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spk10: Good morning. My name is Kirby, and I will be your conference operator today. At this time, I would like to welcome everyone to AI's third quarter 2021 earnings conference call and webcast. All participant lines have been placed in a listen-only mode, and opening remarks by AI management will be followed by a question-and-answer session. I will turn the call over to Steve Lambright, Chief Marketing Officer. Please go ahead.
spk03: Thanks, Kirby. And welcome, everyone, to AI's third quarter 2021 earnings call. With me today are Blair LaCourte, our chief executive officer, and Bob Brown, our chief financial officer. Earlier today, we announced our financial results for the third quarter 2021. A copy of the press release can be found on our website at investors.ai.ai. 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, uncertainty, and changes in circumstances that are difficult or impossible to predict. You can find more information about these risk uncertainties and other factors in our reports filed from time to time with the Securities and Exchange Commission, including the registration statement on Form S-4 that includes a definitive proxy statement that AI formerly known as CF Financial Acquisition Corp 3 filed with the SEC. Additional information will be sent forth in our quarterly report on Form 10-Q for the quarter ending September 30th, 2021. 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. All information discussed today will be as of November 11, 2021, 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 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. So let's start by quickly revisiting the day that brought us here.
spk04: We're here today to celebrate a great milestone, a testament to the vision and dedication of our team. AI was founded eight years ago based on a very simple concept, to create a computer vision platform that could make vehicles safer, more efficient, and enable true hands-off, eyes-off, autonomous features on demand. We uniquely set out to build that platform that leverages neuroscience, biomimicry and 80 years of military LIDAR knowledge to create the first commercial adaptive LIDAR platform. Today, we are pleased to say that these systems are in evaluation and deployed globally across numerous industries. That is a grand, grand achievement and just the beginning of what we believe will be a transformative era in the way we make vehicles smarter. I would like to thank my teammates who are not able to be here today. They are the engine that propels us, provides us innovation and creativity, and we are sustained by their dedication and commitment. AI is now LIDR, and we are dedicated to bringing positive returns to our investors and positive change to the world. Hello, everyone. My name is Blair LaCourte, and I am the CEO of AI. I am joined by my colleague, Bob Brown, our CFO and treasurer. I want to thank you for joining our first earnings call as a public company. We understand that as an investor, you invest both with your time and money. We realize both are limited and appreciate you prioritizing AI. We are grateful to have completed our D-SPAC as this was an important milestone and will help us accelerate adoption of AI's high-performance adaptive LiDAR system and fulfill our mission to make vehicles safer, more efficient, and to enable the next generation of autonomous mobility. Today, and on each quarterly earnings call going forward, we intend to follow a standard framework. First, we will provide you with an overview of key themes influencing the LIDAR market. Following that, we will provide an update on the business, including product, customer, and partner highlights. And finally, Bob will outline progress on strategic milestones, financial performance, and or outlook when appropriate. In conclusion, we will turn the floor over to you for your questions. With that said, let's get started. AI's next generation system is designed to leverage AI and edge processing to move the complexity from the hardware to the software, giving industrial customers and automotive OEMs the ability to add new and compelling features. This approach also enables a unique business model, with one platform addressing all markets, accelerating hardware cost reduction, and the use of partnerships to manufacture and sell in a more flexible manner. AI also has a great track record of innovation and leadership over the last eight years. Most recently, in 2020, we released our third generation of products, the Foresight series. We launched the Foresight A for ADAS and the Foresight M for industrial applications to a very positive response. 2021 has also been an exciting year. We completed our merger with CFAC and became a public company. We hit a milestone of filing more than 100 patents supporting our unique technology. And we continue to secure customer and third-party validation of our industry-leading performance with a 1,000-meter range in weather, scanning speeds of more than 20,000 hertz, and super high resolution of 1,600 points per degree squared, four times that of any of our competition. As this is our first call, we thought it was important to take a few minutes to articulate the technology vision AI was founded on in 2013, which was to build an AI-driven sensing platform that would perform better than the human visual cortex, not to simply build a standalone passive LIDAR sensor. We used lessons from biomimicry as well as lessons from the military's use of targeting and surveillance systems over the past 30 years. We developed three key technical principles to guide our base technology architecture, partnering strategy, and commercial model. First, we needed to rethink LiDAR hardware. We understood from our experience with radar and cameras that to really drive LiDAR adoption, it needed to be an intelligent, upgradable, and ultimately have a very steep cost reduction curve. We started with a transformational patented bi-static design, which is at the core of our adaptive capabilities. This allows us to parallel process information, increasing speed and accuracy, similar to a human eye's use of the visual cortex. We also knew that the ability to scale hardware production while reducing costs would require that our components be modular and be produced through standard, high-volume processes by world-class, automotive-grade Tier 2s. Second, we understood you need to have an intelligent software at the sensor level, which is a departure from the common approach of transferring raw detects to a separate perception software engine. LiDAR needs to enable functionality that cameras and radar could not, such as tracking fast-moving environments with small objects and lateral entries. This requires intelligent software on the sensor that substantially increases situational awareness and the probability of detection while reducing false positives without impacting swap C. Third, with these new hardware and software capabilities, we had to rethink the role of perception software within the autonomous vehicle stack. We understood that sending a perception engine more data wasn't the answer. Perception systems need the right information. Traditional passive LiDAR systems always oversample and undersample with every scene, especially in high speeds or variable weather. By delivering better quality information, we enable any perception engine to be faster and more accurate, whether it's AI's perception software or an in-house or third-party system. Our conclusion was that the world is dynamic. The way your vehicle senses should be as well. So why are our customers so excited? This adaptive sensing platform enables them to use our software to optimize a sensor for any placement in a vehicle from the grill, headlight, windshield, or roof. and to optimize the scan pattern for any use case or market requirement, from super long-range requirements of trucking and rail to more general scanning requirements for construction applications to very highly specialized scanning requirements for aerospace or intelligent traffic systems. Our partnership model, combined with our embedded SDK, uniquely enables Tier 1s and systems integrators to assist end users in this process if needed. We also intend to offer customers the ability to upgrade their software for different application needs. The Intelligent Sensor software platform can be broken down into four simple levels, each designed to meet the needs of specific use cases or applications. The first level we call design. It enables users to create a single deterministic scan pattern to deliver optimal information for any specific use case to address use cases such as highway autopilot or pedestrian detection in the city. The second level, triggered, has a set of scan patterns, each one addressing a specific use case. For example, a user can create a different scan pattern for highway, urban, and suburban driving. In addition, users can create scan patterns for those same driving environments, but optimized for bad weather. The design and trigger levels are ideal for ADAS applications. There are, however, two additional levels designed for industrial and mobility applications that are intended to be unlocked on demand. The first of these is responsive. With responsive, the entire platform is situationally aware, adjusting in real time how it scans the scene. In this level, system feedback loops and other sensors such as camera and radar inform the LIDAR. The highest level is predictive. Predictive understands the motion of everything it sees, which enables the system to deliver more information with less data, focusing its energy on the most important objects in a scene while paying attention to everything else in its periphery. Now, before we talk about specific customer highlights, let's step back and take one final look at how we uniquely approach the market in comparison to our peers. The combination of our unique hardware and software creates a high-performance LiDAR system that allows us to address multiple markets with the same platform. This creates a unique advantage against competitors who are unable to reconfigure the capabilities of the product to address the specific needs of each market. Another advantage of our model is that we can approach each market with an appropriate selling model. We can sell direct as we do in several industrial markets or through a licensing model with Tier 1s in the ADAS market. This gives us the flexibility as the markets mature to drive adoption of LIDAR. Now let's highlight a few of our partners and customers. As you may be aware, Continental, one of the world's largest automotive suppliers, has selected AI's LiDAR as their high-performance ADAS sensor to be implemented into its installed base of customers. This validation by Continental is critically important because Conti has been one of the leading global suppliers of ADAS solutions over the past 25 years. After an exhaustive two-year review of LiDAR technologies, Continental selected AI as its partner. Together, we announced that Conti will be shipping a long-range LiDAR product based on AI's technology to its automotive and trucking customers with volume production starting in 2024. I would like to mention this relationship goes well beyond licensing and manufacturing. We jointly and recently exhibited with Continental at the IAA conference in Munich and traveled thousands of miles on a roadshow across six countries where we reinforced key relationships with major OEMs with current or impending RFQs. For more on our work with Continental, let's hear from Gunnar Juergens, Continental's Vice President of LiDAR. Gunnar?
spk08: Thanks, Blair. I appreciate the opportunity to be here today. For those who aren't familiar with Continental, Continental is a 150-year-old company that today is one of the largest automotive technology companies in the world with currently more than 192,000 employees and an annual revenue of over 37 billion euros in 2020. We have a wide range of products in automotive, starting with mission-critical parts like tires and brakes, up to high-technology ones like the high-performance computers or ADAS sensors. Continental has been one of the world's leading suppliers of ADAS technology over the last decades, recently shipping our 100 millionth radar unit. In addition to radar, our 5,000-strong ADAS engineering team is working on the full ADAS system stack, including cameras, LIDARs, automated driving control units, ADAS software, as well as data management. What many people may not be aware is that we also have delivered more than 20 million LIDAR systems to more than 50 different vehicle models. We have a large ADAS market footprint with over 25 OEMs and 50 brands in our installed customer base. So with a history of more than 20 years in delivering LiDAR solutions to the automotive market, Continental is already uniquely positioned in the industry. But the next high priority for OEMs is to offer integrated ADAS systems that include a high-performance long-range LiDAR to address specific requirements for applications such as highway autopilot and hub-to-hub autonomous trucking. So we searched for the ideal technology partner to jointly develop such a new high-performance long-range LiDAR. We found AI, and we learned about our compatibility with regards to technology and market vision. We share common subsystems, suppliers, and design elements. And although the applications for our existing short-range flash LiDAR and the new long-range MEMS-based LiDAR with AI are different, they are complementary offerings that help us deliver our ultimate vision of a full-stack autonomous solution. Equally critical has been AI's willingness to license its platform so that we can utilize our manufacturing processes and purchasing power to create a truly differentiated continental product. We believe we are unique in our ability to bring an automotive-grade, high-performance, long-range LiDAR product to market at a competitive price and in large-scale production. Our teams are deeply integrated from our engineering processes through to our joint marketing materials and customer engagements. We have daily alignment meetings, we have quarterly executive offsites, shared IPT structures, and also resident engineers. We have successfully implemented all the mechanics necessary to bring a continental product to market based on AI's reference design. And today we are on schedule for delivering our product for SOP 2024 and we are producing B-samples of our production lines. Currently, we are jointly participating in numerous RFQ processes with major OEMs around the globe. The strong relationship between Continental and AI accelerates and de-risks development of our high-performance long-range LiDAR product. This product also extends and completes Continental's integrated ADAS system. As a standalone high-performance long-range Continental LiDAR, or as a part of our ADAS system, we are creating a compelling market position and a unique competitive advantage that strengthens our OEM relationships. OEMs value AI's unique high-performance technology in combination with Continental's proven ability to industrialize, manufacture, and deliver automotive-grade products in high volumes.
spk04: Thanks, Gunnar. Let's switch gears, excuse the pun, and talk about the industrial markets. Earlier this year, we announced a development partnership with global self-driving technology company 2Simple. 2Simple is working with numerous truck OEMs on hub-to-hub and ADAS applications, as well as level 4 self-driving trucks targeting production in 2024. TuSimple chose AI because of our system's extreme long-range performance, impressive weather capabilities, and the ability to address the most challenging autonomous trucking situations. It's widely believed that the trucking industry will be one of the early adopters of autonomous vehicles as a solution for driver shortages, fleet logistics, and safety concerns. We are also working with horizontal technology providers. Our partnership with NVIDIA is a great example of our efforts here. NVIDIA's DRIVE system is being used by many OEMs, mobility providers, and industrial companies as the foundation for their full-stack autonomous solutions. In July, AI and NVIDIA announced that AI will bring intelligent sensing to the DRIVE platform. With this integration, autonomous vehicle developers will have access to next-generation sensing capabilities as they build and deploy state-of-the-art autonomous applications with adaptive LiDAR. In 2021, we have also kicked off engagements with leaders in other industrial markets to develop solutions that address their specific needs. This includes Komatsu and construction and mining equipment and Hitachi Rail, to name a few. I would like to specifically highlight that in the third quarter, we launched AI's Foresight M into the intelligent transportation system market at the ITS World Congress in Hamburg. In the ITS market, working with the right partners is critical. In addition to our previously announced relationships with Econolite and Mitsubishi Electric, we announced a new and exciting partnership with Sol Robotics, a leading 3D perception company used in ITS applications, and Entetra, a pan-European ITS solution provider specializing in automated tolling solutions. Now let's look at how our Capital Light model works with manufacturing our products and leveraging our global value chain to drive innovation. As we heard from Gunnar, we have transitioned manufacturing of our ADAS product to Continental. They have begun producing automotive-grade B-samples of their HRL131 LiDAR system. For the industrial markets, we have also begun to move our manufacturing from our Advanced Development Center in Dublin to our contract manufacturing partner, Samina. In addition, we are expanding our Advanced Development Center at our Dublin, California headquarters and recently opened our Partner Innovation Center. By bringing together the resources and the talent that exists within our partner ecosystem, we expect to facilitate communication and collaboration and to accelerate innovation. Finally, together with our partner, Samina, we're building an industry-leading test facility, which will be available to our team and partners. This is expected to be operational in Q1 of 2022. We will continue to formalize these testing programs and share our results as we believe this transparency will help our customers better understand and appreciate the unique capabilities of our technology and our products. With that, I'll now turn the call over to Bob Brown, our CFO, to review our key business and financial milestones and third quarter financial results.
spk15: Bob? Thanks, Blair. I'll begin with a summary of our progress in executing on our strategic milestones during the quarter. Then I'll discuss our third quarter results. I'll start with our primary financial milestone, which was to complete our D-SPAC transaction in the third quarter. We successfully completed that in August by listing on NASDAQ as LIDR and raising over $200 million net of fees. We also eliminated over $50 million of outstanding debt at the closing of the transaction. With respect to product, we had a goal this year to clearly and measurably demonstrate the performance of AI's LiDAR. We succeeded in establishing LiDAR performance standards for range, speed, and resolution in third-party tests, and we also validated our superior weather performance. Manufacturing is another key milestone for us, and we made considerable progress there in the third quarter. Initial automotive B samples from the Continental line are in bring-up, and we are on schedule for automotive series production in 2024. We are also on track to begin production this quarter of our Foresight-M LiDAR sensor at Sanmina, our contract manufacturing partner. The Foresight-M will be used in our industrial and mobility applications. In the area of customers and partners, demonstrating commercial traction with leading players in the market is another key milestone for us in 2021. We're pleased to have advanced key relationships in the third quarter, including with Continental in ADAS, TuSimple in trucking, NVIDIA in mobility, Komatsu in construction, Hitachi in rail, and Mitsubishi Econolite in Tetra and Sol Robotics, all in support of our recent ITS launch. With respect to governance, our goal was to establish a strong public company board to represent our stockholders. We're pleased to have elected a new board of directors comprised of numerous highly respected board members and led by Carol DePetiste as chair. Scaling the company has been a key goal of AI for 2021. We substantially increased our key employee hires in engineering, operations, and sales and marketing to support our product rollout. As Blair will share later, our new hires include several key executive leaders across the company. In a competitive labor market, we're pleased to be attracting such high-caliber talent from across the LIDAR and automotive industries that will help us to execute on our growth plan. Innovation is critical to our success, and we have now filed over 100 patents for several groundbreaking concepts that should meaningfully expand AI's competitive position and protect our IP. So we've made a lot of progress against our strategic milestones for 2021, and we think that builds a strong foundation for us heading into 2022. Now let me touch on our third quarter financial results. Third quarter revenue of 0.1 million was down from the prior quarter, which included significant development contract revenue that did not reoccur in the third quarter. We expect to continue to see significant variability in our revenue quarter to quarter at this stage of AI's growth. Our gap net loss was $17.4 million for the quarter, or a loss of $0.15 per share. Non-gap net loss was $13.7 million, or a loss of $0.12 per share. And our adjusted EBITDA was a loss of $12.5 million. We raised approximately $200 million in net proceeds from our SPAC transaction in the third quarter, which we intend to use to fund investments in product development, increase scale, and support AI's growing customer base. We also eliminated over $50 million of debt as a result of closing the transaction, including repayment of our bank loans and the conversion of our convertible notes to equity. We closed the third quarter with a strong balance sheet, including $182 million of cash, cash equivalents, and marketable securities. For the third quarter, our weighted average share count was $114.9 million. As a result of the completion of our D-SPAC transaction, we now have approximately 155 million shares outstanding. For modeling purposes, as you think about our outlook, it's important to consider the following factors. We expect revenue from our industrial and mobility business to begin ramping over the course of 2022, but quarterly visibility is limited. We may also have additional development contract revenue in the future, but the amount and timing of that revenue is uncertain. Therefore, we plan to provide annual rather than quarterly guidance, and we will begin offering our 2022 outlook on our fourth quarter conference call in March. As a reminder, automotive LIDAR production by Continental using AI's technology is expected to start in 2024. It's also important to remember that our high-margin technology licensing model in the automotive market and contract manufacturing relationships in the industrial and mobility markets should minimize our capital expenditures and our working capital requirements. Finally, we expect that our operating expenses in the near term will continue to grow significantly as we make investments that support our goal of accelerating LiDAR with our high-performance intelligent LiDAR system. Our team executed well against our strategic milestones in the third quarter, and we look forward to reporting additional progress in the coming quarters. With that, I'll pass it back to Blair to share a short video and introduce some of our new executives.
spk04: Thanks, Bob. I'd like to wrap up with a look at AI's greatest asset, our people. We're building an amazing, talented, passionate team. As my dad would say, you have to bet on the people. During 2021, we made significant strides in attracting the top talent in the LiDAR market to AI. In March, we announced the appointment of Rick Toole as our Chief Operating Officer. Rick was previously the COO at Belladine. Rick has a demonstrated record of leadership and success in building and operating enterprise-scale technology businesses. In June, we announced the addition of Hod Finkelstein as our Chief R&D Officer. Previously, Hod was CTO at Sense Photonics, now a subsidiary of Ouster. Hod has led several organizations in the design and productization of disruptive technologies. In July, we announced the appointment of auto veteran Bernd Reithart to the role of Senior Vice President of ADAS. Bernd previously served as the Global Vice President for ADAS and LiDAR at Vallejo, having built their ADAS business over the past seven years. And just today, we announced the addition of T.R. Ramachandran in a newly created position as Chief Product Officer. T.R. was most recently the Head of Product Management and Marketing at Septon and formerly was the Vice President of Product Management at Velodyne. People who know LiDAR best are choosing AI. The number of exceptional individuals who have joined us this year from other LiDAR companies stands as a testimony to how we are received in the market. To conclude, we thought it would be inspiring for you to hear from some of our newest hires and the reasons for joining AI.
spk01: LiDAR is the mandatory sensor for high-end ADAS and autonomous driving. And it's very simple. AI has the best technology and performance to meet the market needs.
spk12: I wasn't aware of any other product on the market that was so adaptable in terms of scan patterns.
spk09: then also that range how they're able to achieve that range but also have this flexible system for multiple situations we depend on the software not the hardware so hardware is fixed and software we can change very quickly that is a really advantage for oem in the development progress.
spk11: AI was the only company with a unique model to leverage partners and licensing our technology out to those partners to then penetrate perfect type of products into each of those verticals.
spk05: The strength of the business model is the fact that we're able to leverage our automotive supply chain with our partner Continental into our industrial mobility markets. And it is unique to AI. And I think it's a tremendous strength that we have.
spk00: And AI's collaboration with Continental, where customers get AI technology with Continental's manufacturing quality and reliability and support infrastructure, it means that AI is one of a very small number of companies who don't just talk the talk, but can really walk the walk.
spk07: I joined AI because of the people, a lot of solid key people with knowledge of how to bring a product like LIDAR to the market.
spk13: Everybody's like awesome. They love working with each other. You can just feel the atmosphere and it's a collaborative and work environment. It's more of a family unit.
spk06: Everybody that works here is incredibly smart, incredibly driven and enthusiastic really about enabling our customers to change the world. It's a really amazing place to be.
spk04: I am confident that AI's team, along with a world-class board assembled as part of our public listing, will help us achieve our goal of driving LiDAR adoption across the automotive, industrial, and mobility markets. Now let's open it up for questions. Operator?
spk10: If you have any questions at this time, please press star, then the number one on your touchtone telephone. And if your question has been answered or you wish to remove yourself from the queue, you may press the pound key. And the first question comes from the line of Joseph Osha of Guggenheim Partners. Joseph, your line is now open.
spk02: Hello, everyone. Thanks for the detailed presentation. That was really interesting. A couple of questions. I wanted to start with this issue of procurement, in particular, if you look at what your main 1550 competitor has done, you know, in wide band gap detectors versus your strategy of saying what the you know, what the market sorted out. Can you explain to us a little bit how how you see your strategy being an advantage versus that sort of backward integration that that the other guys are pursuing?
spk04: Sure. So thanks for the question, Joe. You know, in every market, you know, there's different strategies. And I think this one is pretty clear. You can vertically integrate if you believe that the solution that you need has already been innovated on and it's in a mature phase. And all you're trying to do is actually to reduce costs with the same components. Or you may actually believe that you're an earlier market and you'd like to take advantage of an open supply chain, a modular supply tier two hardware supply chain that's doing a lot of R&D. We felt that our intelligence sensor system was better suited to a supply chain where we can actually, at any given time, as new technology starts to arrive, either from new materials or from a cost reduction standpoint, that we can integrate into our product seamlessly. So I think it's just a different strategy. You could vertically integrate, you're dependent on your own team, or you could have an open supply chain where you have proprietary designs with standard processes and take advantage of the innovation and size of the global automotive supply chain. And we picked the second.
spk02: That makes great, great sense. Could you talk a little bit about how you perceive the current opportunities in time of flight versus some of the early rhetoric out there about FMCW?
spk04: Sure. And you know, at first I'd like to say that we are not religious. about technology itself. What we are religious about is delivering a system to our customers that provide value. If we can't make our customers money and they can't provide value to their customers, then there is no market. So one of the premises, as you heard at the beginning of this presentation we came to, was that we would actually look at every technology out there and we would continue to evaluate as we went along. And so, you know, LiDAR has been around since 1962. FMCW has been around since 1963. You know, coherence in general is a very well-known concept. We picked what we believed was the most appropriate auto-grade technology today. And we also have a very, very different architecture, as we said, a bi-static architecture where we're separating the send and receive paths. So we actually can do things with our intelligence sensing platform that many other technologies can't. FMC is a continuous wave. We actually can pulse and change and create different patterns and collect different information using a time of flight system, whereas most passive time of flight systems can't do that. They work very much like a camera. They get the same density and the same distance everywhere in the scene. So I think this again was just a technology choice. We believe that if you're going to be in cars, in 2024 that you need a technology that is reliable, predictable, and that actually can be produced through an automotive grade supply chain. And we just, we didn't see the value of added coherence into the system today. Again, that said, we evaluate every year and our system is modular. If we decide we want to add some functions in, we'll add them in.
spk02: Great. Thank you. And then one more for me, and I'll quit monopolizing the call. Obviously, the relationship with Conti is very exciting. Might we see Conti start talking about who some of their end customers are for this product here? And if so, when might we expect to hear a bit more about that? Thanks.
spk04: Sure. Well, as you know, because you've been in the auto business for a while, most Tier 1s don't talk about who their OEMs are because the OEMs, until they get into volume production, see no value in actually talking about who the vendors are at that point in time. So what Continental has done is they've talked about their installed base of 25 OEMs, the 50 brands they work with. They have also talked about how many people were engaged with in RFQs today. But at the end of the day, Continental is our customer, and it will be their decision on when they actually decide to articulate who the specific OEMs are. It's a lot easier in smaller volume projects or in smaller brands to actually talk about things and take a risk on it. A lot of the projects we're working on right now are very, very large, and I would expect that Continental would wait until everything was tied up before they – they articulate them.
spk02: Okay, but just to follow on that before I go away here that it would be logical to assume that on the other part of the business where you're just you're working with contract manufacturers and selling selling completed units to your industrial customers that we would hear from you when you strike?
spk04: Absolutely. Our customers are the tier ones on the high volume business and we'll let them talk about their end user. But on the other side of the business where we're producing the hardware and the software ourselves and selling into the vertical markets with the caveat that we would always respect our customers and make sure that we got their permission, we have a lot more flexibility to talk about pilots and rollouts in those markets.
spk02: Okay. Thank you very much.
spk10: Next question comes from the line of Suji De Silva of Roth Capital. Suji, your line is now open.
spk14: Hi, Blair. Hi, Bob. So congrats on the SPAC merger close, obviously. So a few more questions on Continental. Since they already have done high-volume contracts, I'm wondering if they kind of have a line built out that you would leverage as you go forward, or do they have to build out a line in support of your B sample? Do you need a C sample to do that line build out? Just some color there on the remaining steps for Continental would be helpful to understand.
spk04: Sure. And as you alluded to, they have produced a tremendous amount of hardware products, including LiDAR in the past. Their process is to basically build out the sample line and then to actually build out the full line leveraging on that sample line. And that's what they've said publicly. And they are already producing the B samples as we speak today, as Gunar referenced in the project. One of the reasons that we partnered with them is because of their pragmatism and their reliability and their processes, quite honestly. While we are building product through contract manufacturers, The standards that a Continental will have, given that it's selling into a regulated market with high volumes and warranty and liability falls back to them, is much more sophisticated. And so they will be building out a custom line for these products that I'm not sure they've announced how big it is, so I won't step on their toes. But, you know, as you they are committed to not only building that line, but selling the volume off it.
spk14: And Blair, just to follow there, typically those lines are built to size, to committed customer volume, to giving you visibility. Is that a fair way to think about it?
spk04: Yes, but there is a minimum optimal line that you would build out. Again, I'm going to defer back to our partner out of respect, but what I would... expect in the industry is when you build out a line, you build out a high-volume line, and it's a large line.
spk14: Understood. I appreciate the sensitivity of the partner. And then the HRL 131 product you talk about here, and then also you talk about level 2 automation with the software stack and integration. When you have to provide products that are capable of L3 and beyond, Is that a software upgrade or do you need to have a reconfigured hardware module?
spk04: Right. So in the ADAS market, when we go to market in ADAS, whether it's level two or level three through our tier ones, including Continental, we will supply the software that allows them not only to decide how much they want to unlock, but it also is an open platform where it allows them to drop their algorithms and a lot of their IP onto our platform. That's why we call it a platform, so that they can customize it for their product and per OEM, given whatever the use case is or the specifications that they're trying to meet. So the embedded software license, will sit on the sensor, and the hardware will stay the same and be controlled by the different software permutations that they decide. So from one OEM to another, they may have the exact same hardware, which gives us scale, reduces cost, increases reliability, but they will adjust the edge-based intelligent sensor software And they have the capability, which I believe that they announced, I'm pretty sure, that they not only have the ability to now sell our product as a standalone, highway autopilot or hub-to-hub trucking, but they've already done the integration into their system with their cameras, their radars, and their control units. So when they go to a customer... they actually will ask the customer, would you like to buy an individual unit? Or would you like to have it integrated in part of a bigger system? We think that that was one of the reasons we thought other than the fact of manufacturing and industrialization and, and warranty and liability, we also felt like that was really a value to OEMs to be able to have a person come in because, you know, at the end of the day, a car is a smart asset. It's becoming much more of a system. And, you know, Continental has the capability to actually optimize that system per OEM.
spk14: Okay, that's very helpful color blur. I appreciate that. And then switching over to the non-automotive side, I know you have rail and industrial coming online, but also mobility. And you mentioned NVIDIA as a mobility partner, which I hadn't seen before. That was a channel for that. Do you have mobility wins, or have you announced any yet? Or what is the likelihood that comes in relatively soon? Because I know that market's pretty active for other LiDAR vendors. I'm wondering if you have a position there or whether we should not expect that nearer term.
spk04: No, it's actually something we've been working on for several years. We actually have just and are in process, obviously, with the transfer of a B sample to release the next generation of our product. So we will actually get that into production before we start to externalize the movement of pilots into into bigger opportunities. So as Bob said, you will see in 2022 that we'll be taking that contract manufacturer product into mobility and industrial, and I would expect that you would see some things later in 2022. But we are already engaged with, you know, part of being in a small industry and a very specialized industry like LIDAR, Look, on the ADAS side, there's 25 OEMs and 15 commercial truck companies and another 20 up-and-coming companies. There's not that many people. And when you talk about mobility, it's a very discrete market. So we've been working, as our peers have, we've all been working with these companies for a number of years.
spk14: Okay. Very helpful, ColorBlur. Thanks. Thanks.
spk10: Again, if you have any questions, please press star 1 on your telephone.
spk04: All right. I think that may be it for our call. So, listen, thank you, everyone, for dialing in. And, you know, it's a very exciting time in our marketplace. And the fact that we actually have such a robust set of companies here together, we believe we're all going to make each other better. Thank you for tuning into our first call. Thanks, everybody. Have a great day.
spk10: Thank you so much to our presenters and to everyone who participated. This concludes today's conference call. You may now disconnect. Have a great day.
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