was an afterthought it was it was a poorly implemented non-functional or non-useful kind of cobbled together system not something that was engineered at the silicon level so i expect there to be a lot of that kind of thing that happens for the next couple years as companies try to market the idea of color lidar but they won't derive the benefits of it because customers are smart i say you never trick a customer into buying a a lidar sensor all customers are going to test before they buy and um and uh and and so you can't kind to fake this color capability. And so I think we have multiple years, two to five years of Head Start, depending on, you know, which type of product and which environment we're using it in Head Start because of the silicon lead times associated with doing this correctly. In the meantime, there will be all kinds of press releases with companies claiming they've done it.

And it will be irrelevant because it'll be kind of a demo prototype system that customers can't actually field at scale awesome so then just shifting to the the sensor fusion and software piece of this right you know uh that's um something you guys have talked about you know you you've made some acquisitions related to some of the software but you know sensor fusion has been historically a critical part of performance for these these systems you know but obviously with more information native to the sensor you can redesign some of that sensor fusion in the computer can you talk a little bit about what you've done from an investment perspective around software, SensorFusion, and what that means for system simplicity and performance.

Yeah, so SensorFusion is a really nitty-gritty problem that every single customer has to solve. And it involves timing synchronization and understanding where different sensors are pointed and getting all of that data into one reference frame that a machine learning algorithm them can parse in a gpu you have to take all that data from many different sensors bucket it up properly and give it to machine learning and the the the quality of the machine learning output is directly related to how well you do all that that fusing of of data up front that's why native color native color just gets to sidestep some of that you know when we're talking about color camera versus LiDAR. But it also pertains to when you have multiple LiDAR sensors or maybe LiDAR sensors and stereo cameras or monocular cameras, stereo cameras, LiDARs and inertial measurement units. And so there's a broader ecosystem of sensors that all have to be calibrated, synchronized, and fused before you apply algorithms to them. And I think this is a this is a place that ouster can provide huge value by building that that software layer for customers and providing it as part of our our sdk and software ecosystem you know providing the the it just works platform of sensor perception and development that no other company has ever tackled um we've done this in a couple ways but the big one is that we acquired a company stereo labs just at the beginning of this year which is a leading provider of stereo cameras so that's our that's colorized point clouds from stereo cameras and monocular cameras that we can pair with our colorized rev8 point clouds and uh and stereo labs is also invested in this sdk the z sdk that has over 10 000 users um something they've built over the last decade and a half And what it does is it fuses the disparate data streams from all these different sensors into one coherent stream that they can then pass to machine learning algorithms. So we have 10,000 customers currently using the ZSDK. It's doing this exact, this really difficult technical challenge that every customer needs to solve. And now we're just investing more and more. We're getting Rev8 onto the platform. We're building it out to be more robust and rigorous for production environments. Because I want customers, I want the heavy equipment manufacturers of the world that are going to put, you know, 10,000 construction machines out into the world that have to last for 10 years. I want them running our software and our sensors. And so this is the start of that autonomy platform play, which is a major investment for us for the next decade.

Excellent. And, you know, just continuing on that, you know, you guys have deepened the NVIDIA partnership. and Rev8 to drive and Jetson and dedicated toolkits and drivers for Orin and Thor, you know, how does that reference design position and the kind of the brand, you know, compatibility with NVIDIA translate into the sales process and, you know, adoption rates for the Ouster platform?

Yeah, the partnership with NVIDIA has been great. We've really expanded our work. I mean, Rev8 did a couple things that immediately put us as a key partner for NVIDIA. The first is just ASLB automotive safety standards and just safety qualifications. So we're an automotive Rev8 product line now, and so the NVIDIA Drive group is very interested in that aspect because they want automotive qualified sensors. In the robotic space, we now have all the monocular and stereo and cameras along with the Rev8 LiDAR cameras. So we have the full suite of robotic vision sensors that we can deploy into the NVIDIA robotics ecosystem, Jetpack and NVIDIA Isaac. And then there's some other stuff that we can do in the future with smart infrastructure and things like that. But so we're a great partner because we have all of these sensors. They all work well together. And we're making the investment to make sure that they work in the NVIDIA ecosystems like Drive and Jetpack. And in some ways, it's a similar play to what we're doing internally with our own SDKs to make everything interoperable and a great ecosystem. but you know some customers are going to want to work in an nvidia ecosystem some customers are going to work want to work in an ouster ecosystem when it comes to software under the hood it's still ouster sensors and it's still nvidia chips whether it's our software platform or an nvidia drive platform or or an nvidia jet jetpack platform so everyone's kind of winning no matter what and it's and we're just providing a couple different ways to interface through software whether it's an ouster software sdk or an nvidia software sdk so um that's part of the broader

ecosystem play here we want we want customers to have a lot of different options to go build this high quality software and uh you know we're still under the hood the the the key enabling technology and the hardware and uh and the low-level work that's been put in on the software side on on on both ecosystems that's super helpful so ken um how are you guys translating that into you know evidence of pricing margins durability of cash flow how are you thinking about that you know there's maybe this is for both of you guys but i'll put you on the spot ken and give angus a minute to catch his breath um you know that's that's the real heart of this right is you know the the business model you guys have built and the operating leverage plus the flywheel of amplifying sales here. So how are you thinking about that mode evolving from here and translating into margin?

Well, I think it's three steps. Number one is continuing this rotation into a platform, having the ability to offer customers both the LiDAR, the camera, the compute, and the software to it. That becomes a very sticky and becomes value add versus just selling an individual component. And so continuing that rotation to bring solutions to the marketplace that can help, you know, it's like we do with Blue City with a no-code turnkey ITS solution is a perfect example of how we're going to continue to innovate and grow this platform out. I think the second piece is continuing to be diverse in our product portfolio and finding ways that we can continue to go across our verticals with the products and offerings that we have. Not being niche or specific to a specific use case like ADOS or consumer ADOS has really benefited the company in not being price pointed down or being pressured into a point where you have to lower your standards in order to win business. Having a portfolio that can go across all these different use cases has really been invaluable to helping bolster that overall ASP and the value that people can see from our platform. So those two things really are the major drivers that we see in the long term. And last but not least is innovation. You know, what Angus didn't say is, you know, with the new L4 chip that we released, we have programs and roadmaps we're working on today for next generation innovation. So continuing that investment into innovation, continuing to broaden our portfolio, not just from new chips, but also from form factors that can fit into different use cases using the same base technology. That's something you're going to see us invest in over the next 12 to 24 months. It's going to keep that ASP and that margin at a good level.

Excellent. And then just shifting gears a little bit into the supply chain. And, you know, obviously you guys have, you know, been qualified for the blue UAS, and there's a lot of Buy America activity right now, you know, the tariff dynamics. Can you talk a little bit about how you're seeing the supply chain evolve as you start to scale up a little bit more actively and start to see some of these other elements impact, you know, the sales process, as well as just component availability and pricing?

Well, I can start with that, Angus. I think number one is having the ability to buy ahead on long lead time parts. The good thing about having visibility and a backlog with your partners is you know what they're looking for, what quantities they're at. So we've been able to go out into the marketplace and secure enough components to give us visibility, sometimes 18 to 24 months into the future to make sure that we have that inventory on hand. You might have seen, if you look at our balance sheet, it's ticking up a little bit, and that's predominantly because of two reasons. One, we're going to continue to invest more in the supply chain. We want to be a provider that can do quick turns with folks, particularly within the Stereo Labs business. So you're going to continue to see us invest more in that finished good inventory to be able to supply and meet the market demand pretty quickly. So continuing to invest in the supply chain and the capacity at our CEMs is something that we're going to focus on here over the next 12 months.

Angus, would you talk about anything that you would supplement around that?

Yeah, maybe around the strategic aspects with customers, I think is part of the question you're asking is like things like Blue UAS, which is a certification around the source of our supply chain components, really a domestic source or Western partners for sourcing strategic technologies like LiDAR. So there's been a lot of effort to make us a preferred partner for companies that need a secured supply chain of LiDAR. It's been years of effort. We've divested from a Chinese supply chain as one example, which is no small feat. And it's why we're able to get a certification like a Blue UAS certification. These aren't just window dressing. this is real effort and uh and uh and getting the certification was was a huge lift um and it's just one that's that we've been investing in for years at this point so um there's definitely you know when i go into customer conversations now it's one of the first questions that gets asked is where are you buying your parts where your major suppliers where are you manufacturing the product how can i you know guarantee that i'm going to maintain a supply of this this product and you don't have undue risk in your supply chain so that's and part of it's about geopolitics and part of it is about just like things like semiconductor crunch and uh continuity of supply and things like that so we have a world-class operations team and supply chain team that has built very deep partnerships with our you know critical single source suppliers um and it's it's just not something you build overnight we we've been working on this for years and i think we're are way ahead of kind of the average technology company when it comes to this.

Excellent. Yeah, speaking of de-risking, you guys have raised a lot of money in the last 12 months, And you put yourself in a fantastic position from a balance sheet perspective and a model. You know, you've kind of stayed disciplined on your spending. You've got kind of single-digit, low single-digit millions of EBITDA losses per quarter, you over 400, over $450 million of cash, you know, after this last transaction, you know, talk to me about what, you know, what that does for you from a customer perspective and a planning perspective for the organization as you think about trying to become the, you know, well, really being the dominant LiDAR player in North America and Europe, you know, on a go-forward basis.

Yeah. I mean, the first thing is we got to this point because we were good stewards of cash and we're going to continue to be good stewards of cash despite having 450 plus million on the balance sheet. But it is a critical, it's a selling point. You know, when I'm in customer conversations and, you know, a lot of times now these are C-suite level conversations because LiDAR has become a critical technology for the future of autonomy platforms kind of the world over and there aren't that many places to buy LiDAR. Alistair is one of very few companies that a lot of companies are able to source from. So they want to know that we have a long history ahead of us. And this completely removes, these raises that we did completely remove any kind of financial funding risk from Alistair. You know, we said on the earnings call, we see this as we have a fully funded business model, you know regardless of kind of what happens or what directions and investments we make in the future we're fully funded so that resonates you know internally it resonates with investors and it it resonates with customers it's definitely a strategic selling aspect of of what we've done here so what you know as you guys look at the landscape you know in the physical ai space is evolving pretty quickly you know where are the the the biggest risks that you guys are thinking about right now and um you know where's the the most rapid evolution that you're gonna have to

respond to you know i think as folks start to digest the impact of ai and and you know on some of the design cycles you know there is some improvement in some kind of you know just fluff you know about what's happening here and so there's there's i think a lot of bs and then there's some real things that are happening so here's how you guys are thinking about technology risk and market risk on a go-forward basis and how Oster is getting ready for that?

You know, we diversified fundamentally because it reduced risk, diversified commercially into our four markets, automotive, industrial, smart infrastructure, and robotics, because it reduces risk. And a lot of the risk is technology risk associated with, you know, our customer, a particular type of customer scaling an emerging technology. And when we founded Ouster in 2015, the emerging technology that had risk was robo-taxis. And we were smart to diversify into many different verticals. We still sell into robo-taxis, and today we have a great business in our robo-taxi, robo-trucking customers. But man, was it a longer timeline to scale than most people predicted in 2015. other than, you know, we were one of the few that kind of had a realistic view on this. So, and that's not to say that there wasn't a lot of revenue generated along the way for things like ladder sensors into robotaxi companies. So I think that there's, I take that same viewpoint to the current scaling of robotics. Obviously, everything that's happening with advanced robotics is real, is here to stay. There are going to be humanoid robots doing productive work in our society, guaranteed, and already are in some cases. But we have purposefully diversified to the point that, you know, we don't know the exact trajectory of that scale up a few moments. It's very frothy right now, and people are deploying a lot of that type of robot or building a lot. We're selling a lot of cameras and a lot of LiDARs into those applications. that's great revenue but it's also not the only revenue that we generate we're diversified because no one can predict the way that this set of physical ai robotics is going to progress um uh in in in kind of fine-grained detail um all i can say is that i know that it's growing very significantly and ouster is a core part of it and you know and now we're coming to end here and and we've spent a lot of time on technology which i kind of enjoy uh as much as some of the finance pieces but you know as we think about you know a robotic future right and

the interaction of robots in human environments and you know human machine interaction you know you guys uh ruled out even though there's a lot of you know attention around rgb elements of the lidar the functional safety piece of the ladder is a big deal right in terms of where risks sits at the product level and who takes this on. And, you know, the way you guys explained it to me was just like it's like automated breaking, right, you know, and that sort of functionality.

Talk to me about how important that is as folks start to figure out, you know, human machine interaction with these bots and what you bring to the table in terms of facilitating that market adoption and growth. yeah this is a great this is somewhat of a subtle part of our strategy or maybe you know we haven't been communicating enough about how important safety certified sensors are and safety in general is for physical ai you know if you a world in which there are millions and millions of these powerful capable robots in our world is only a good future if those robots are safe And humans are bad at judging the level of safety required for us to be comfortable with technology. This is not 99% safety. We can't have one in 100 robots or doing something unsafe, falling on your toddler in your home. You can't have one in 100 days, a robot breaking the dishes in your dishwasher. You can't do this over one in 1,000 days if it comes to human safety. It might be, if you ask people, maybe one in every 10,000 days across the robot population, you can have a robot doing something mildly unsafe in your home, but not when it comes to your kids. So there may be one in 100,000 robots can do something unsafe every year in someone's That's probably the level where most people will accept it. That is vastly beyond where we are today for this technology. and a core that you know the path from getting where we are today to getting where we need to be ultimately comes down to well it's many layered but a core component is certifiable perception knowing that the world around you that you're sensing is being sensed in a guaranteed certified way that is is quote functionally safe and uh and is is uh is is correct in kind of all ways and is fault tolerant. And so that's what we're beginning to sell is certified safety critical LiDAR sensors. All Rev8s are going to have this option. And it means that you will literally be able to trust your life and the life of everyone around you on the output of Ouster's Rev8 LiDAR products. And that's how we bridge the gap from a robot that works one in 100 days to a robot that works one in 100,000 days, which is where we need to get. There are many more layers to it, but a really critical and hard part of it is the underlying sensing hardware. And there's a huge amount of value to capture from being a company that gets there and builds a reputation on providing that kind of technology first.

Well, given the fact that we're just about at time, and that's a very big idea for people to digest and think about how to value that, I think we'll We'll leave it there. Guys, I want to thank you all for your time and your partnership here. You know, we have the working relationship with you guys and are excited about what you're building. For the investors here, please give me a call if you have any questions. We're happy to answer questions or get you in touch with the company as it makes sense. So thanks, guys, for the afternoon, and we'll look forward to talking to you soon.

Always a pleasure.