Good afternoon, and welcome to the AEye, Inc. Q2 2022 update conference call. All participants will be in listen only mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star then one on your telephone keypad. To withdraw your question, please press star then two. Please note this event is being recorded. I would now like to turn the conference over to Clyde Montevirgen. Please go ahead.
Thank you, and welcome everyone to AEye's Q2 2022 earnings call. With me today are Blair LaCorte, our Chief Executive Officer, and Bob Brown, our Chief Financial Officer. Earlier today, we announced our financial results for the Q2 of 2022. A copy of our press release can be found on our website at investors.aeye.ai. Before we begin, I would like to remind participants that during this call, management may make forward-looking statements including without limitation, statements regarding our future operating results, future performance, growth strategy, and financial outlook. Forward-looking statements are based on our current expectations and assumptions regarding our business, the industry, and other conditions. These forward-looking statements are subject to inherent risks, uncertainties, and changes in circumstances that are difficult or impossible to predict. Our actual results may differ materially from those contemplated by the forward-looking statements.
We caution you therefore against placing undue reliance on any of these forward-looking statements. You can find more information about the risks, uncertainties and other factors in our reports filed from time to time with the Securities and Exchange Commission, including in our quarterly report on Form 10-Q for the period ended June 30, 2022. All information discussed today is as of August 15, 2022, and we do not intend and undertake no obligation to update any forward-looking statements, whether as a result of new information, future developments, or otherwise, except as may be required by law. In addition, today's discussion will include references to certain non-GAAP financial measures. These non-GAAP measures are presented for supplemental informational purposes only and should not be considered as a substitute for financial information presented in accordance with GAAP.
A reconciliation of these measures to the most directly comparable GAAP measures is available on our press release, and you should refer to our reconciliations of non-GAAP financial measures to the most directly comparable GAAP measures in our earnings release. With that, I'll pass it over to Blair.
Thank you, Clyde, and thank you for joining us and investing your time to participate in our quarterly update. As you have seen in our earnings release today, we had a solid finish to our Q2, meeting our revenue expectations and significantly outperforming our expense and cash plan. Our main investor themes and objectives for 2022 remain unchanged. We see strong evidence that customer demand for adaptive LiDAR will continue to accelerate as we prepare to launch the AEye 4Sight platform in Q3. As always, our focus on execution remains paramount. Given the present global market and macro business environment instability, you will see that we have proactively taken actions in Q2 to optimize schedules and modulate our spend. As a result, we ended the quarter with a cash balance that was $11 million higher than our plan.
Today, we'll be highlighting four of our key 2022 objectives, and we'll update you on our progress in Q2. First and paramount is the release of both the AEye and Continental products on our next generation 4Sight platform. In Q2, we made the initial transfer of our platform to our contract manufacturing partner, Sanmina, on schedule. Sanmina will be manufacturing our AEye 4Sight product line for the industrial markets. While we are not experiencing a reduction in demand, the disruption in global supply chains has delayed the start of production to late Q3. In Q2, we also transferred to our lead customer, Continental, their B sample on schedule. Continental will be manufacturing their HRL131 ADAS product in their state-of-the-art Ingolstadt, Germany facility.
We believe we're the only LiDAR company that expects to have the capability to manufacture completed LiDAR units in high volume production lines with two industry-leading global partners in 2023. Second, since our hardware design freeze earlier this year, we have been advancing our ability to utilize our sensor-based operating system to configure hardware performance dynamically as a key differentiator from our peers. These software-definable sensors allow AEye to continually innovate between hardware cycles. Today, we'll show you several new groundbreaking capabilities we added in Q2. Third, we have been engaging with all of our key end user markets as we prepare to roll out our new products. For example, we will share with you how quickly we have extended our reach into Aerospace and defense with several new strategic engagements.
Fourth, we continue to build out a world-class team, public company infrastructure, and optimize our liquidity in the currently volatile financial markets. In short, today we will show you material progress across all four of our stated objectives. I will focus today on our product, our manufacturing progress, and customer traction. Bob will discuss financial results and metrics that support these efforts. I will then conclude by sharing a few closing remarks. The call will then be open for Q&A. As I have outlined in our executive summary, we have made significant progress on our path to productization, both on our AI product with our partner, Sanmina, and our first AI ADAS licensed product with our customer, Continental. For our AI product, you can see Sanmina is ramping up our initial sensor production line.
Our precision optical components are sourced from top-tier suppliers worldwide for final sensor assembly in this Sanmina facility. We also jointly developed and deployed an automated state-of-the-art calibration and end-of-line testing and validation facility where each sensor is put through its paces to ensure that it reliably delivers AEye's renowned superior performance. As we head towards large-scale distribution, we are also testing our new ruggedized, lower-cost, environmentally friendly packaging. For our automotive ADAS product, we are excited to publicly share for the first time a major milestone for AI. We have transferred manufacturing of the B sample Continental HRL131 high-performance LiDAR to Continental's world-class manufacturing facility in Ingolstadt, Germany. It is our belief that this is the first time that a major tier one has transferred into production a licensed long-range LiDAR technology with the intention to deliver it to their installed customer base.
This is a validation of our unique capital-light business model in automotive. Now let's switch gears. Excuse the pun. Today, we would like to share something remarkable. In the next two minutes, we will demonstrate how we utilize our sensor-based OS to instantaneously transform our LiDAR hardware into a completely new system, reconfiguring all of the individual components entirely through our software operating system. As Sanmina pointed out in our last earnings call, we can quickly add capabilities to enter new markets, enhance features within existing markets, and customize performance for evolving use cases, all without retooling the manufacturing line. You can think of this software configurability similar to how smartphones utilize an OS to add capabilities to the same phone using apps and completely transforming the same hardware into a different product, such as a pedometer, a document scanner, or even a Geiger counter.
Today, we're demonstrating what we believe are two industry first capabilities that could power new applications. Our 4Sight platform's new zoom and stabilization. Let's start with zoom cam. Similar to how cameras change between wide angle and telephoto modes, 4Sight can dynamically zoom in on objects on the fly to add resolution at extremely long distances. Remember, passive LiDAR systems are limited as they scan with fixed patterns at fixed distances. This new capability not only opens up new markets, but improves confidence in object tracking for existing customers. In this automotive example on the highway, we receive three points on an SUV at 300 meters. With zoom cam enabled, we improve resolution on distant objects ahead and now receive 19 points from the same SUV beyond 400 meters. This six times increase in resolution is a game changer in autonomous decision-making.
In rail, trains equipped with 4Sight could have one mode designed for scanning a station or platform and can use zoom cam while in transit to detect track obstructions at extremely long ranges to allow adequate train stopping distance. In Aerospace and defense, helicopters could utilize zoom cam for longer ranges to detect wires or birds in their path and switch to a wider field of view to locate the ground during landing maneuvers. Now let's show you steady cam. Similar to what a gimbal does in hardware to help cameras compensate for unsteady movement, 4Sight can dynamically adjust the software for any vehicle or use case. All roads aren't flat, smooth, or straight. ADAS and autonomous vehicles require this capability to enable horizon tracking to compensate for less than optimal road conditions. This becomes even more important for off-road, high-speed, or weather-impaired scenarios.
In this video, we're using our automated testing rig to move the sensor pitch to simulate varying road conditions. You'll notice with steady cam disabled, the dense region of interest moves up and down with the sensor pitch, which we know is a problem when a vehicle is going over speed bumps, potholes, or sloped roads. If we look at the same scene with steady cam enabled, you'll see 4Sight automatically adapting to the change in pitch dynamically by repositioning its laser scan pattern to keep the region of interest where it needs to be, right on the horizon. When you look at the two outputs side by side, the importance of software-enabled steady cam becomes apparent as the AI sensor is able to put more density where you need it.
This patented horizon tracking capability, we believe is a key to adoption of Highway Autopilot, a popular feature consumers have been requesting from automotive OEMs. This is a game changer not only in automotive, but also for off-highway applications such as mining, construction, and agriculture. Steady cam allows these autonomous industrial vehicles to easily navigate a constantly changing ground elevation, which impacts vehicle pitch. As we prepare to launch our new AEye and Continental licensed products in Q3, we already have significant traction across several key markets. Again, in automotive and trucking, we use a licensing model. Our lead customer is Continental, who is building their next generation high performance long-range LiDAR on the AEye 4Sight intelligent sensing platform. We are jointly engaged on multiple opportunities with major global automotive and trucking OEMs. Continental's B sample of their high performance HRL131 LiDAR has been well-received.
The performance of this product, combined with Continental's ability to scale production, quickly puts us on track to move to C sample phase in 2023. In the smart infrastructure market, AEye's 4Sight sensors are being installed by top-tier system integration partners for applications such as automatic incident detection, smart tolling, wrong way driver detection, and smart intersections. The implementations have been worldwide, from intersections in California and Florida, to pedestrian and bicycle detection systems in Ireland, to highway incident detection in Virginia, and automated tolling applications across Europe. We will be showcasing solutions from many of these partners at the upcoming ITS World Congress event in Los Angeles this September. Today, however, we want to highlight our progress in a market that is well known to AEye's executive team, Aerospace and defense. Our collective defense industry experience is encapsulated in our systems approach.
AEye's 4Sight sensors are uniquely capable of long-range detection, exceeding three kilometers with custom optics, are flexible enough to track a bullet at greater than 20,000 frames per second, and can either cue off of other sensors or self-cue, adapting to place high-density regions of interest of up to 1,600 points per square degree around targets. These capabilities, enabled by 4Sight's in-sensor perception, greatly expand the utility of AEye and machine learning for defense applications. Add in additional capabilities like zoom cam and steady cam, and you can see why these customers are so excited. I would be remiss if I also did not mention at this point, capabilities enabled by a recently granted AEye patent on optical communications that directly expands our ability to extend our solution envelope for Aerospace and defense.
With this capability, the same sensor can not only navigate and acquire targets, but could allow the LiDAR to optically communicate between assets in theater, enabling the ability to coordinate and swarm where Wi-Fi and other communication systems aren't available. Most importantly today, we are announcing a cornerstone partnership with Booz Allen Hamilton, one of the Department of Defense's premier digital systems integrators and a leader in data-driven artificial intelligence. In addition, we will be integrating AEye's 4Sight LiDAR platform to enhance Booz Allen's real-time embedded processor perception stack with high-quality spatial information, and ultimately, to enable their digital battlespace vision. This vision combines technologies like high-performance LiDAR, artificial intelligence, machine learning, and edge computing, providing an information-driven, fully integrated conflict space to realize information superiority and achieve overmatch across all war fighting domains.
This partnership with Booz Allen Hamilton significantly accelerates our time to market in the Aerospace and defense domain. In addition to our strategic partnership with Booz Allen, we are also excited to announce another highly respected partner in the Aerospace market, LAKE FUSION Technologies, a company with a proven history of delivering LiDAR-based perception and software applications. We will be working with LAKE FUSION to create airborne applications for deployment in 2023. To support these expanded engagements, we have opened a new office on the Space Coast of Florida that will be the focal point of our efforts in this area. Our new Florida office will be led by industry veteran, Steve Fry, who has extensive Aerospace and defense experience at companies like L3Harris and Lockheed Martin. Now let's turn to our financial update with our CFO, Bob Brown.
Thanks, Blair, and good afternoon, everyone. I would like to discuss our Q2 financial performance, our strategic cash management, and then speak briefly on our outlook for the balance of the year. Revenue in the Q2 was $706,000, which was consistent with our guidance of $700,000 of revenue for the quarter. We have been managing our spending carefully over the last quarter, given the slowing economy and market volatility. We are continuing to grow our team and advance our technology, but we are doing so in a very thoughtful way. GAAP operating expenses were $25.9 million in the Q2, an increase of $1.4 million from the prior quarter, which relates to strategic investments to scale our team and advance our R&D and sales and marketing efforts.
Conversely, our G&A expenses declined by $1.5 million quarter-over-quarter. In addition, our non-GAAP operating expenses were $19.1 million in the Q2, down slightly relative to Q1. Net loss was $26.5 million on a GAAP basis, and GAAP EPS was a loss of $0.17. Net loss on a non-GAAP basis was $19.8 million, and non-GAAP EPS was a loss of $0.13 or $0.02 better than the consensus estimate for Q2. We continue to manage our cash carefully. Net cash used in operating activities for the quarter was $17.1 million, which increased by $1.1 million from the prior quarter. Our capital expenditures in the quarter were nominal, under $1 million.
We exited the Q2 with $125.8 million of cash equivalents, and marketable securities on our balance sheet. That includes $1.4 million in proceeds during the quarter from issuing shares under our $125 million common stock purchase agreement, which now has up to $123.6 million of potential proceeds remaining. When you consider our cash equivalents, and marketable securities, together with the potential proceeds from our remaining common stock purchase agreement, we have total available liquidity of approximately $250 million. We believe that provides us with a solid financial base to support our growing business. We expect to make modest use of our common stock purchase agreement in the Q3.
We continue to make improvements as an organization and have grown from an R&D-focused entity into a scalable product-focused commercial operation. We believe that our capital-light business model will allow us to optimize our resources in order to mitigate risks and take advantage of market shifts faster and more effectively than our peers. By focusing on our core competencies, we intend to continue to extend our industry-leading position. Let me turn now to our near-term outlook. We expect to see modest revenue growth over the next few quarters as manufacturing of our commercial product begins to ramp up at Sanmina, setting up our ability to scale volumes in 2023. As Blair mentioned, our initial ramp is getting underway in Q3.
However, we have not been immune to the impact of supply chain challenges, which has had a direct impact on our ability to build product at expected volumes requested by our customers. Because of these industry-wide constraints, we're taking a more cautious view on revenue for the second half overall. We expect our revenue for the Q3 to be in the range of $700,000-$900,000. While we have not seen a reduction in demand, we expect that these global supply chain challenges are going to be with us for a while longer. For the full year 2022, we now expect our revenue to be in the range of $3 million-$4 million. In response to this uncertain environment, as we noted earlier, we've been managing our spending carefully without compromising our expected growth in 2023.
As a result, even at the lower end of our revenue guidance, we expect our full year net loss on a non-GAAP basis, excluding stock-based compensation expense, to be in the range of $90-$95 million, improving from the $100 million non-GAAP net loss we guided to at the beginning of the year. We do expect our capital expenditures to grow modestly in the second half as we work with our contract manufacturing partners on the production ramp. While we anticipate slower growth in the broader economy and supply chain challenges to persist in the near term, we have an experienced team to manage through that, and we're confident in both the superiority of our product and the market opportunity in front of us. With that, I'll turn the call back to Blair to wrap things up before the Q&A. Blair?
Thank you, Bob. I want to close by thanking each AEye team member for their impactful contributions for this successful quarter, where we made great strides in product development, customer engagement, and enhancing our financial strength. We look forward to continued progress in the second half of 2022 and believe we are well positioned to scale in 2023. Now, let's open the call for questions.
We will now begin the question and answer session. To ask a question, you may press star then one on your telephone keypad. If you are using a speakerphone, please pick up your handset before pressing the key. To withdraw your question, please press star then two. We ask that you please limit yourself to one question and one follow-up. If you have further questions, you may re-enter the question queue. Once again, that was star then one to ask a question. At this time, we will pause momentarily to assemble the roster. Our first question will come from Suji Desilva of Roth Capital. Please go ahead.
Hi, Blair. Hi, Bob. Just wanted to get a sense, the changes in the near-term outlook, if that has any impact on what you may have communicated during the SPAC merger in terms of the intermediate opportunity and the timing of the volume ramp, for the auto and non-auto businesses?
Yeah. Hey, Suji, it's Bob. I think we're not gonna give a longer-term outlook on today's call, so we're gonna continue to give annual guidance. I think this is in terms of the near-term impact that we talked about. This is really supply chain challenges primarily affecting the industrial business. It's really us working through some of those basically component shortages that have impacted us in the short term in terms of the ramp. Again, this primarily relates to the industrial business here for Q3 and Q4. That's the impact you're really seeing. Meanwhile, we continue to move full speed ahead with Continental on the B samples and working very closely with them on a number of opportunities. Blair may wanna comment on the automotive side and the opportunities there.
Yeah, no, I think that was well said. What you're seeing in the guidance today has to do with our ability to get products out of the factory versus the demand in the industrial markets we're seeing for those products.
Okay. Appreciate that color, Blair and Bob. Then, you know, you talk about Highway Autopilot that's clearly being watched carefully in terms of timing of adoption. I'm just curious if that's a L4 feature or if that can come in L2 plus L3. What are the key features like Steadicam that are gonna be needed to make that something that the Tier 1s are comfortable implementing?
Right. You know, we've talked before, so you know the kind of way we contextualize adding LiDAR into the market. Number one, we believe that cameras and radar aren't going away. Number two, we believe that there's a huge advantage in use of orthogonal data for certain features. You know, one of those features in auto is Highway Autopilot, because as you've seen, others try with different solutions, it's very difficult at higher speeds where you need reaction time with small objects and in highly dense metal environments where you have guardrails to actually enable a Highway Autopilot without having a high performance LiDAR system that can do a couple of things, right? One is you need to be able to have the density to find those small objects on the road.
Number two, you need to be able to have the distance at those higher speeds to allow lane changing or stopping. Number three, which is, I think, probably one of the things that is most difficult for non-adaptive systems, is while you're doing that, you need to also be able to follow cut-ins or wide angle or lateral entry type of activities. When we talk about the Steadicam capability, what we're really addressing is finding those very small objects like bricks on the road where you're not bouncing and you're not gonna miss it because that you can't actually attach to the road surface at the longer distances.
Okay. That's helpful there. Thanks. You talked about several end markets in the prepared remarks. Can you give a sense of maybe which ones have the relative opportunity sizes of each? I know it's, you know, for just kind of relative, notions, and more importantly, which ones have the nearer time to production revenue ramp? Just kind of refresh us on that.
Sure. As you know, the automotive market, because of the functional safety requirements, when the demand moved from, say, B2B or the autonomous vehicles, into the ADAS type systems that have been coming together faster, that's a consumer product and therefore you not only need to have a product, but you need to put it through functional safety testing. The revenues ramp up over a number of years. You get a pilot, you get a contract, and then ultimately your system is tested, and it will be implemented. Then over time, either you'll continue to scale up in number of car brands or models, or you'll stay in a small section, and someone else will come in. Right? That's the way the automotive market moves.
When you look across our sector today, the automotive market, the way you have to judge it is who you're, you know, what's the performance of your product, who you're working with, and where are you getting traction and pilots and then ultimately longer term contracts. The near term revenue across our industry is really industrial revenue, right? The industrial market for LiDAR has been around for a, you know, a decent amount of time. You know, in the, you know, Aerospace and defense and telecom business, we're talking about 60 years. In traditional industrial markets, there's been about 20 years of use of LiDAR systems. Now, I'll caveat that by saying it's been bimodal. There's been a lot of very low-end mapping systems.
Mm-hmm
... you know, substantive to GIS, and then there's also been very, very high-end systems that were very, very expensive for very unique or specialized things like being able to see in the dark in a mine with dust. Okay. When you take a look at the industrial markets in the shorter term, our belief is that the operators of ITS have been expanding for a couple of reasons. One is you've already seen a lot of cameras and radar implemented in everything from stoplights to toll roads, and this system actually has tremendous value either as an addition or replacing those systems. Most governments around the world, including the new transportation bill from the United States, are actually setting records for funding to initiate these type of activities.
I think you're gonna see in ITS and smart cities a significant ramp over the, you know, the next two, three, four, five years, redoing infrastructure. The second market that we often talk about is the more industrial construction, agriculture, and mining type markets. Again, smaller markets, but with high value, and they're ready for systems today. The value proposition is different. An ITS system is obviously a safety-based system, and it's selling data to the cities. The models in those industrial markets tend to be more closed loop within a certain site, and they tend to have much higher value in keeping safety high and throughput high.
Those two things are unfortunately related, where if you have a safety accident, it can cost you $50 million a day to close down a segment of a mine. The third area which we also highlighted today is really a back to the future type area, where as I said, for the past 60-70 years, Aerospace and defense has really used LiDAR. I think a new emerging market in Aerospace defense is coming in, which is really using COTS, you know, or commercial off-the-shelf products that are now reentering Aerospace and defense. That's one of the things that we announced today with our partnerships, is we're seeing great demand.
I think that ultimately will in the near term may dwarf some of the other industrial markets just because they've been using sensing systems. Quite honestly, if you saw Top Gun, you would have seen a system that a bunch of our engineers did, which is the LiDAR system on the side of Tom Cruise's jet, right? They understand the value of spatial data.
Sure.
Again, our opinion, you know, is that ITS and smart cities, you'll see the narrower niche in agricultural construction and mining, but higher, you know, value in pricing. Then you're also gonna see the emergence of Aerospace and defense.
Thanks, Blair. That was really comprehensive. One last quick question then I'll pass it along. The optical communications technology you talked about, is that applicable potentially for consumer V2X? Thanks.
Sure. This is a more complicated question in the sense that every single technology has to be actually weighed against, you know, what's there today. You know, what are you gonna be actually moving out. There's an opportunity for it, but it's much more applicable in the short term, we believe, in some of the more industrial markets. Again, we wouldn't say that it's, you know, that it couldn't be used for V2V, maybe even more for V2X, but I think the industrial markets tend to have a closed loop infrastructure.
Hmm
It's easiest to implement there. I think if you start to see some traction in V2X and industrial, it's easier to actually migrate it back into the consumer markets.
Okay. Thanks, Blair. Thanks, Bob.
Thanks, Suji.
The next question comes from Hans Chung of D.A. Davidson. Please go ahead.
Hi, thank you for taking my question. First I want to follow up on the supply chain issue. Can you provide some color around the shortage I think you mentioned in some component, and just wondering what kind of the component. Is that some kind of the chips, the chip or is, I don't know, maybe laser or other stuff. Also, how are you confident with the ramping, I mean, tracking to the end of the quarter and any potential challenges here in terms of supply chain as we move on?
Sure. I'll handle the first part and I'll let Bob handle the second part of the question. Clearly the chip crisis still impacts us. I wouldn't say it is the main driver of what we've been dealing with in the last few months. Ironically, it's been some things that you wouldn't think of, very small connectors or very small BOM cost pieces of the system. Unfortunately what you realize is, although you've locked down all of your main component suppliers, if the entire BOM is not ready, you can't finish full assembly. I appreciate the question because, you know, I think there's still challenges around chips, but it's mostly it could be solved with price if we wanted to.
Some of the shakeout now is just that these really small things, and Bob will get mad at me if I go into too much detail, but one of the challenges, you know, we spent a decent amount of time on was a $2 part that just wasn't available, right? And you know, was unexpected. I would leave you thinking, look, we're not gonna get out of supply chain challenges anytime soon, you know, because the world is what it is. I think what you're seeing is we and the rest of us, you know, the rest of the industry are working through how to manage those.
I think the little bit of this last bump in the road was just the unexpected that tiny little things, not big things, could have actually, you know, caused us some consternation in how we get the final assembly done.
Got it.
Bob, I don't know if you can handle the next.
Yeah. Just to add to that, Hans, yeah, I think Blair's exactly right. We're doing our best to get those parts that we need as quickly as we can. We think we're gonna be able to solve much of that during this quarter. We won't have necessarily access to as many parts as early as we'd like, so that is putting more ramp into the back end of the quarter, as Blair said in his remarks. Consequently, there's some risk there, of course, on the revenue side for Q3 with more of that revenue coming in later in the quarter. We did contemplate that as part of the guidance we gave on revenue for the quarter of $700,000-$900,000.
Part of that range incorporates some risk around getting these parts as quickly as we'd like and actually getting into early production. It has set us back both in terms of, you know, the production as well as some testing that we need to do on the products. We're working through all that expeditiously and we think we'll make some good progress against that in the quarter. There does remain some risk there, right, that we've got to work through.
Right. Hans, you know, I know you'll go back through the math in your head and what you'll see when you look at this is that it's probably put us back two months, right? When you take a look at what Bob said about getting testing done early enough so that we feel comfortable on product and EOL end-to-end line, you know, calibration and also in just getting enough parts into the system. We don't feel like this is a, you know, a structural problem that will continue over time.
We do believe it's something we're gonna live with, a low level of this, and we're just gonna have to, like everyone else, mitigate the risk and plan for it.
Got it. That's helpful. Our next question is about the new aero defense business. Is that like the kind of incremental opportunity based on the current 4Sight platform, or is sort of new application or based on new platform?
Right. Look, it's not a new business to many of us in the company. It was not considered a large portion of our plan in the short run because we weren't sure, you know, how it would be, how the product would be accepted. What we found is that there's been a much more pull than we thought. I don't know if that is a, Bob, is that a fair,
Yeah. I think we had always contemplated aero and defense as an opportunity, Hans, but we hadn't necessarily built that explicitly in the models for the reason Blair suggested. As you said, this is really a commercial off-the-shelf solution, but because we've got this unique software capability, we're able to adapt to different solutions like a defense sort of application, right? That's one of the strengths of this model and this technology, is that it is very adaptable to different markets using that same platform. We think we'll get synergies out of that over time, and defense is one example of that, where we can address that market with the same fundamental platform with different software implementations.
Yeah. To emphasize that, I think part of your question was, this product will be coming off the Sanmina line. It was not gonna be a new line. It's the same, it's within the industrial. Now, there may be times, you know, in the future, just like, you know, with everything else, where there may be a customer who wants to do something that's very different, and then we'll address those opportunities as they come up. But today, we're assuming this is just another application off of our 4Sight operating system.
Got it. Okay. Then next, recently, one of your peers got a deal with the Volkswagen Group, and it seems like kind of a long-term big deal. I know, would that imply that this kind of closes the door with you and Continental to Volkswagen, or is it not necessarily?
No, no. In fact, you know, I sent a note to congratulate them. You know, they, those guys come from actually the same background we do, in a sense, from the military background. That was a deal that we were not involved in, and it actually predated our and Continental's partnership. Remember, in our model, we don't go direct to automotive without a licensee. You know, we were not necessarily involved in that deal. Also, when you look, take a look at Volkswagen, they, you know, have multiple different radar systems. They'll have multiple different LiDAR systems, multiple different camera systems. This is, they, you know, there's been an initial selection or nomination for a certain application.
The beauty of, you know, I think we talked about this the last call. The beauty of where the automotive industry is moving is to software definable cars. The point there is that they'll have multiple sensors with multiple applications that they can add value to the consumer and ultimately, you know, be able to charge for that. You know, we look at this as a good sign that these initial systems are getting specced in. You know, there'll be many, many more opportunities, not only in people like VW but, you know, the other 25 OEM brands.
Got it. Okay. One last quick. Will you be able to benefit from recently passed the CHIPS Act bill in some ways?
Right. Let's first of all, we're a huge supporter of this because it drives innovation, and we need that, and we think we have a lot of opportunities there. We are actually number one participating in the LiDAR Coalition at the highest levels to actually help everybody in the industry. We specifically see opportunities within our domain because we work with so many partners. We're an open system with modular hardware. Either with us working on design or with some of our partners, we think this is a good opportunity to accelerate innovation. Now, Bob actually came from that industry. I don't know if you had any thoughts.
Yeah. No. Our model, Hans, really benefits from development in the semiconductor ecosystem, right? Because of what Blair said, we're really this open modular architecture, and our strategy has been to use components that are developed by major players in the semiconductor industry. So the CHIPS Act, we think supports certainly that whole ecosystem, and therefore, we're gonna benefit from that probably indirectly. We'll also look at whether there are some direct benefits as well, but anything that supports the semiconductor ecosystem supports our platform.
Right. Thank you, guys.
The next question comes from Michael Mullen of B. Riley. Please go ahead.
Good afternoon. This is Michael Mullen on behalf of Craig Ellis. Thanks for letting us ask a few questions. To start, I just wanted to begin with your industrial segment. Given AEye's focus on high performance and long-range sensors in this market and its various applications, could you just talk about the competitive landscape in this particular area? What kind of greenfield opportunities are there? Like, Aerospace and defense, as you mentioned, is an emerging opportunity. How do you think they're currently served or underserved, and where does AEye fit into that mix?
Sure. What I would say first is that the way we look at the industrial markets is through you know value-based use cases right? You know although we have to say it's an ITS it's mining it's agriculture it's Aerospace and defense there's a set of things that you can do with a very fast powerful deterministic sensor like LiDAR. The way we've actually approached each market is to take a look at what we can do that helps them either to increase safety increase efficiency or to add features that they can make more money on.
If you take a look at the business model behind that, part of the challenge has been that some of these markets will pay a great deal because it's high value, but there's not a lot of volume. You know, one of the things in the automotive business is everyone's always looking for big volume to drive a full manufacturing line. Bob alluded to it, but one of the strengths of our model is that our manufacturing line at Sanmina can be used for any industrial market, no matter how big or small, because all the customization for the high performance comes in the operating system after the manufacture of the hardware.
That's really the way we look at it, and Bob said, you know, quickly, and I caught it, but it also gives us the ability to actually, you know, take advantage of things faster. If ITS gets big legislation, there's a big uptick in people that want it, we can ramp up our volume using that line, or we can ramp down if there's any delay in that type of market. That's the way we look at industrial is that, there's a tremendous amount of different markets based on similar use cases, but they're all in our model, we're building the technology on one manufacturing line, and then we're using the software to add those capabilities in.
Great. Thank you for that. Maybe just to follow up on your new features, so nice to see the color there. I was just wondering, given that, particularly with the industrial market, given that, there's typically higher ASPs than maybe in auto and, what do you think about pricing considerations or gross margin considerations for these kind of new features? How does that fit into your long-term strategy? Maybe what other features, if you can give us any color, do you plan to roll out that can also be as expansive?
Sure. You bring up something that's you know a larger context in the business model of sensors, right? If you take a look at auto and you take a look at ADAS, a lot of the software is automotive-grade software, functionally safe and integrated with other systems, is done by the OEMs or by the Tier 1s. We're unique in the sense that we actually license software to our Tier 1 partners and we highlighted Continental, our lead customer. But you know, there's a limit on how much you can make on software using the traditional model where you're just selling a hardware product. Usually that's bundled in. We have a very different model. It's a very, you know, high-margin licensing model.
In the industrial markets, however, to your point, we think the markets are maybe smaller in hardware volume, but that there's a lot more value to be added, and therefore a lot more software margin to be gained if you can produce what they need to, again, either make it safer so my mine doesn't shut down, to make it more efficient so I can increase throughput, or to add a new feature so that I can actually do something I couldn't do before. I mean, at the end of the day, you have to look through the eyes of the customer. We actually believe that there's going to be more software opportunity in the industrial markets over the next couple years for us than maybe people would expect.
Great. Thank you. Maybe for my final question, so nice to see the progress with the B sample with Continental. Could you just walk us through the rest of the timeline, in terms of timing when you get the C sample and the other stages before production, over the next few years?
Sure. I mean, you and I know you're familiar with the automotive you know vernacular. It's tough. You know, some people talk about A, B, C, D, and but in reality, in the automotive industry, it's a very distinct, very formal and very structured process. This you know process for us our you know we transfer at B sample so that the industrialization can be done by Continental and their facilities, where they pick up all the costs of the manufacturing line, they pick up all the cost of the warranty and liability, and they pick up all the working capital. Our transfer point is the B sample.
Continental having, you know, shipped over 20 million LiDARs and 150 million radars, will move it into the C sample, and they will decide, you know, when they actually wanna launch, as part of their, as an individual offering or as part of a system offering to their installed base. We're in, you know, we've moved through, you know, B, we're transferring over and Continental will decide when they're in the C sample. We can't talk too much about, you know, their business because it is their product, other than we did allude to the fact that we believe that, you know, given the normal standards that 2023 is when the C sample will come out.
Got it. That's helpful. Thank you very much.
No, thank you.
The next question comes from John Roy of Water Tower Research. Please go ahead.
Thank you. Blair, I wanna talk about the Booz Allen deal just a little bit. I mean, obviously, you won that business. I was curious as to, you know, what were the key elements of the technology or the business, that allowed you to actually win that business?
Yeah. You know, I think it may seem counterintuitive, but it's really around data architecture, right? Whereas, you know, most people talk about the hardware, the acquisition of data first. Because Luis, when he designed the system, designed it from a military perspective, he designed the network and the software first and then how do you acquire it through, whether it's a LiDAR system or a combination of LiDAR and other sensors. I think that was refreshing and very attractive because in most Aerospace and military situations, they're actually trying to solve a problem first, which means it's about data. Most people, maybe you wouldn't put it this way, most people don't think about this, but at the end of the day, you can't be autonomous without making decisions. You can't make decisions without data.
We're really in the data business. Better spatial data faster. That's really, I believe, what impressed our partners at Booz Allen, because they're the experts at AI and machine learning. One of the challenges that they have, as they've said publicly before, is that a lot of times people are bringing them in to build out the system, but they have to deal with whatever data that's being put through the pipeline, and they can't change it. Well, with us, our system can actually, it's two-way communication, they can actually ask for the type of data that they want. It's much more impactful in their perception stack because we together can actually acquire and pre-process data in a way that makes it easier for AI and machine learning to add value to make decisions faster.
I think that's the first thing. I think the other thing is just that, you know, we're adaptive. I think that in the Aerospace and defense, there's very rarely a one-size-fits-all solution. The fact that we could give them a commercial off-the-shelf hardware system that had the kind of performance envelope they were looking for, yet they could customize in software and on the sensor, I think that was also very attractive. I think data and adaptability of the operating system.
Is this giving you a pretty big barrier to others getting into the market that Booz Allen Hamilton's going after with their own versions?
Look, again, I said this at the very beginning of the call and our philosophy, I think. Look, sensors are a heterogeneous environment. I think that there will be, you know, in places Aerospace and defense have been using sensors for a long time. I don't really look at it as defensibility as much as I look at it as value added. I think we have a unique opportunity to add value that maybe others aren't designed to add. That I think that will ultimately work with cameras and radars and infrared and other types of sensors in almost every application that we do in the defense area, because it just makes sense, you know.
Even if you take a look at human vision, 80% of human vision is actually pre-processed in the visual cortex at the edge of the network, and 40% of human vision is impacted heavily by other senses, touch, smell, sound, when you rotate and foveate. I think it's just, you know, if we wanna be better than humans, there's a lot to be learned from bio inspiration.
Maybe-
I just upset Bob. I upset Bob because I ended with philosophical, but I was able to get that in there right at the-
Yeah.
Right at the end.
Maybe one final question. The Aerospace and defense strategy that you have, I mean, obviously partnering is gonna be key. Can you give us any more color on what you're thinking is there?
Yeah. Well, I think that you look at these things that they're a mirror. In the consumer areas, we're trying to find, you know, detect, acquire, and make a decision on objects so that we're safer, right? I think that there's a direct analogy to that in defense, which is they have a different terminology. They call it find, and feel and fix, right? We're doing the same thing. We're trying to actually give computer systems the ability to find things, to acquire them, detect, acquire, and then to act on those. That's really, again, I'll say it again, the basis for autonomy is the correct data to make decisions without a human involved. That's the definition of autonomy, is the final sensor is not a human sensor to make the decision.
Our philosophy is to go out and give this adaptive platform to a bunch of people who need to solve that problem and let them help us help them.
Thank you very much.
All right. Well, thanks for the questions.
This concludes our question and answer session. I would like to turn the conference back over to Blair LaCorte for any closing remarks.
As always, thank you for those of you who joined us today. I think this was a record for our earnings call. I'm gonna give Clyde, our head of IR, you know, some kudos for that. As always, you know, thank you to all the employees who really made this possible. Bob and I are just actually out here to actually report. This presentation and the videos will be available on our website in our investor section. Thank you.
Thanks, everybody.
Conference is now concluded. Thank you for attending today's presentation, and you may now disconnect.