AEye, Inc. Q2 FY2022 Earnings Call

Good afternoon, and welcome to AEye's Inc. Second Quarter 2022 Update Conference Call. All participants will be in a listen-only mode. After today's presentation, there will be an opportunity to ask questions. 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 second quarter 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 second quarter 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 ending 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 that 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 second quarter, 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 AI 4Sight platform in Q3. As always, our focus on execution remains paramount. Given the present global market and macro business environment instability, you'll see that we have proactively taken actions in Q2 to optimize schedules and modulate our spending. 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 in paramount is the release of both the AI 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 AI 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 startup 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-defined sensors allow AI 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've prepared 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've 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 license 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 AI'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-1 has transferred into production a licensed long-range lidar technology with the intention of delivering 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 ZoomCam. 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've received three points on an SUV at 300 meters; with ZoomCam enabled, we improved resolution on distant objects ahead and now received 19 points from the same SUV beyond 400 meters. This 6x 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 ZoomCam while in transit to detect track obstructions at extremely long ranges to allow adequate train stopping distance. In aerospace and defense, helicopters could utilize ZoomCam 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 SteadiCam. 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 are using our automated testing rig to move the sensor pitch to simulate varying road conditions. You will notice with SteadiCam 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, puddles or sloped roads. If we look at the same scene with SteadiCam 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 right on the horizon. When you look at the two outputs side-by-side, the importance of software-enabled SteadiCam 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 the 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. SteadiCam allows these autonomous industrial vehicles to easily navigate a constantly changing ground elevation, which impacts vehicle pitch. As we prepare to launch our new AI in Continental license 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 AI 4Sight intelligence 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 its 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, AI'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 AI's executive team, aerospace and defense. Our collective defense industry experience is encapsulated in our systems approach. AI's 4Sight sensors are uniquely capable of long-range detection, exceeding 3 kilometers with custom optics. Our flexible enough to track a bullet at greater than 20,000 frames per second and can either queue off of other sensors or self queue, adapting to place high-density regions of interest of up to 1,600 points per square degree around targets. These capabilities enabled by 4Sight in sensor perception greatly expand the utility of AI and machine learning for defense applications. Additionally, capabilities like ZoomCam and SteadiCam demonstrate why these customers are so excited. I would be remiss if I also did not mention at this point the capabilities enabled by a recently granted AI 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 when 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 the leader in data-driven artificial intelligence. In addition, we'll be integrating AI's 4Sight lidar platform to enhance Booz Allen's real-time embedded processor perception stack with high-quality spatial information, ultimately enabling their digital battle space 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'll 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 Frey, 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 second quarter 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're 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 second quarter, an increase of $1.4 million from the prior quarter, which relates to strategic investments to scale our team and advance our R&D in 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 second quarter, 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 second quarter with $125.8 million of cash, 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. So when you consider our cash, 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 third quarter. 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 third quarter to be in the range of $700,000 to $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 a range of $3 million to $4 million. In response to this uncertain environment, as we noted earlier, we have 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 a range of $90 million to $95 million, improving from $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 are 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.

Thank you, Bob. I want to close by thanking each AEye member for their impactful contributions for the 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 follow-up.

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?

Hi, Suji, it's Bob. Yes, I think what we're not going to give a longer-term outlook on today's call. So, we're going to continue to give annual guidance. But 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. This primarily relates to the industrial business here for Q3 and Q4. So that's the impact you are 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. So Blair may want to comment on the automotive side and the opportunities there.

Yes. 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 demand in the industrial markets we're seeing for those products.

Okay. Appreciate that color, Blair and Bob. And then you talked 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, if that can come in L2 plus L3, and what are the key features like SteadiCam that are going to be needed to make that something that the Tier 1s are comfortable implementing.

So, we've talked before so you know the kind of the 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 the use of orthogonal data for certain features. 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, or 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. So 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 going to miss it because you can't actually attach to the road surface at the longer distances.

You mentioned several markets in your prepared remarks. Can you provide an overview of the relative opportunity sizes for each of those markets? Additionally, which ones are expected to have a near-term revenue ramp? Could you 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. Therefore, you not only need to have a product, but you need to put it through functional safety testing. So, 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. And 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? So, that's the way the automotive market moves. So when you look across our sector today, the automotive market, the way you have to judge it is who's the performance of your product, who you're working with and where are you getting traction with 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 decent amount of time in the aerospace and defense and telecom business, we're talking about 60 years. But 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; some are 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. When considering the short-term outlook for industrial markets, we believe that intelligent transportation systems (ITS) have been expanding for several reasons. A notable development is the extensive implementation of cameras and radar in various applications, such as stoplights and toll roads. These systems offer significant value as either enhancements or replacements for existing solutions. Governments globally, including under the recent transportation bill in the United States, are allocating record amounts of funding to support these initiatives. Therefore, we anticipate a substantial growth in ITS within smart cities over the next few years as infrastructure is updated. The second market that we often talk about is 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 and 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. So, 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, whereas I said for the past 60 to 70 years, aerospace and defense has really used lidar. I think a new emerging market and aerospace defense is coming in which is really using commercial off-the-shelf products that are now reentering aerospace and defense. One of the things that we announced today, with our partnerships, is we're seeing great demand. I think that ultimately is probably in the near term may dwarf some of the other industrial markets just, because they've been using sensing systems. And quite honestly, if you saw Top Gun, you would've 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.

Thanks. It was really comprehensive. One last quick question, I'll pass along the optical communications technology talked about, is that applicable potentially for consumer V2X? Thanks.

This is a more complex question because each technology needs to be evaluated against what currently exists and what will be replaced. There is potential for it, but we believe it is more relevant in the short term for certain industrial markets. However, we wouldn't say it couldn't be applied to B2B, possibly even more for V2X. The industrial markets often have a closed-loop infrastructure, making implementation easier there. If we start seeing progress with V2X in industrial settings, it would be simpler to transition back to consumer markets.

The next question comes from Hans Chung of D. A. Davidson. Please go ahead.

Hi. Thank you for taking my question. So first, I wanted to follow up on the supply chain issue. Can you provide some color around the shortage? I think you mentioned a shortage in some components. I'm just wondering what kind of the component, is that some kind of chip or I don't know maybe laser or other stuff? And then 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 from?

Sure. I'll take the first part and let Bob address the second part of the question. The chip crisis continues to affect us, but I wouldn't say it is the primary issue we've been facing in recent months. Interestingly, it has been some very small components, like tiny connectors or minor parts that are essential to the system. Even though we've secured our main component suppliers, if all the required parts are not ready, we cannot complete the full assembly. I appreciate the question because while there are still challenges with chips, many of them could be resolved with pricing adjustments if necessary. However, the recent difficulties stem from these unexpected small components. One specific issue we spent significant time on involved a $2 part that was unavailable, which was surprising. Overall, we are likely to continue experiencing supply chain challenges for the foreseeable future due to the current climate. Nonetheless, we and the rest of the industry are finding ways to manage these issues. This last setback was largely due to unexpected minor components, rather than major ones, which caused some frustration in achieving final assembly.

Yes. So just to add to that, Hans, yes, I think Blair's exactly right. And so, we're doing our best to get those parts that we need as quickly as we can. We think we are going to 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. So, consequently, there is some risk there of course on the revenue side for Q3 with more of that revenue coming in later in the quarter. So we did contemplate that as part of the guidance we gave on revenue for the quarter of $700,000 to $900,000. So part of that range incorporates some risk around getting these parts as quickly as we'd like and actually getting into early production. So it has set us back both in terms of the production as well as some testing that we need to do on the products. We are working through all that expeditiously, and we think we will make some good progress against that in the quarter, but there does remain some risk there that we've got to work through.

Hans, as you review the calculations, you will see that this situation has likely set us back by two months. Considering Bob's comments on the importance of conducting testing early enough, we want to ensure we are confident in the product, the end-of-life processes, and the line calibration, as well as securing sufficient parts for the system. We don't believe this is a long-term structural issue; rather, it's something we anticipate managing at a low level moving forward. Like everyone else, we will need to mitigate the risks and plan accordingly.

And so, our next question is about the new aero defense business. So, is that kind of incremental opportunity based on the current 4Sight platform or is it sort of a new application or based on a new platform?

Right, it's not a new business for many of us in the Company. It wasn't seen as a significant part of our short-term plan because we were uncertain about how the product would be accepted. However, we've discovered that there's been much more demand than we anticipated.

Yes, I think we had always contemplated aero and defense as an opportunity, Hans, but we hadn't necessarily built that explicitly into 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 application. 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.

Yes. And to emphasize that I think part of your question was, this product will be coming off the Sanmina line, it was not going to be a new line; it's within the industrial. Now, there may be times in the future just like 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.

And then next, so recently one of your peers got a deal with the Volkswagen Group and it seems like kind of long-term a big deal. Would that imply that this kind of closes the door for you and Continental to Volkswagen or it's not necessarily?

No, I actually sent a note to congratulate them. They have a similar military background as we do. That deal was not something we participated in, and it actually happened before our partnership with Continental. In our model, we don't engage directly with automotive companies without a licensee, so we weren’t directly involved in that deal. Additionally, Volkswagen has several different radar, lidar, and camera systems. There’s been a preliminary selection for a certain application. We discussed this in the last call—the automotive industry is moving towards software-definable cars. This means they will have multiple sensors for various applications, allowing them to add value for consumers and charge for those services. We see this as a positive indication that these initial systems are being specified. There will be many more opportunities, not just with VW but with other OEM brands.

Got it. Okay. And one last quick, so will we be able to benefit from the recent CHIPS Act bill in some ways?

So let, first of all, we're a huge supporter of this because it drives innovation. 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. But we specifically see opportunities within our domain because we work with so many partners. We're an open system with modular hardware. So either with us working on design or with some of our partners. We think this is a good opportunity to accelerate innovation. Bob actually came from that industry; I don't know if you had any thoughts.

Yes, no. Our model 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. Therefore, we're going to 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.

The next question comes from Michael Mani of B. Riley. Please go ahead.

This is Michael Mani 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 AI'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 Greenfield opportunities are there like aerospace and defense, as you mentioned, is an emerging opportunity? And how do you think they're currently served or underserved and where does AI fit into that mix?

Sure. First, I want to emphasize that we analyze industrial markets based on value-driven use cases. While we categorize them into sectors like mining, agriculture, and aerospace and defense, there are specific applications for high-speed, high-performance sensors like lidar. Our approach in each market focuses on enhancing safety, boosting efficiency, and adding features that can generate more revenue. In terms of business models, some markets offer substantial payments due to their high value, but they typically have low volume. In the automotive sector, for instance, the priority is often on achieving large volumes to support full manufacturing lines. One advantage of our model is that our manufacturing line at Sanmina is adaptable for any industrial market, regardless of size. Customization for high performance occurs through the operating system after hardware production. This flexibility allows us to respond quickly; if there is significant legislation in ITS, we can increase our volume, or decrease it if there are market delays. We view the industrial landscape as comprising various markets with similar use cases, all supported by technology built on one manufacturing line, with software enabling additional capabilities.

Great, thank you for that. And maybe just a follow-up on your new features; it's nice to see the color there. I was just wondering, given that, particularly with the industrial market, given that there are typically higher ASPs and maybe in auto. What do you think about pricing considerations or gross margin considerations for these kind of new features? And how does that fit into your long-term strategy? And maybe what other features, if you can give us any color, do you plan to roll out that can also be standard expansive?

Sure. You bring up something that's 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 done by the OEMs or by the Tier 1s. So, we are unique in the sense that we actually license software to our Tier 1 partners, and we highlighted Continental, our lead customer. There is a limit on how much you can make on software using the traditional model where you are just selling a hardware product; usually, that's bundled in. Therefore, we have a very different model. It's a very 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 is 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 mind 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. 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 of years for us than maybe people would expect.

Great, thank you. And maybe for my final question, it's nice to see the progress with the B sample, the Continental. Could you just walk us through the rest of the timeline in terms of time you want to get the C sample and the other stages before production over the next few years?

Sure. I understand you're familiar with the automotive terminology. While some may refer to ABCD, in the automotive industry, it follows a very distinct and structured process. For us, we transfer at the B sample so that industrialization can be managed by Continental and their facilities, which cover all manufacturing line costs, warranty and liability costs, as well as working capital. Our transfer point is at the B sample, after which Continental will advance it to the C sample. They will determine when they want to launch it as part of their digital or system offerings to their existing customer base. We've completed the B phase and are transferring to Continental, who will decide when they reach the C sample. We can't disclose much about their operations since it's their product, but we have indicated that we expect the C sample to be released in 2023, following the usual timelines.

The next question comes from John Roy of Water Tower Research. Please go ahead.

So Blair, I want to talk about the Booz Allen deal just a little bit. I mean, obviously, you won that business. I was curious as to what were the key elements of the technology or the business that allowed you to actually win that business?

Yes, it might seem surprising, but it's fundamentally about data architecture. While most people focus on hardware and data acquisition, Louis designed the system from a military viewpoint, starting with the network and software. The acquisition methods, whether through lidar systems or other sensors, follow that. This approach was refreshing and appealing because, in most aerospace and military contexts, they begin by addressing a problem, which revolves around data. Ultimately, you cannot achieve autonomy without making decisions, and decisions rely on data. Therefore, our focus is on providing better spatial data more quickly. This impressed our partners at Booz Allen, who are experts in AI and machine learning. They've publicly stated that a common hurdle is that they often have to work with whatever data comes through, and they can't modify it. In contrast, our system allows for two-way communication, enabling them to request the specific data they need. This significantly enhances their perception stack, as we can jointly acquire and preprocess data in ways that facilitate faster decision-making in AI and machine learning. Additionally, our adaptability is crucial. In aerospace and defense, there's rarely a one-size-fits-all solution. Being able to offer a commercial off-the-shelf hardware system with the performance they need, while allowing for software and sensor customization, was also very appealing. So, I believe data and adaptability of the operating system are key.

So is this giving you a pretty big barrier to others getting into the market than Booz Allen's going after with their own versions?

I mentioned this at the start of the call and it's part of our philosophy. Sensors exist in a varied environment. Aerospace and defense sectors have utilized sensors for a long time. I don't see this as a matter of defensibility but as an opportunity for value addition. We have a distinctive chance to enhance value in ways that others may not be equipped to do. I believe we will integrate cameras, radars, infrared, and other sensors in almost all our defense applications because it’s logical. If you consider human vision, 80% of it is processed in the visual cortex, while 40% is influenced by other senses like touch, smell, and sound when adjusting focus. Therefore, to surpass human capability, there is much to learn from nature. I noted this philosophical aspect, but I was glad to include it at the end.

Maybe one final question. So, the aerospace and defense strategy that you have, I mean, obviously, partnering is going to be key. Can you give us any more color on what you're thinking in there?

Yes. Well, I think that this, you look at these things that they're a mirror in the consumer areas. We're trying to find, 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. So 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.

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'll give Clyde, our Head of IR, some kudos for that. And as always, thank you to all the employees who made this possible; Bob and I are just actually out here to report. This presentation and the videos will be available on our website in our Investor section. So thank you.

Thanks, everybody.

Conference is now concluded. Thank you for attending today’s presentation and you may now disconnect.