LIDR - NASDAQ

Good day, and welcome to the AEye's, Inc. First Quarter 2022 Results Conference Call. All participants will be in a listen-only mode. [Operator Instructions] After today's presentation, there will be an opportunity to ask questions. [Operator Instructions] Please note this event is being recorded. I would now like to turn the conference over to Clyde Montevirgen, VP of Investor Relations and Strategic Finance. Please go ahead.

Thanks and welcome everyone to AEye's first-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 first quarter of 2022. A copy of our press release can be found on our website at investors.aeye.aeye. Before we start, I'd like to remind participants that during this call, management may make Forward-looking statements, including without limitation, statements regarding our 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 these 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-K due for the period ending March 31, 2022. All information discussed today is as of May 13, 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 information 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 in 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 all for being here today and investing your time to participate in our quarterly update. As you have seen in our earnings release today, we finished our first quarter solidly meeting both our financial and operating expectations. In addition, we remain on track to achieve our full year plan. While we continue to follow external global events closely and monitor market volatility, our main investor themes and objectives for 2022 remain consistent and our focus on execution remains paramount. In our year end earnings call, we outlined our go forward strategy and our progress to date building product partnerships and infrastructure to meet our key objectives. We also spent time differentiating our unique business model and disruptive technology platform versus peers in our last call, you also had a chance to hear from several customers in the automotive and Industrial markets directly. They shared with us the value of the AEye intelligent sensing platform brings to their solutions. We would like to first emphasize the importance of 2022 as we intend to both begin shipping the 4Sight product for industrial markets with our partner Sanmina, as well as transferring the B-sample of our first joint automotive ADAS product to our partner Continental. In today's call we intend to do a quick review of the market dynamics. The differentiation of our disruptive intelligent sensing platform, and illustrate why we and our partners believe AEye sensor-based operating system is uniquely positioned to enable the evolution of smart vehicles, infrastructure, and assets. We will use the majority of our time today to focus on our execution with an update on the fourth key investment theme, commercialization, industrialization, and capital light manufacturing. We will touch on both the 4Sight product line, as well as our joint Continental ADAS product. We believe we will be the only company in our peer group to bring up volume production capabilities with multiple manufacturers. The market headline is sensors are a highly desired addition to many vehicles, infrastructure and other assets. Cameras and radars, our interpretive sensors with unique strengths and weaknesses, but have one attribute in common. They collect information and intelligently guess. Lidar is a deterministic sensor which can provide definitive data for many decisions, enabling new value-added features that can be standalone, like hub to hub trucking or highway autopilot for consumer vehicles, or Lidar can also complement radar and cameras to increase reliability or accuracy for existing features, such as in slower speed, traffic jam assist. What is clear is that Lidar's commercial performance has continued to increase substantially over the last several years. Concurrently, it's manufacturability is maturing and therefore size, weight, power, and costs continue to be optimized as Lidar is being applied across numerous industries. Many of us already have a Lidar sensor in our smartphones, Advanced Driver Assistance Systems in our cars, and we experience traffic flow optimization on toll roads and other parts of our infrastructure. We believe Lidar has a wide range of applications well beyond what most people have imagined. That said all Lidar are not the same. With many traditional Lidar systems, data is collected in a fixed and limited manner and then passed along to a perception engine. This is a one way flow from the sensor into an application software layer. AEye software on the edge is different. First, we can control hardware components individually, using a software-based operating system located on the sensor with two-way communication to change the way the sensor works, depending on different environments. In addition, the 4Sight operating system does not silo itself from other sensors. Customers can create unique systems that can use maps, cameras, radars, and IMUs to trigger the Lidar. So they can be more intelligent and efficient when collecting critical information. As recently demonstrated with Continentals, integration of its current Aedes suite, including radar and camera with our joint Lidar product. Finally, and most importantly, to software defined architecture is natively compatible to manage data over its local sensor network, and to be enabled for over the air updates. So we can change the way the hardware performs through software, allowing our customers in the future the ability to upgrade and new features and functionality. While this seems too good to be true, you only have to look to your smartphone to see the path that has already been taken by many durable goods manufacturers and infrastructure providers in automotive, specifically, the acceleration of EVs provides a natural greenfield opportunity to create. software definable platforms for cars. The future is now one powerful example of the software defined ability is adaptive placement. The 4Sight platform enables automotive OEMs to embed the same Lidar sensor and various integrated locations using AEye's proprietary sensing software. This optimizes performance for the vehicle specific packaging and integration without detracting from design or limiting performance. AEye's operating system provides OEMs with the ability to transform the sensor performance and enhanced data capture across various mounting locations and vehicles. This is in contrast to most traditional sensors today. Which cannot be optimized for placement tolerances and applications, making them sub-optimal across a platform with multiple brands and models. At the end of the day, the ability to change the mounting locations and the height, as well as correct for curvature and transmissivity of external surfaces allows us to increase platform adoption, optimize feature implementations, and reduce cost and complexity. This same adaptive placement capability and software definability conversely allows AEye to customize across markets. Along the use of the same hardware on a roof mount at four meters and a negative 40-degree angle on a Class A truck, as a grow mount at 65 centimeters and a negative 15-degree angle on a trendy sports car. Up until this point, we have been talking about how our adaptive systems can add intelligence into current vehicles, infrastructure, and assets. So let's take a step back and discuss the future and what differentiates the Software Defined Vehicle from a traditional vehicle today that has intelligence siloed in many subsystems. On the left, you see a vehicle with all of its technology and functionality set when you purchase it. In many cases, you would need to physically change or alter a component to adjust the hardware functionality of the vehicle. On the right, you see a vehicle with a more streamlined platform reference design, reducing complexity, and allowing for the flexibility to control the hardware more efficiently as part of an overall system. As we continue to advance cars with software, you will see systems begin to consolidate into software definable platforms with more connectivity both within and outside the vehicle with this added connectivity and distributed Intelligence within the vehicle, the opportunity to add value and increase revenue from software expanse. The AEye operating system model is architected to complement this migration, focus not on hardware alone, but on collecting the best data for decision making. Adding features to add safety and performance for the consumer and driving profitability for the OEM. For example, in the future, arrange sensor may trigger a rain performance mode or a camera may trigger a Lidar to confirm an object. This distributed intelligence is key for what we consider a software enabled vehicle in a recent reported was estimated a Tesla today makes 67% of his profits from these types of software enabled features. While our products already have the adaptability to be definable across multiple applications using the same hardware. The real power in the future, where cars may be driven for 10 years. Maybe the ability to continue to adapt overtime and update remotely using OTA and acronym for over the year updates. As an example, as new vehicles increased software content, OEMS, we'll be able to update software over the life of the vehicle, similar to have your phone gets updates today, vehicles will be able to send and receive data, enabling them to continuously increase in value. These updates will allow new features and functionality translating to improved safety and performance. As vehicles and infrastructure head towards over the year evolution, we believe our software-defined sensor will be a key enabler of these new business models. In summary, we believe the power of AEye's unique sensor platform is that is intended to be a set of hardware components that can be manufactured, then configured for any high value use case in the software. For instance, OEMs or Tier ones could use the sensors operating system to enable ADAS features that can be bundled for a range of consumer vehicles. The same operating system could be used by system integrators in the ITS or intelligent traffic systems market, who are able to optimize the sensor for pedestrian safety at intersections, or forecasting traffic flow on toll roads. Trucking can leverage high performance, high reliability sensors designed for first mile, last mile, or hub to hub applications. In the high demand rail and aviation markets each sensor can be optimized for the extreme range and the resolution they require. So let's talk about execution and our progress around commercialization and scalability. There's no better place to start than our latest product, the 4SightM, which we intend to transfer to volume production later this year. I would now like to introduce Tom Fallon, Executive Vice President of Strategic Business Development at Sanmina. Our 4Sight manufacturing partner. Take it away, Tom.

Thanks, Blair. Sanmina is one of the world's leading integrated manufacturing solutions provider. Headquartered in Silicon Valley with a global footprint, we have earned a reputation for innovation, reliability, and quality, with a passion for customer success. It is important to understand that we only win when our partners win, so we're very selective in where and when we invest in new processes and emerging companies. Each year, with our customers, we bring about 3,000 new products to market. So we are approached by a lot of companies. We proactively choose to partner with the companies where we see a mutual alignment around ideas and processes. We also look for a well-defined market opportunity that is large and rapidly approaching. With AEye, we found that alignment. We also found that AEye has a compelling vision and business model. We believe AEye's smart software-definable sensors will be a driving force in the automation of cars, infrastructure, and assets across many industries. At the core of our relationship with AEye, there are three fundamental pillars we have found important to increasing the probability of success. First, AEye decided early not to build a factory, but rather invest their time and resources in designing their systems for outsourced manufacturability, with an eye toward optimizing efficiency and cost without compromising on industry-leading performance and reliability. Second, AEye's innovative approach of aligning component suppliers with their reference system design, utilizing modular component source for improving automotive grade suppliers not only allows accelerated innovation, but also was a tremendous advantage in helping us to scale and harden our global supply chain. We believe this approach creates a strategic differentiation from others by optimizing time-to-market volume, quality, and cost. Third, AEye has transferred much of the system complexity from hardware to the software layer and it's unique sensor-based operating system. We don't usually see companies make that leap until four or five generally of product release cycles. This allows one manufacturing line to produce the sensor hardware at scale in software-as used to customize the sensor per market or partner, and to enable continuous enhancements in functionality over time. Most importantly, AEye and Sanmina have worked as one team from the beginning. We have leveraged these other strengths to develop integrated design, manufacturing, and testing processes that will bring the AEye 4Sight Lidar systems to market faster and with greater reliability and performance. Sanmina believes that what we make makes a difference, we're very proud of our partnership with AEye. Back to you, Blair.

Thanks, Tom. Earlier this year we mentioned the convergence of our components across markets and the focus on shared volumes and cost reduction to drive adoption. Tom also referenced our joint efforts to design for manufacturing, reliability and the power of converged supply chains. One example of this collaboration we would like to share for the first time publicly is how this effort drove advancements in our MEMS components. Custom designed and built around standard industry processes for manufacturability. The small dot in the center of the chip on this picture is our micro MEMS, significantly smaller, faster, and more adaptable than any we have seen in commercial production. Proving that record breaking performance indeed does come in small packages. Another concrete example of how AEye and Sanmina are innovating together is our new joint calibration and testing facilities located on Sanmina's San Jose campus is a perfect compliment to AEye's indoor range and doubling. Industrialization and reliability are at the core of any successful path to scale and highly regulated and mission critical systems. This large, dedicated state of the art facility not only allows us to do environmental and performance testing, but also to bring customers and integration partners into an immersive and flexible testing environment. This jointly developed facility gives us tremendous flexibility and validating the performance of our 4Sight sensors. Working with Sanmina and our end-user customers, we have developed a rigorous testing methodologies that help us fine tune the performance of our sensors and a wide variety of use cases and applications. You can see in our video, our ability to quickly reconfigure the operation to run customer-driven test this week. From small object detection at speed or rider down motorcycle scenario, intersection, pedestrian safety, too much larger applications for acquisition and countermeasures in the Aerospace and defense markets. In addition to our extensive in-house testing with Sanmina, we have extended domain specific testing resources by partnering with some of the largest Tier one automotive suppliers in the world. In this process, we're exposed to their world-class processes, including environmental standards, product validation, functional safety and performance benchmarking. This has led us to collaboratively working with some of them most influential and respected third-party testing groups in the world. We have also taken the unique step of releasing these results when appropriate to the public. As an example, we work closely with VSI, a leading independent researcher of active safety and automated vehicle technologies to validate the performance of our light for AEye's applications. We do this at locations such as the American center for mobility, where we were able to test and independently verify the ability of our products to perform. In this VSI designed, produced, and verify testing scenario, we were able to detect very small objects such as brick set long range, in inclement weather while inside a tunnel. On top of that, we're demonstrating these capabilities with our Lidar looking through windshield glass, opening yet another unique placement opportunity not available to most traditional Time-of-Flight Lidars. We have progressed on plan and are executing on track and on time with our development, testing and transition to production later this year. I will now turn things over to Bob Brown, our CFO, to discuss our financial update.

Thanks, Blair, and good afternoon, everyone. I'd like to discuss our financial performance for Q1 and our near-term outlook. Revenue in the first quarter of $1.1 million was up 229% over the first quarter of 2021. The top line growth largely reflects an increase in development contract revenues, as we complete work with key partners, as well as higher prototype sales relative to the prior year. As we've discussed previously, the sizable percentage of our revenue is driven by one of the largest Tier 1 automotive suppliers in the world, which is a strong validation of our technology and strategy. GAAP, Operating Expenditure of $24.5 million in the first quarter rose $14.1 million from the first quarter of last year. As we've continued down the path to commercial production over the last year, we scaled our team and spending to support that progress, as well as to support the infrastructure required as a public company. Our non-GAAP Operating Expenditure were $19.2 million in the first quarter, which excludes $5.3 million in stock based compensation expense. Net loss was $24.9 million on a GAAP basis and GAAP EPS was a loss of $0.16. Net loss on a non-GAAP basis was $19.5 million in Q1 and non-GAAP EPS was a loss of $0.13. Net cash used in operating activities for the quarter was $16 million and our CapEx was less than $1 million. We'll continue to manage our cash carefully going forward, and our team is managing to a strict budget. The vast majority of our spending is focused on R&D, operations, and sales and marketing, with the goal of scaling our business as efficiently as possible. We exited the quarter with $144 million of cash, cash equivalents, and marketable securities on our balance sheet. When we include up to $125 million of potential proceeds from our Common Stock Purchase Agreement, we believe our total available liquidity of $269 million provides us with a sound financial base to execute on our strategy. We anticipate there we'll begin accessing the Common Stock Purchase Agreement this year. While we're on the balance sheet, I wanted to note that we adopted the new lease accounting standard, ASC 842, in Q1. As a result, you'll notice increases in right-of-use assets and operating lease liabilities. These amounts are primarily related to our office lease obligations. It's exciting to see how we've grown over the last few years from an R&D -focused entity into a commercial operation. We're starting to reap the benefits of our capital-light strategy by focusing our time, effort, and money on our core competencies and the activities that will extend our technological lead while getting our products to market faster. We're executing our plan to develop products for both the Automotive and Industrial segments based on the same revolutionary architecture. This is key because unlike most of our competitors, we don't need to develop different products for different applications. We will use one software to find architecture for all applications across all end markets. We expect that this strategy will provide us with economies of scale and improve our margins as we grow the business relative to our near term outlook, we expect revenues in the second quarter to be about $700,000 as we wind down prototype sales in preparation for the ramp of the commercial version of our 4Sight end product in Q3. So combined with the Q1 performance, our revenue for the first half of the year in total should be slightly ahead of expectations. As we mentioned on our call last quarter, we expect to see revenue growth in the second half of this year as manufacturing of our commercial product starts to ramp at Sanmina. We expect that growth in the second half will enable us to deliver on our revenue goal of $4 million to $6 million for the full year. We continue to expect a non-GAAP net loss of approximately $100 million for 2022. I'm pleased with our team's performance in Q1 and we're tracking to our plan. We continue to execute well against our strategic milestones, and we look forward to sharing further progress against our financial, commercial, and technical objectives in the coming quarters. With that, I'll pass it back to Blair to wrap things up before we open the line for questions.

Thank you, Bob. Want to close as we always do with our talented and culture. We're fortunate that we continue to attract the brightest minds in the industry. This includes our global advisory board. We started our advisory board very early in our history and has been a valuable resource for us as we have built our business, we expect the latest additions to continue to be a vital part of AEye. Let me introduce you to a few new members. Marcus Lipinski, our [Indiscernible] and Dr. Erlich Weinman. Marcus was most recently the Managing Director at Aptive, a global automotive tier one supplier. Previously he had been a leading executive that VW, MAN trucks, and Daimler. He has a history of delivering digital innovation in both the automotive and software industries. Erl has been an executive at [Indiscernible], now, Qualcomm and Autoliv to leading Tier-1 suppliers, where he led global teams focusing on active safety solutions. Erl brings a breadth of high performance business operations and sales strategy to the team. And finally, Dr. Wyman has extensive knowledge in the OEM space, predominantly as global SVP at Harman and COO at Alpine Electronics, as well as Senior Executive at BMW. We welcome you all to AEye and look forward to working together. Culture is a powerful force, and I would like to share with you today an employee-driven initiative that we are very proud of. Over the last two years, we have partnered with Richard Branson and Virgin Galactic, Virgin Orbit, and Virgin Hyperloop to bring together our technologists and engineers to explore the future of transportation. Part of this exploration has been to look at how we invest in the future and share this knowledge with the next generation. One key element of this has been the development of the BLAST program. BLAST stands for Black Leaders in Aerospace Scholarship and Training. By providing mentoring and internships, BLAST aspires to change the funnel by creating a village with a network of support that helps black students find connections and opportunities. This program has also changed AEye. In the process of mentoring, we learn, and we become inspired. I can honestly say this program has been a significant value-add to our culture and to our effectiveness. We hope BLAST is also an example of how AEye serves as a role model within our industry, and as a leader in providing opportunities to talented minorities pursuing a career in engineering and technology. Looking forward, I want to first thank the team for all their hard work, as we've been busy this quarter setting ourselves up for the rest of 2022 and setting the stage to scale in 2023. As we mentioned at the beginning of the call, the world is changing quickly. As a company we're staying focused on the things we can control and leveraging tight relationships and the community of our employees and our partners. During this call, we discussed our software platform and how we're implementing disruptive intelligent sensing. We also talked about how we have made significant progress in delivering cost and scalability efficiencies by utilizing a capital light business model. Finally, I'd like to reiterate, but Bob stated in our financial review, we are on track to deliver our 2022 guidance. I want to again, thank everyone who joined the call today. Operator, let's move over to Q&A

[Operator Instruction]. Our first question comes from Suji Desilva with ROTH Capital. Please go ahead.

By Blair. Hi, Bob. Congratulations with progress here. So the you talked about Blair in the prepared remarks, the B-sample transferring to county. I'm wondering what that entails in terms of it moving to county for you guys. And also has county been in addressing OEM, RFPs, RFQs ahead of the B-sample transfer or is that kind of want to things that's happened before that. Those are our fees get addressing.

Sure, thanks Suji. The transfer of the B-sample is a little bit misleading in the sense that as we've said on earlier calls and you've heard from [Indiscernible] directly. We've actually integrated our team's completely, we actually have residents -- engineers and residents at both unit. So we've been working jointly from the beginning of the HRL designed to now, when we use the term transfer, we talk about the transferred a single-stock, where we have sample lines in the U.S. and we're kicking up the sample lines in Germany, which again puts more of the emphasis on the. testing and functional safety concerns that [Indiscernible] is more responsible for. But we work on the product jointly today and we'll continue until the product shifts and beyond in support. And as far as customers go -- yes, we've been working and I think we've said in other calls, and I don't know the exact number so I will give a range, but there's somewhere between 15 and 17 RFPs, RFQs that we have been jointly working on as you know from your experience in the industry. People want to see engineering samples, they want to see B-sample, and they want to input in what they want to see before you close out the C-sample. In addition, we spend a lot of time in R&D projects with the same, say, 25 to 27, both automotive and trucking OEMS looking at the next-generation and getting them attuned to what is possible out there. So we're -- our sales teams are tightly integrated on and in fact we have functional twins all over the world, as well as an individual set of priorities by region.

Okay, great.

Both of the questions.

No, it did, Blair great job and I just wanted to stand as we see auto OEMS commit to the AEye Lidar, how would we become aware of those wins and what do think the time frame is from this point forward as to those sort of announcement just awareness of those wins being secured.

Sure, I know there's been a lot of I talked at least there was last year about flop forward looking order book and we talked about that in every executive, meaning that we have. But for the automotive market, that is our partners the Tier ones we work with, specifically the one that is moving to manufacturing first is Continental so they will make the decision on when they announce. As you know, the tradition in the automotive industry for radar and Lidar. The other Lidars that have been before this, as well as cameras have been to wait, closer to the SOP. I think that we'll be talking about it much sooner just because the tradition has started to morph, as there's been more talk out there. Continental will be in charge of talking about their industrial automotive. In the industrial markets however, in the second half of the year we will start as we are the direct sales arm, we will start to talk about those wins much sooner.

Great. And I look forward to the industrial announcement that's going to help drive second half revenue, as you said. One last question on the Industrial side. Great to have the Sanmina Executive on to help with getting insight there. What was it about your tech, the way you approach the technology, software, and hardware that allows you to leverage high-volume proven components, which obviously is something Sanmina like to by you guys a lot? Other Lidar guys we know are using some more exotic components. So if you could talk about how the software is allowing you to pull that off, that would help us understand some of your differentiation.

I think having spent enough time with him, I'll -- I will try to tell you what we heard from them was that we made a decision very early that we would move from being an R&D company to a high-volume production company because we believe although this has taking a while for LiDAR to come to commercialization, that the curve will be much faster. I've said in the past that it took 15 years, really, for extreme penetration for radar into almost everything and it took about 11 years for cameras. We think that that curve is on track to be less than five or six years, which is at light speed. If you believe that then you would want to get out of what R&D companies do, which is vertical integration, exotic design, and building your own factories where you have to spend time on tooling that you then would have to get rid of it there's an advancement in the technology. We decided early on that we would design for manufacturability, and that we would use custom designs, but standard component processes. So one of the things we've been doing over the last three years is working with the largest component suppliers, Tier-2 suppliers, as they say in automotive, in the world and convincing them that they can build our designs using their standard lines, which then brings down costs and increases volume across the different types of components. So that's when we talk about this, when we talk about our relationship with Sanmina, they really appreciate this as the final manufacturer because they're dealing with not only Tier-2's who already have standard processes but Tier-2's that are already automotive grade compatible.

Okay, great. Thanks, Blair. Appreciate it, thanks, guys.

Thanks Suji.

The next question comes from Joseph Osha with Guggenheim Partners.

Hello, everybody, Happy Friday.

Thanks Joe you too.

A couple of questions. First, Bob, I'm just wondering if you can just talk us through a little bit of the cadence of the burn as you work through the rest of the year here. And where I'm headed with this is that given your relatively modest burn so far and the amount of cash and equivalents you've got, it -- I'm surprised that you're tapping the equity facility this year. It seems like you've got some breathing room there that would not require you to do that. So I'm wondering if that's just belt and suspenders being careful, or the message there is that the burn is going to go up as the year progresses. Thanks. And I have a couple other ones.

Yes, we do expect the OpEx to go up a bit this year. So, for modeling purposes, I'd assume the non-GAAP OpEx will probably increase on the order of about 15% per quarter sequentially, so I would probably build it out that way in terms of modeling. But to your point, the burn has been fairly modest. We don't have to tap the common stock purchase agreement, we don't want to. That said, there may be some advantage to doing some dollar cost averaging over time and just using fairly moderate basis. We've got 11 quarters left to utilize that facility so if you can do the math on that and we've got a $125 million facility. That's a little over $11 million per quarter, so it's not a huge amount by any means, if you were to average it out over those 11 quarters, so we're expecting to obviously look at the volumes, look at market conditions, and then decide how much will actually do each quarter. But the idea is to be fairly moderate about it over time.

Yeah. I think Joe, you also hit on one of our cultural imperatives, which is there's a lot of ambiguity in the world, and if you take a look back to last year, what we raised the largest pipe because we wanted to offset the possibility that redemption's would go up and that actually did happen. We also actually executed the E-lock on the heels of our IPO, probably a year before most people would have done it and that was again, I think credit to Bob's conservatism. We got a great partner and we got tremendously good terms on that, so I would say that this is more us taking a look at how to be prudent and how to be pragmatic. We don't intend to at least do anything that would be radical surprising or would be detrimental to investor value.

Okay, Thank you that's interesting. Second question, that relates to the ramp of 4Sight, right. And so obviously it's an early stage product, but as you point out, this is being done in the high volume fulfill the with commercially available products into it. So I would think that on that basis, we'd begin to get a fairly early on kind of one aside as to what gross margin for that part of the business might look like. Can you understand the insight into how we might think about that?

Yes, we probably have more to say about that next quarter's call Joe, so we're expecting to get some early production here in Q2 these will be more samples in Q2, so we'll get some initial volume we think coming out of Sanmina later this quarter. But then the ramp you say really starts to happen in Q3. So we'll probably provide a little bit more color on that when we have our next earnings call, which I believe is in August.

If I asked them in a different way, I mean, understand you get perhaps you can't discuss the numbers per say now, but would it be logical to assume that gets to some acceptable gross margin reasonably quickly because it's this combination of the capital light approach and focused on off-the-shelf input.

Yeah. We'll start making progress on gross margins certainly, we think, because we've been selling prototypes up till now, so we're expecting some improvement over time. Exactly what that's going to look like, we'll, as I said, share more in the coming quarters. But I think for the year, we're probably still looking at negative gross margins overall for 2022 is probably the way to think about it. And then as we scale it up, it will improve in, certainly, the future years as we start to get more scale with it. But it'll still be relevantly modest volumes for 2022 as we ramp it up, and we are doing the proof-of-concept deployments with customers. So we've got to get the product in their hands and get them testing it before we get widespread deployment. So the volumes will still be fairly modest for 2022. So you don't get the -- this full value out of the leverage yet, but we think we'll start to see that in '23 and beyond.

And I know you've done a lot of research on this, dug into the models before. The way that I think about it is in the automotive markets where we're getting a standard licensing fee we know from the beginning of the contract without any risk, what our margins are going to be? In the industrial markets where we are selling direct, we have 2 variables. One is a positive variable where you don't have to wait for SOP, functional safety testing and then SOP. We can go from pilot in 3 to 6 months to more of a production roll out in those markets. That's one thing is we've got to get through the pilots to figure out how it's going to be deployed. The second piece, as we've talked about before, is that we believe that in the ADAS market there's not a lot of room for add-on software. As I think many people have alluded, they may be able to get to. Our opinion is that once these contracts are set, there's not a lot of room for add-on. We're happy to get our licensing fee, which is a different model. But in the industrial market, we're also looking at building on top of that operating system. It's much easier for us now that we have an operating system on the sensor to build out custom software applications. Or you'd look it in your iPhone as app. So we don't know how that's going to play out and how fast that will play out. That could as well impact product margins over time. But I would, as we've been conservative and again, pragmatic in the past, this is the early stages of roll out in this year, and I would agree with Bob, we're not expecting to optimize on gross margins. We're out there to get customers to use the product, show value, and build opportunities to do production roll outs?

Okay. Thanks. I understand that's useful color, and then the third and final question would be, with regards to kind of platform vision, you articulated it, I can't remember which slide it was showing the two different sort of vehicle platform visions, which is something that I hardly agree with and you and I have spoken about, but it does imply that at some point there needs to be a fairly high level of engagement with whatever large semiconductor company you think is providing that big, powerful compute platform. How do you think about that? Can we see you make an announcement or form some kind of venture with an Intel or Broadcom or Qualcomm or something like that?

I think you're 100% right on, I think that at the end of the day, as we've talked about in the past, this is ultimately value hardware margins are tightened over time as we get more efficient software verticalizes. And ultimately the data into the network is were a lot of value is added and decision-making and autonomy it's even more specific. You can't get to autonomy without good data to make decisions. And I believe that anyone in this space will have to have a data platform strategy with these compute platforms, because I think they're going to enable us. Now, EVs are going to help them enable us, but they're already -- there's over -- in some cars, over a 100 ECUs today, even if we move to the platform, we will simplify it but there's still going to be a lot that has to do with data optimization and compute power. And you can expect us and I think any of the other leading companies in our space, we're providing data into that system to after work closely with them to make the system work. So we think we have an advantage in that we have an operating system on the sensor which has two-way communication. We've been ratifying and talking to these types of people that they appreciate that they see it as a network addition. But at the end of the day, there'll be multiple types of implementations, whether it's. point sensors, passively sending information, or active sensors that are pre -processing or integrating information across it. But I think your thesis is correct. Is that over the next two to five years, we're building new compute platforms. They just happened in some cases, drive around and drop-off the kids at soccer.

Right. Thanks. I'll jump back in queue.

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

Hi, Blair. Thank you for taking my questions, so few questions. So first, just from your perspective, are there any potential technology or capacity constraints on the supply chain. For example, maybe it's laser, receivers, scanner, etc just how to get a sense that we have to identity maybe 1 or 2 factors, like potentially using more challenges, regarding [Indiscernible], l mean proceed to volume per taxing on auto side? Just wondering here, any comment.

Sure. And I appreciate the question. You actually brought this up last time and I thought it was appropriate, Stephen, more appropriate today. I'll answer it two ways. One is, because we have the same thought you do, we spend a lot of time working the key components, we talk about the fact that we have -- really and our system is -- you can drive cost down in three ways, right? One is simplicity of system design, the second is in adding new materials, innovations, and the third is in volume production, right? So when you look at our system design, there's really only four components, and some people would say three, I mean you have a laser that sends out the energy, you have a scanner that -- and in fact, in our case we have an adaptive scanner, that actually interrogates an environment, and then you have a receiver which receives information. We've spent a tremendous amount of time trying to secure those supply chains and make sure that we wouldn't have any disruption in the short-term. But what I would say is that it's amazing. Some -- when you're building a system, sometimes it's only one small component which you didn't consider a large piece that can trip you up. So I'd say most of our -- well we've spent a lot of time on the big components. It's amazing. Every couple of weeks, you'll find out that some small piece of the puzzle is built in Shanghai, And then it's closed down and we have to go to our secondary source. So today we feel good about what's happening with our supply. I should good as a relative term, we feel confident that we've done what we can do for our supply chain. But I'd say that this isn't going away over the next couple of years and it's forced us to be -- to take a much wider lens of what is inventory management. And when you get to the full assembly, everything has to be there at the same time. So there's the short version of that. If I wasn't getting paid by the word Bob, Bob, pays me by the work, but the short answer is, we think we have a good focus on the main components. But I'd tell you we're still shaking out while we haven't moved into the next phase. We're still finding things that we hadn't expected and we're moving stuff around to fix it and I think that's going to be indicative of many of our peers, and just many of the people in tech in general. But it's great question.

Got it, that's fair. So next question, just yet interestingly, just you pointed out, you highlight managed technology in the slides. Actually you just curious to be, can you elaborate more on these, I think is MEMs scanner. And what's the differentiators for your technology? And maybe talking you can address the point of cloud density or the scan, maybe something like that, and they just curious that.

Sure.

How your technology?

You've got me on one of my passion subject, so I will try to actually, it's difficult being Italian to be succinct but I'm going to try. So Luiz original design came from the top down. He was designing a network software to pull in data and it just happened that in a lot of cases you need hardware to actually acquire that data. So in Luiz original model, he wanted to be a modular hardware. So as innovative happen, you can plug in, play the wavelength, can change the anything in the model can change because hardware changes over time. And that's something that he and I both saw over the years in telecommunications and in the military. But just as important as that insight, I think was Luiz's insight for adaptability, so the by static design of our product where you, where you separate the send and receive versus having it be coaxial and their hard wired together is actually a legacy of the same design, which is let's design from the network information model down. So since we separate versus putting the 2 together, we actually have a extremely flexible send component. So our MEMS are, in some cases 250 times smaller than many of what other people call MAMS. We call them micro OEMS or micro MEMS, so they are very small and they are not actually hardwired to the receive, which means that in most cases when someone says we can see longer distances than anyone in the world and how could that be the laws of Physics haven't changed. The laws of Physics may not have changed, but the laws of mechanical orientation are still open. And so we don't have to wait for the light to come back with our receiver when we send it out so we can move very quickly. That's how we can go longer distances and we can also get greater density because if you take a look I am not an engineer, although I've spent most of my career working with engineers. So my apologies upfront for the simplicity of this answer is, though size of the MEMS is so small that the inertia allows us to move in ways that no one else could move their maps. A single pair of MEMS, we actually, I'm not a lot of to say exactly how fast we move them. But as you saw us track a bullet which will start to the impossible. Everywhere we're well over 20,000 hurts, right? So we can go anywhere from 10 hurts to 20 over -- 20,000 hurts in speed. We can go and we're going to be showing in August. I think we'll be showing some implementations of this operating system. We've already announced that we can go over a kilometer and I think in some cases alluded much further than that, and in density, density is determined by how close they actually points hit and how you actually segment and acquire an object so that you know what the object is. With the MEMS that we have, we can change the pattern on the fly inside of frame, so it all depends on what kind of density we want. The trade-off is always speed, distance and density and what we do with our adaptive system is when we place it on a truck that's higher, and we have a certainly use case, we will optimize every strike for that unique packaging placement application, right. And so I can tell you the extremes of how what we can do. We think we've set the world record in every in speed, in density and in distance. But again, what really matters in a network is you get the information that a computer needs to make a decision, that's going to be better than a human. And that's the definite definition of automation. So the micro MEMS is an absolutely important part, but so is the fact that a receiver is separated and that actually has a capability to track in a very, very unique way. In some ways, a lot like cmos camera. So I hope that answer your question. I wasn't wondering in it, but the ability to have this kind of MEMs, this small kind of MEMs that we don't believe anyone else in the world has is a huge advantage in adaptability and intelligence.

Yeah. That's definitely very helpful. And a quick follow-up. So is manufacturing, the process, technology on the macro segment mature or it's also new?

As we've said, we may have custom designs, but we actually try to stay within standard processes to help our suppliers and to drive down our costs. So in any way we can, we always drive to existing standard processes for manufacturing.

Got it. Got it. And last question, just regarding the equity purchase agreement. So I know you just mentioned just probably just moderately do this over time. But do you have any guideline? Do you have any price flow, like you won't to do this and then -- or -- because I think for this year, you probably don't need the clarity on this. And -- but just curious how you think about the strategy or tactics here regarding how you want to do? And then do you have any -- do you have a color, I won't do more than X amount, something like that? Just any color.

Yeah. We do internally have some of those metrics, nothing that we're going to share at this point, but we're going to be very thoughtful as Blair said about how we use it. So we're not going to want to put undue pressure on the stock as as we use, of course, so we're going to be very thoughtful about how we approach it. So as we said, it's about $11 million per quarter, over 11 quarters. If you average it out and some quarters will certainly be below that, and some quarters we will might be above that, and the differentiation there is really going to come from both the trading volume of our stock and the market overall, as well as general market conditions, so that's how we're going to approach it. So we're not going to have specific table that we're going to lay out for folks on how we're going to use it, so we expect to be nimble with it and thoughtful about how we use it.

Right, and you know, I have to invoke my father every time I get a chance. But look, at the end of the day there is some ambiguity but the answer to ambiguity is probably not going to be certainty, it will be trust and what Bob saying to you is our philosophy is do no harm, but also be pragmatic and conservative and smart about how to run a business that we believe will be here for a long time. So that's our commitment is we're going to be smart and I hope you won't be surprised by anything you do. I hope you'll look back and say that was stocks.

Got it, Okay thank you guys.

Great. Thank you Hans.

Good question comes from Andres Sheppard with Cantor Fitzgerald. Please go ahead.

Good afternoon, guys and congrats on the quarter and thanks for squeezing me in here and I know we're about about time. Most of the good questions have been asked already, but maybe just to take a step back. I was curious if you could remind us again on the strategy in terms of both short term and long term. And by that I mean, in terms of your target markets. Do you anticipate, do you kind of prioritize the automobile sector which will ramp up over the next few years or is the strategy, maybe in the short term to pursue and target some non automobile markets while the automobile ramps up? Thank you.

The answer is yes. I know we spent a little bit of time talking the other day. I appreciate the question because I think a lot of people want to -- actually many of our peers are focused in one place or another. If you think about how we're focused on network information, where we can actually optimize our product using software, using the same manufacturing lines in the same hardware components. So what we believe is something that we had to do and why this year is so critical for us is we believe that we had to have the components and the manufacturing capabilities ready in both markets. Because in the automotive market, while you're point is well taken, you will not see the SOPS for a few years. Upto this point there has been pilots, but you will see over the next two years, the most of the OEMS actually committed. So we have to have a product that they can look at with Conti, and that they can trust and say, this is not automotive grade this has reliability, this has the right cost profile you have manufacturing setup. I mean, most people don't realize even to get to a million units, it's about a $150 million line with tooling and $250 million in working capital and then warranty and liability. So for us, our model is we don't have any of those costs, right? We basically get a royalty on every unit that goes off, but we have very tight partners in Tier 1's and Continental who will handle that. So we are in the automotive markets, I think someone earlier asked how many RFPs and RFQs are out there. Almost every company is actually investigating over the next 2 years to committing to programs. Now they're spread out over highway autopilot, hub to hub trucking and maybe some traffic control but they are all engaged that LiDAR is a way for them to actually add value and therefore make some more money. Now on the other side, it's a tale of a very different market. When you take a look at some of the industrial markets, they have actually used LiDAR. It's a little bit bimodal they have used it in mapping in the past and they've also used it for highly specialized application, so for instance, in a mine, in the dark trying to see through dust and trying to be able to be more efficient and push throughput. Now, in those markets, what's interesting is the turn cycles are faster, you don't have to wait for functional safety. They truly appreciate that you're using automotive grade components, because the industrial market shocked by reliability has been the major issue with the LiDAR systems in the past, but they're actually trying to focus on how to actually deploy systems that make money within the next year. So if you look at ITS, the largest amount of money that's ever been put in a transportation bill is now embedded in smart cities and ITS. So we believe those markets are going to happen and they're going to happen sooner. And I think as Suji maybe referenced, we need to be ready with Sanmina so that we can roll full, complete products off the line that could be implemented and be in use for three years to five years, because in many of the ITS applications, the installation is just as expensive as the actual sensor itself. So what they appreciate about us is that our automotive focus has led us to high-quality reliability, and the ability to have an operating system on the sensor allows you to upgrade infrastructure over time. And almost every intersection out there today in a major city actually already had some Cameron radar. And the ability to actually look at data holistically and how we can use that is appreciated. So when I say yes, it's -- good news, bad news as the Chinese curves says, who's to say, we believe that both markets are engaging right now. We're just going to market a different way. In Automotive, we're going through large Tier 1s like Continental, and we're in the processes, and in Industrial, we're working with systems integrators and we're helping -- and we're selling side-by-side direct, a fully-manufactured product through Sanmina. Did that make sense?

Yes that's wonderful [Indiscernible], I appreciate all of that infor, very helpful. Maybe one last quick follow-up for me. This is maybe more directed towards Bob, but looking at the the liquidity, so a $144 million in cash plus the $125 million in the CSPA is the thought now that, that should be sufficient to, again, to go through that ramp-up period in terms of being fully funded or do you maybe anticipate additional capital races in the next few years? Thank you.

I think for now we feel good about where we are and liquidity and where we are with our plan. We're not going to give long term projections on the call today. So we're going to stick with just our annual guidance and updating that. But we feel good about where we are as you said, from our liquidity position, we've got quite a bit of cash on the balance sheet and access to the common stock purchase agreement. So we feel that puts us in a very good position today. And as we said, we're going to be thoughtful and careful about how we deploy our OpEx going forward and also how we use our common stock purchase agreement to access that additional liquidity as we needed. But we feel very good that we've got a sound liquidity base to execute the strategy from. So for now that's what we feel like we need.

And Bob's not lottery spending money, and he keeps cutting me out from being able to pay for lunch, he's got a very focused strategy on liquidity.

That's excellent. Well, thank you so much, congrats on the quarter. l'll pass it on, thank you.

Thanks, Andres.

Our next question comes from John Roy with Water Tower Research. Please go ahead.

Thank you. So Blair, obviously you've been talking a lot about 2 different markets and you've been building this product, you really want make a reliable, scalable, industrialize. And it seems like you expect some cross pollination from the to manufacturers. Can you go into how you expect those 2 to work together or not? And is this part of your business model differentiation, will you be able to leverage that?

Sure. Thanks. We did -- we touched on this very slightly the last call. But what we are doing right now, we had originally had a sequential product roll-out where we were rolling out the industrial products, and then we're rolling out in 2022 the automotive products, and then we were coming with a refresh where we converge both products in 2023. The last call, we announced that we would be accelerating that and beginning to merge the products. So to your question what that means is, the software, the operating system is being built out and hardened so that it can handle both markets, and it can be triggered by individual sensors in each market. Each market has their own individual sensors that they depend on. The second piece is that I think we're -- I don't want to misquote it because I don't have the exact number, but I think over 80% of the components are the same in this set of releases, which again reduces our complexity, increases our reliability, simplifies our design and, ultimately, we believe should actually reduce costs because you're using the same components and increasing volume on those components. It may even be higher than that, but I'd say, conservatively, it's about 80%. When you look at the difference in our presentation of the size of the products, and then you harken back to looking at that tiny little MEMS and a tiny little receiver on a chip, The difference in size is really how we've optimized the boards. There's a lot of air in those products because of the industrial space, they actually don't mind having a little bit more size, right? Whereas in the automotive product, when you try to package it in the grill or on the roof or behind the windshield, size does matter and that's really what we believe is the key to our business model is that it was designed from the beginning to be software operating system focus, so that we can -- I think Joe brought up so we can work better with the compute platforms and that we can actually use the same hardware components across multiple markets. And as we said in the Sanmina piece, use one manufacturing line and then optimize and customize per market in the software.

That's really helpful. The AEye percent number is interesting. Now, also you've certainly talked a lot about software definability. The on sensor, OS, etc. We're starting to hear others use the software definable Lidar term, maybe you could just give us a little bit of differentiation between what you mean by that and what maybe others might mean by that. How is your software going to really be that different? I understand it controls a hardware understanding by static but maybe if you can give us more of a Layman's explanation as to, okay, this is what it really means to the end-user.

Sure, again it would be hubris for me to get inside other people's minds and pretend that I understand exactly what they're saying, what I would proposition is that if you're a hardware focus product, you use software defined ability sometimes to do configuration, right? And so you can change some small things in the hardware at design or implementation. You can't -- there's a few levers, not a lot. What we mean by software definability and why we use the term operating system on a sensor is that we actually built from the software down so that every single component is individually controlled. So I can change the way the laser works without touching the receiver. Now, why would that be important while I can change the field of view? If in a certain application or certain mounting situation I don't have to put in a different piece of hardware to get a larger field of view or smaller field of view, I can change it in the software, or I may be able to actually change the way that I do density. So while I'm actually scanning across, I may actually decide that we'll actually acquire objects, which means putting more points on them within the same frame to articulate them and pass that on to the external perception engines. Or I may decide to take an input from an outside outside sensor, which if it's raining, maybe I'm going to push it from 2 returns to 4 returns, maybe I'll be at 6 returns, which means up push through experience, and take the returns after they pass through. All of those are attributes of -- if software defined ability that you needed operating system to do. They're not configuration, they're actually customization and optimization with the ability to have 2 way communication between different system. So I think that we all realize in our industry that humans are very good at intelligent scanning when they're moving that's why 92% of accidents or caused by distraction, not because humans are not good at scanning their environment. But what we have to do, I believe, to take humans out, which is what really automation is, is we need to be 10 times better than a human and that doesn't just mean not getting distracted. It means being intelligently scan better than they can, and that means trading off temporal scanning and spatial scanning in the same frame. If you can do that in a functionally safe way, you have added a tremendous amount of value. Consumers will love it, OEMS will love it and if you've already bought an asset in the industrial space, you're safety and I will go up overnight. So we always have to look through to the end. We're not building technology for technology sake, we're building technology that can acquire data to make decisions. And that's why again, we have software definable, but we also are software definable with an operating system. And that's the track we're taking. There will be -- and I'll finish with where I started again. There will be multiple types of Lidar systems in the world, just like there's multiple cameras and there's multiple radar systems. Our goal is to build intelligent LiDAR systems and they have their niche and we believe they'll have a great value. And the key for us is getting through this year so that we can start to scale and get it in customers hands so that next year you'll be asking us very, very customer specific questions because you'll have the feedback

Great. Thank you so much.

Thanks.

Thanks John. Alright. I think that wraps up our Q&A session. Operator, I think we're going to end the call at this point. Thank you all for joining us and we hope you all have a great weekend. Thanks so much.