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Operator
Good afternoon, and welcome to the AI Inc. 3rd Quarter 2022 Earnings Conference Call. All participants will be in listen-only mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star, then one on your telephone keypad. To withdraw your question, please press star, then two. Please note, this event is being recorded. I would now like to turn the conference over to Clyde Montevergan, Vice President of IR and Strategic Finance. Please go ahead.
Clyde Montevergan
Good afternoon, and thank you for joining AI's third quarter 2022 earnings call. With me are Blair LaCourte, Director and Chief Executive Officer, and Bob Brown, Chief Financial Officer. We will also hear from Louis Desson, AI's co-founder and chief technology officer, to celebrate a significant company milestone with the official launch of our groundbreaking Foresight Adaptive LiDAR platform. Earlier today, we announced our financial results for the third quarter 2022. A copy of our press release can be found on our website at investors.ai.ai. Before we begin, I would like to remind participants that today's discussion may include forward-looking statements as defined by United States securities laws in connection with the future events, future operating results, or financial performance. 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-Q for the period ending September 30, 2022. All information discussed today is as of November 10, 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 the 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. Let me now pass it over to Louis.
Blair LaCourte
This is a targeting pod that is used on almost every U.S. and NATO aircraft today. It is a multimillion-dollar system that includes advanced state-of-the-art sensing technologies and real-time data analysis software. I helped design it. I also designed this, the AI Foresight M. Almost 10 years ago, I started with a white sheet of paper and the vision to bring some of these cutting edge military spec capabilities of the targeting pod to vehicles of all shapes and sizes to enable safer and more efficient transportation. AI is now bringing that vision for a safer future to life. We took the complexity out of the hardware and moved it to the software. creating an operating system on the sensor. This enables us to create an intelligent sensing platform that delivers incredible flexibility, reliability, and performance. The Foresight M for automated tolling speeds up traffic at what before was a bottleneck, reduces emissions, and maintenance costs. The Foresight M is providing automatic incident detection on freeways. radically improving safety, reducing accidents, and improving highway throughput. The Foresight M is detecting obstacles and wires in the blind spots for helicopter pilots, saving lives. This same technology is also now available in an HRL 131 production intent B sample from Continental. It's currently in pre-development design programs with leading automotive OEM ADAS systems and autonomous trucking platforms. And now we can deliver this technology at scale. AI's Foresight M is being built by our partner, Sammina. And with our products in hand, We can help provide a safer and more efficient future for all of us.
Blair
Thank you, Louis, and congratulations to the entire AI team and our partners on achieving this important milestone. Let me begin today with three thoughts to frame our presentation. First, some feedback from the market. We see an accelerated demand for information to help automate processes that increase safety and or drive productivity gains. This demand transcends terms such as software-defined cars, intelligent infrastructure, smart assets, and network-based defense systems, to name a few. It is also finally accepted as fact that LiDAR will be an impactful player in the sensor market, providing unique deterministic data in high-performance and high-risk automation environments. second some feedback from our partners and customers ai's newly launched foresight platform with its superior performance and intelligence rocks technology adoption has clear patterns hardware will need to become a platform to become more adaptable and intelligent to expand market opportunities and to reduce per unit costs software is an excellent way to customize features to verticals and leveraging a sensor-based operating system to transform data into information is where the real value is created. As Louis outlined earlier, we took a different approach and one that is designed to add value in this paradigm. Our goal is to show you what we believe is the next generation of software-driven adaptive LiDAR that will greatly enhance autonomous systems, and where this launch is here today. Finally, we know our investors need a compelling investment thesis. If you believe that automation and autonomous systems are the next major advancement in technology, and you believe that intelligent LiDAR will be a key enabler, the only question would be why not lean forward now? Our answer comes in a very old quote. If the basis of your investment approach is to buy great companies at low prices, we have a great presentation for you today. AI's foresight platform is game-changing across all markets, but particularly in areas where speed and distance matter, such as in hub-to-hub trucking and true high-speed highway autopilot for automotive, the two most requested features from OEMs and their customers. As you can see, the industry and customers are recognizing that AI is delivering the only high-performance, software-defined, adaptive system in the market today. Our goal for 2022 was not only to build capabilities, but to actually launch our industrialized product for scale distribution in 2023. In our last quarterly call, we took you to the Continental Ingolstock facility and the Semina San Jose pilot line and test facility. Today, we are announcing that we have broken ground for our low-cost, high-velocity manufacturing line at Seminole's future plant in Thailand. This commitment from our partners to build out high-volume and low-cost manufacturing capabilities ensures automotive-grade industrialization and reliability. We believe AI is the only LiDAR supplier to have two manufacturing partners and a capital-light business model. Today's agenda is focused on the successful execution of our 2022 plan. Bob will update you on our financial performance. I will return and do a quick refresher on what is unique about our technology and the launch of our new product platform. Then I will finish with a summary of our progress in our key markets. We will conclude and open up the call for questions. Bob?
Louis
Thanks Blair. Good afternoon everyone. I'd like to discuss our third quarter financial performance, our strategic financial management in this challenging macro environment, and then speak briefly on our outlook for the balance of the year. To begin, I wanted to address some of the questions we've gotten about our stock price. As you see on this slide, we're now experiencing some of the most bearish U.S. investor sentiment in the market since 2009. For those that believe in contrarian indicators, this could present an interesting opportunity. We believe the impact we're seeing on our stock price is predominantly related to overall market sentiment rather than something company-specific. We've seen particularly negative sentiment around growth stocks given the dramatic rise in interest rates coupled with a potential recession looming. We'll continue to focus on improving our shareholder value over time by controlling what we can, which is executing well on our product development goals and on our business plan. Revenue in the third quarter was $768,000, which was slightly above consensus estimate and up 9% from the prior quarter. We saw a significant increase in LiDAR sensor sales in the third quarter on both a sequential and year-over-year basis as we moved from engineering samples to production quality units. This reflected the initial ramp of our Foresight M product in the industrial market. We generated revenue from software licenses in the industrial market in the third quarter, which takes advantage of our unique adaptive capabilities and enables our customers to more effectively deploy our sensors for application-specific use cases, such as road tolling and intersection management. Our development contract services revenue was down in the third quarter due to variations in contract-specific activity, but we expect that category to grow in the fourth quarter. We've been managing our spending carefully throughout the year, given the slowing economy and ongoing market volatility. Gap operating expenses were $21.3 million in the third quarter, a decrease of $4.6 million from the prior quarter. The improvement quarter over quarter reflects lower accrued payroll, stock-based compensation costs, and general and administrative costs. Our non-GAAP operating expenses were $15.1 million in the third quarter, down from $19.1 million in the second quarter. Net loss in the third quarter was $23.6 million on a GAAP basis, improving by $2.8 million from the second quarter. Gap EPS was a loss of 15 cents per share in the third quarter or an improvement of 2 cents per share from the second quarter. Net loss on a non-gap basis was $17 million, and non-gap EPS was a loss of 11 cents or 5 cents better than the consensus estimate for the third quarter and an improvement of 2 cents per share from the second quarter. Net cash used in operating activities for the quarter was $22.4 million, which increased $5.3 million from the prior quarter. This increase in cash usage in the quarter was driven by annual prepaid insurance costs that were paid in the third quarter and working capital associated with our production ramp. We're continuing to manage our cash very carefully in this environment, and we're focusing our cash outlays on critical areas that clearly support our strategy and product ramp. Our capital expenditures in the quarter were modest at $1.6 million, reflecting our unique Capital Light business model and the partnerships with manufacturers like Continental and Sanmina. We exited the second quarter with $112.2 million of cash, cash equivalents, and marketable securities on our balance sheet. We issued a convertible note in September, which provided us with $10 million of net proceeds. We have the right, subject to certain conditions, to issue another convertible note to the same investor in 2023 in the same amount and on the same terms. Our cash balance also includes $1.5 million in gross proceeds during the quarter from issuing shares under our $125 million common stock purchase agreement, which now has up to $122.1 million of potential proceeds remaining, but is subject to a limitation of 29.7 million shares remaining that we can issue under this agreement. So, when you consider our cash, cash equivalents, and marketable securities, together with the potential proceeds from our remaining common stock purchase agreement, we have total available liquidity of up to approximately $244 million, assuming that we can fully utilize the capacity under the common stock purchase agreement and issue the second tranche of our convertible note. We believe that provides us with a solid financial base to support our growing business as we head into what's expected to be a challenging economic climate in 2023. Overall, we continue to improve our products and market position in the third quarter with solid execution across the board. We're emerging as a scalable, product-focused commercial operation with a unique capital A business model. We think that keeps us nimble and allows us to respond to customers and market conditions quickly. Let me now turn to our near term outlook, we expect to see modest revenue growth in the near term as manufacturing of our commercial product begins to ramp up at Samina for the industrial market establishing our ability to scale volumes further in 2023. The supply chain challenges we articulated during last quarter's call still remain, but we were successful in meeting our production goals for the third quarter due to strong execution by our employees. We're maintaining a cautious view on the fourth quarter outlook in this macro environment. We expect our revenue for the fourth quarter to be approximately $1 million. The production ramp of our industrial product, the Foresight M, is on track, although we do expect the global supply chain challenges are going to be with us for a while longer. In response to this uncertain environment, as we noted earlier, we have been managing our spending carefully while still enabling growth in 2023. However, our operating expenses were unusually low in the third quarter, and we expect operating expenses in the fourth quarter to be similar to the levels we saw in the first and second quarters of this year. We now expect our full-year net loss on a non-GAAP basis, excluding stock-based compensation expense and certain other items, to be in the range of $80 million to $85 million, improving from the $100 million non-GAAP net loss we guided to at the beginning of the year, and also improving from the updated guidance for a non-GAAP net loss of $90 to $95 million that we provided last quarter. We expect our capital expenditures to be approximately $2 million in Q4. Let me conclude by saying that while we expect to see the impacts of a potential recession and ongoing supply chain disruptions in the near term, we have an experienced team to manage through those challenges and we are managing our spending accordingly. Meanwhile, the secular backdrop for LiDAR adoption across the automotive market with Continental's HRL 131 and industrial markets with the newly launched Foresight M product remains compelling in our view. The feedback we're getting from OEM customers on Continental's automotive production intent B sample is very encouraging, and we're excited to have our new Foresight M product available to our industrial customers now. We're looking forward to the opportunities in front of us as we approach 2023. With that, I'll turn the call back to Blair.
Blair
Thank you, Bob. So let me take a few minutes to explain how this launch of our Foresight platform and unique product architecture is providing groundbreaking performance and system capabilities that our customers have been requesting. The majority of commercial LiDAR companies today are building hardware-centric, static LiDAR sensors, passively transmitting raw detection data to other software systems to then process. Much like the original Motorola StarTAC flip phone, this analog approach allows for collection and transmission of data, but no intelligence. As Louis explained, we took a fundamentally different approach. First, we can control the 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 AI Foresight platform does not silo itself from the other sensors like our peers, allowing our customers to create unique systems that can use maps, cameras, radar, and IMUs to trigger our LiDAR so they can be more intelligent and efficient when collecting critical information. Finally, and most importantly, our software-defined architecture is natively compatible to manage data over its local sensor network and to be enabled for over-the-air updates perfect for this new era of software-defined vehicles, intelligent infrastructure, and smart assets. In our last call, we announced that we had patented the ability to add optical communication to this network and enable applications in smart infrastructure, as well as compartmentalize industrial sites and unique aerospace and defense scenarios where other communication modes are not practical or require secondary channel. Today, we will announce another industry first, enabling perception data to now be processed and triggered in the cloud. As we will demonstrate later, this native network architecture extension opens up enormous capabilities for our customers. While this seems too good to be true, you only have to look at your smartphone to see the logic and potential to move from an analog serial processing approach to a digital parallel processing network design. But more on that later. With the launch of our groundbreaking Foresight platform this quarter, we are accelerating our progress in automotive and trucking. Together with Continental, one of the world's top three automotive technology providers, and our lead automotive customer and licensee, AI participated in the IAA commercial vehicle show recently in Germany. This show is one of the world's largest events dedicated to commercial vehicles and trucking. We took this opportunity to preview our production intent automotive product that you saw earlier in Louie's official launch video. As you can see, we were featured as a cornerstone of Continental's booth and our platform has been integrated with their sensor suite, including radar, camera, and perception software. In addition, AI was featured prominently in Continental's Class 8 truck demo in front of the venue. A true show of force. AI and Continental were also excited to be named LiDAR Product of the Year for the HRL 131 by a distinguished panel of automotive industry leaders at AutoSense. AutoSense is the world's leading community for advanced driver assistance systems and autonomous vehicle technology development. We were also encouraged by the strong positive momentum we see. This product line is setting new standards in range, resolution, refresh rate, and intelligence. One question we have heard prior to this call was, how are customers testing your products today? Our current B samples produced at Continental's Ingolstock facility are production intent, which means they only need to be put through design validation testing. This allows our OEMs to do their own internal validation and conduct field operation testing on vehicles with existing pre-production units. Then the design is scaled with production tooling to meet the high-volume customer demand. Another question we have heard from investors was in regard to customer evaluation and RFQs, which has been, how are your joint engagements with OEMs progressing, and when will you disclose Continental's commercial partners? AI and Continental have been engaged with OEMs for over two years in evaluations, RFIs, and now we are in the final phase of multiple RFQ processes. We began distribution of our latest production intense samples in Q3 to get feedback on our fit and performance. we have had substantial and very positive technical feedback from OEMs. In fact, we have been told by numerous OEMs we have the highest performing LiDAR solution and that they appreciate our business model that reduces their production risk by leveraging Continental for automotive industrialization and manufacturing. It has been imperative that we stayed on schedule in 2022 as we believe that multiple customer awards are on the horizon. We reiterate today that we are still actively engaged in more than six RFQs with Continental. Our sensor's high performance uniquely enables desirable features such as automated hub-to-hub trucking and highway autopilot. As OEMs transition from initial pilots to higher functionality features at high speeds, we continue to be down-selected for our superior performance metrics and partnership with Continental. While the industry has seen some delays in 2022, to the best of our knowledge, no potential programs have been canceled, only delayed. We do not believe that we have lost any production awards from automotive OEMs for any program where the Continental AI team has been engaged in the RFQ process. Also in September, we achieved another major milestone for passenger vehicles. NVIDIA announced at their GTC conference the HRL131 sensor system developed by Continental and AI is now available for testing and development on the NVIDIA DRIVE SIM platform. another strong endorsement from one of the leaders in automotive technology. This allows Continental to more seamlessly integrate with OEMs using the NVIDIA platform. Platforms are key for velocity to market and adoption of our software-defined LiDAR. We believe this will enable autonomous and driver assistance customers to accelerate the integration of adaptive LiDAR and be able to harness the full capability of our intelligent sensing platform. As we prepare for production, platform compatibility is key for OEMs to further refine the performance of the HRL-131 to match their specific requirements, which will save OEMs time during the development and testing. Again, accelerating time to market for commercial deployment. One market where our Foresight platform is dramatically impactful and gaining considerable traction is hub-to-hub autonomous trucking. As many of you know, there's an increasing demand for goods delivery and a shortage of 80,000 truck drivers here in the U.S. alone, growing to twice that by 2030. The urgency is compounded by new EPA regulations on carbon emission reductions and NHTSA safety goals, accelerating the timeline for deployment of these hub-to-hub autonomous trucks with immediate and measurable ROIs. After several years of evaluation, we have been nominated by a major system integrator for their autonomous trucking platform. AI has been selected based on our LiDAR's ultra-long range performance, impressive weather capabilities, and commercial vehicle robustness. While we have jointly decided not to publicly disclose our partnership today, This trucking platform is a leader in global SAE Level 4 autonomous driving technology for long-haul heavy-duty trucks, and in addition has several large partnerships with OEM brands already announced. To the best of our knowledge, they currently plan to deploy AI's Foresight platform across their fleet network in North America starting in 2023, with a clear roadmap to scale to substantially higher volumes in 2024 and 2025. In addition to platforms, we have and continue to work closely with individual trucking OEMs. We have engaged in multiple pre-development projects, including Ford Autosan. Ford Autosan selected AI's foresight for its autonomous platform development. They will leverage the ultra-long-range, high-performance characteristics of our platform to address the most challenging use cases facing commercial vehicles. These include front-facing small obstacle detection at long distances to determine override ability, as well as rear-facing blind spot monitoring and long-range detection for safe lane changing. The Foresight platform launch is also having a positive impact in the industrial and aerospace and defense markets. AI recently participated in the ITS World Congress in Los Angeles, showcasing how our adaptive Foresight LiDAR can be used to enhance and address many intelligent transportation system applications. We had over 75 demonstrations of the newly launched Foresight platform with government agencies, partners, and end-user customers. Customers are no longer asking, what is LiDAR, but asking, how can we implement LiDAR? We also had several of our software and integration partners doing demos of their products built on the Foresight API in their booths. Shown here is Vuron, a Korean perception partner showcasing Foresight's long-range detection of automobiles along a highway. This highly requested capability can be used to enhance highway incident detection and to automatically notify authorities if there is an accident or if a driver needs assistance. As we gain traction in the smart infrastructure market, AI's foresight sensors are being installed by top-tier systems integration partners for applications such as automatic incident detection, smart tolling, wrong-way driver detection, and smart intersections. These implementations have been worldwide, from intersections in California and Florida to highway incident detection in Virginia and automated tolling applications across Europe. AI and Grid Matrix have also now teamed up to provide a data collection and visualization solution for ITS. With more than 50% of injury collisions occurring at or near intersections, urban traffic management is a top priority at the local, state, and national level for safety, productivity, and economic and environmental reasons. AI's integration with Grid Matrix cloud-based software platform provides the highly accurate data needed by traffic agencies to visualize traffic trends in order to make better, more informed decisions that could reduce congestion, save lives, and help save our planet. Last year, we announced our intent to integrate our LiDAR with Intetra's tolling solutions. I'm excited to say that we hit our schedule and Intetra is now deploying AI's LIDAR-based automated tolling solutions across multiple projects. In aerospace and defense, we announced our intent this year to integrate our LIDAR with Lake Fusion Technologies' helicopter situational awareness systems, which is on schedule in field testing today. On our last call, we announced a partnership with Booz Allen Hamilton. In addition to expanding our business development pipeline with their portfolio of customers, we are proud of the progress we have made in the joint development of a new network-based perception architecture. This capability allows AI to process analytical data in the cloud in addition to real-time data processing on the sensor. This opens up enormous opportunities for users to customize how, when, and where they process critical information and make autonomous decisions. When you combine this with our patented capability to integrate radar and camera and add optical communication, we believe these system capabilities will enable both smart cities and virtual battlefield or defense scenarios. We believe this is revolutionary. In conclusion, we continue to execute on our 2022 goals. Highlights include we significantly increased technology capabilities and extended our patent portfolio. We transitioned the Foresight platform to our two manufacturing partners. We launched the HRL-131 production intent B sample with Continental for the automotive and trucking markets. We also launched the Foresight product into the industrial and aerospace and defense markets. Finally, we managed our spending to match the challenging global environment and have consistently exceeded our EBITDA goals and enhanced our liquidity. I want to acknowledge this has been an extremely stressful time for many people around the world, and I would like to specifically thank our employees and partners for their empathy, dedication, and persistence in helping us make the world a safer place. Finally, if you believe, as we do, that automation and autonomous systems are the next major advancement in technology, and you believe that intelligent LiDAR will be a key enabler, we encourage you to lean forward with all of us at AI. We look forward to a strong close of 2022 and scaling our business in 2023. We will now open to questions.
Operator
in the question and answer session. To ask a question, you may press star then 1 on your telephone keypad. If you are using a speakerphone, please pick up your handset before pressing the keys. To withdraw your question, please press star then 2. Please limit yourself to one question and one follow-up. If you have additional questions, you may rejoin the queue. At this time, we will pause momentarily to assemble our roster. The first question is from Suji De Silva with Roth Capital. Please go ahead. Hi, Blair. Hi, Bob.
Suji De Silva
Congratulations on the progress here. So, Blair, I'm trying to understand the Foresight launching and the application. Is this now the customers can have a working kind of end product in their hands to test, or have they already had some version of that all ready to test? Just understand what the customer needs. facing and implications are of launch, of course.
Blair
Sure. Thanks for the question, because it is a little bit different than what you would have seen out of many of our peers. As you recall, when we first engaged a few years ago, we actually decided out of the blocks that in order to drive adoption of a sensing technology like LIDAR, that there were two key critical things that we believe you had to do. One was to build a horizontal software platform that could control modular hardware so that you could use the same product across any market. It could be customized and you could drive costs down for the, you know, for the hardware piece of this puzzle. The second, you know, piece of it was that we believe that you would need multiple manufacturers and a capital like business model. So what you're seeing here, in Q3 of this year is one of the major milestones in the strategy. We now have released the foresight platform. When we say platform, that means the software platform. That software platform is being used by SAMENA to construct a product for us for industrial and aerospace and defense. That same software system is also being used in automotive by our first licensee to build a customized automotive grade, one that will be functionally safety tested for automotive and trucking. And they have slightly different hardware configurations, but that we can actually leverage one software platform and, most importantly, as you saw today, one data network. giving them the synergy of being able to actually use data in different ways to drive different customer engagements. So what you would see from a customer facing today, if you were in the industrial or aerospace markets, we have been giving them early versions of our product and early versions of our software. We can update our software much faster than the hardware cycle. They just got, at the end of Q3, their first production software, product, which means that it was produced at SAMENA, and it was the final production, and it was at least the first version of the production software. So for them, they just got the product that they'll be using in the field. So this can be deployed not just in pilots, but in production-scale implementations. In ITS, that could be intersections. Or toll roads and aerospace and defense, it could be putting it on a helicopter, putting it on a plane, using it as a defensive targeting system to track incoming mortars. It could be used on an offensive system. But at least at this point in time, what they would have gotten and the early customers did get was a final product. If you were a customer on the automotive or trucking side, you would have been dealing with Continental as our licensee, and you would have over the last year and a half moved from an A sample to a B sample to a B point, you know, to different point levels of the B because we're able to continue to upgrade the software. So what they got was what we call in this industry term is a production intent B sample. which means that this is the product that we intend to take to mass production in C, in the C sample, and we're allowing them, as we go through final DV testing, to also simultaneously use the product in these pre-development programs. As you saw, we just announced another one with Ford, where they can actually have final input into what we're going to be doing. And just like the ITS and aerospace and development, while hardware changes are much more difficult to make, we can still make many, many software changes with our intelligent platform, given the feedback that we'll get from individual customers. So in both marketplaces, what you saw was in the industrial aerospace, the final product is ready and ready to ship for deployment. In the automotive and trucking market, the final product is ready in D sample format. And as we go through these final stages, once they commit to their volumes, we move the tooling into a C sample and larger production.
Suji De Silva
Okay, thanks, Louis. Very helpful detail there to understand, given your unique business model. And then also, just a quick follow-up. When you talked about six RFQs, if I heard that correctly, with Continental, is that six different customers? Just so I understand.
Blair
Right. So we said early on, and, you know, one of the things that we did, which is part of our culture is, you know, finding truth. We went back and listened to every call we've done since we've gone public and and went back to take a look at what we said. So if you go back and take a look at it, we're engaged in a lot more than six things, but we have consistently said that we are focused that we will do a minimum of six engagements through the evaluation, RFI, and RFQ process, primarily with the installed base of Continental, who they already sell to, but also new customers who are approaching us that Continental approves. So what we say in general, since they aren't our engagements, since it's a Continental product, what we say is that we're engaged in at least six of those processes. That doesn't mean we're not talking to more than six people, but that's the commitment from them as our channel partner, that we'll be engaged at a minimum of six processes. They're all separate customers. And I would say you can break them up. half between trucking and half between automotive. And as I hope I, you know, and again, I'm Italian and I may be too loquacious in my explanations, but what I would say, and I hope you got from the presentation, is that We really focused on a particular capability set. That was high performance. Now, in trucking, it's automatic. You need high performance because the amount of time it needs to stop a truck, you need absolute distance. And because most of the trucking automation that they want to implement to begin with is on the highway, you need to be able to do it at high speed, and you need to be able to see small objects moving. you know, on the road. So it had to be high performance. In the automotive market, the RFQs we have focused on have not been the lower level redundant systems to cameras and radar or short distance systems or low density systems. We have focused ourselves on the capability that it would take to bring out features such as highway autopilot. To date, And it's a very difficult, I'll just say Bob's looking at me, it's a very difficult problem to solve to go over 35 miles an hour. And if you're going to do highway autopilot and you're going to meet what we believe is the benchmark, which is the German DMV standards, then you're going to need a high-performance LIDAR system. So while people talk about RFIs and RFQs that are looking at LIDAR, we are very, very focused with Continental on the ones that have a need for high-performance capabilities because we believe they'll be the first to be deployed. We also believe that they will contain the highest margin because the value they add is adding a new feature. It isn't just a redundant system or, you know, it isn't just a nice system like to be able to park the car. There are systems that customers need and that are critical safety systems.
Suji De Silva
Okay, great. Thanks, Blair. And, Bob, just for the record, I don't mind when Blair talks a lot. Thanks.
Blair
All right. Thanks, Suji.
Operator
The next question is from Joseph Osha with Guggenheim. Please go ahead.
Joseph Osha
Hello, this is actually Hillary on for Joe, and I apologize. I'm in transit, so I'm going to say both my questions up front and then hop back on mute. First question, just on the industrial side, as you start to ramp the various end markets and step throughout the next handful of quarters, I'm wondering if you could provide any color on what that margin ramp looks like. And then second question, just on the op-eds, understanding we're going to exit the year a little closer to what the first half of the year looks like. But just wondering if you could provide any context for what that spend rate might look like as we head into next year. Thank you.
Blair
Sure. Thanks, Hillary. I'll handle the first one, and I'll let Bob handle the second one. You know, we have been, you know, I hope, you know, over our first year as a public company, been very transparent, but also giving you our opinion on how things will actually roll out. And I think we've been pretty accurate throughout the cycle. I would say that as we start to roll out into the IPS segments, again, there's very, very different segments. For instance, intersection management, is extremely important. In fact, 50% of the pedestrian deaths happen at or around an intersection. So those are funded by states. And we believe that this isn't a margin issue. This is a safety issue. So we believe that they will be good margins. They're not like a high volume ADAS system where they have a certain thing they have to hit. We do believe, however, that Margins for customizations at high speeds like toll roads or incident detection could even be better margins. And as Bob alluded to, that's where you see us doing two things as the basis for our model. One is partnering. and reselling other people's software. We're an open system with APIs, and the more people that can build on top of us, the more value we can add. It allows us to take some margin from those pass-throughs. And the second is, as Bob noted, we do have some of our own software now being implemented. As you'll recall, two calls ago, we said, you know, I think very differently than maybe a year and a half ago what some people said when they went public is that We believe that the ADAS market has software capability, but it's integrated with the hardware in its high volume, lower margin. We don't believe there'll be a lot of standalone software sales there because the OEMs and the Tier 1s will actually fill that role to do auto SARs and auto-compliant functionally safe software. That's what they've been doing for 20 or 30 years, and that's their expertise. So there's money to be made. It's being made in the volume, right? We believe in markets that have smaller... volumes or that have bigger safety concerns there is an opportunity for a software vendor like ourselves to add software on top of it so we see a little bit better margin profile now i'll end with um the reality that as you implement these type of systems highly regulated um embedded software and um you know application software on hardware The first, you know, year of this, the margins are not great, right? You can take a look at it, you know, any industry or you can take a look at our industry. So while we believe that there's significant margins in the industrial market, it will ramp up slower because you're doing smaller implementations with lower volume and you're actually, you know, in some ways giving better deals to get the test done. So while we definitely see better margin in industrial at lower volumes than in automotive, we also have a ramp over the next year to move it through.
Blair
Okay, and let me answer the second question, Hillary. This is Bob on the OPEX. As you noted, we do expect the OPEX in the fourth quarter to go back to the levels it was in Q1 and Q2. We had some favorable items occur in Q3 that are not going to be repeated in Q4. So that's the reason for the increase, as we noted in the prepared remarks. And we're not going to give guidance for 2023 at this point. But I think as a working assumption, the way we're thinking about OPEX is that we're going to, again, continue to manage it carefully. So we're not expecting significant growth in OPEX next year off of that Q4 level. So we are going to try to maintain it somewhere close to that level in all likelihood for 2023.
Blair
But is it fair, or I should say for you, safe to say that when you take a look at our OPEX for this year, we have adjusted with the market. significantly without major changes or slowing down our product development.
Blair
Is that it? Yeah, no, very much true. We've, I think, made, you know, great progress in terms of product development and launching, as we said. And within that, we've obviously been very careful with the spending, trying to keep it as low as possible while still achieving all our business objectives. And I think we've been able to do that this year. So, I think we'll continue to, you know, keep a tight rein on the expenses for next year and continue to execute well on the business and the product side is our goal. Great.
Operator
Thank you so much. The next question is from Hans Chung with D.A. Davidson. Please go ahead. Hi.
Hans Chung
Thank you for taking my question. So, first, I want to follow up on the foresight and production with Samina. So what's the ramping schedule for 4th IM, I mean, over next 6 to 12 months, and how much inventory are you going to build to prepare for the demand?
Blair
Thanks, Hans. So the plant that is in San Jose, where we also have that world-class testing facility that we're So grateful for Samina for helping us, you know, build and giving us the opportunity the place to actually put it. That is a low volume line, a production volume, low volume. The Thailand facility is intended to be a high volume line. And when you break out, you know, high volume for low volume, you're talking in a low volume line for industrial, you could be, you know, in the tens of thousands and a high volume line, you could be, you know, to 100,000 or more. So that's kind of the way we look at this. The San Jose line is an extremely big jump for us and one we think that covers us in the short run, but we also believe that the ramp over the next, you know, two to three years will require us to actually produce more than we could produce at the Seminole line. So that gives you a little bit of a context.
Blair
Yeah, just to add to that, Hans, again, we're not going to give guidance on 2023 on this call. So what we said for the fourth quarter is a million of revenues, our expectation. So we'll continue to ramp there. Still, you know, fairly modest volumes as we ramp for Q4, and we do expect our development revenue to snap back a bit in Q4 as well. So as Blair said, we're expecting growth next year, but we don't want to get into specifics on the guiding for 2023 at this point in time.
Blair
Yeah, and, you know, and again, I always appreciate the question because you get right down to the nuts and bolts of how a business runs, and I appreciate that you understand that. You know, one of the things from our culture has been that we did not hype at all last year, and we have a very pragmatic approach to to how we're actually rolling out through the market. And, you know, one of the things we're going to, you know, talk about internally is how much volume do we really want to do in 2023? So, but thank you for the question.
Hans Chung
Okay, got it. So, so next, what's your, like, go-to-market strategy for 4iN? I mean, do you work with the distribution partners or you kind of, I mean, go to a market directly. Just kind of curious, what's your marketing strategy here?
Blair
Right, so I... I would tell you, I'll tell you what we're doing today, and I'll tell you what our belief is over time. And maybe I'll start with the second. As you remember, we went through that long meeting, and we talked about, yes, we do believe that building this system from the software down, making it modular, making it intelligent, and integrating it with other sensors and network will make us better. much, much different, but just as different as our product is, our business model is very different. We assume from the beginning that what we'd like to do is drive adoption by integrating with people who are already into the markets. As you remember from our IPO video, we picked the largest integrators who are already working with the largest train companies. or the largest integrators like Continental who are already working with automotive companies, right? In the automotive market, we are exclusively going through licensees, and you'll see that over time. In the industrial and aerospace market, we will go to a customer directly, but we are also very open to bringing in integration partners because we believe the real value of the system is integrating that data into a network. Or we are now rolling out reseller agreements now that the product's ready, where if a systems integrator could take our product and resell it by themselves, we're open to that model as well. Again, our business model is one of flexibility. cost reduction, and using the experts in every industry to actually drive channel demand. But at the beginning, oftentimes because our product is just rolling out, we will go in and do the initial sale. But over time, we hope that the majority of our sales will be that we're making other people money and that they're so happy with us that they're going to drive a tremendous amount of volume. And that's our goal. And that's very different, by the way, than any of our peers, and that's okay. In every market, there's often direct and indirect models. We just have a point of view that since our system is intelligent, the best way to get the intelligence out of the system is to work with the best of breed integrators who can actually configure it for more value for the customer.
Hans Chung
Great. Got it. Thank you.
Operator
The next question is from John Roy with Water Tower Research. Please go ahead. Thank you.
John Roy
So, Blair, I know you're not naming names in trucking, but will your successes in trucking help you with automotive in a sales way or in a technology way? Any kind of color on that would be helpful.
Blair
Sure. It's an excellent question. I appreciate it. If you look at the high-performance trucking, because, again, I said, remember, we have to think about this through the eyes of the customer. In trucking, they already own the truck. This is an ROI decision. It isn't, hey, I'd like to put this thing in. I'd like to go sell some truck drivers that they want to buy this truck because of it. They are buying an asset, and they want to get return on investment. So for them, this is a high-performance decision. what I'll call automation on demand. Hub-to-hub trucking means when I get on the highway, I can actually use this technology to make the driver more efficient. If you look at highway autopilot, while this one is sold to a customer as a new feature, you still need the same capabilities. So we look at penetration into trucking, which we think is moving much, much faster than automotive, as the key differentiator of how we actually win automotive deals. Because if we can run on the highway with trucks and allow them to stop with the kind of distances we have, that gives us a massive advantage over anyone else who's selling LIDAR systems in the automotive industry who can't actually have that kind of high-end performance. So we kind of, in some ways, it's a different sales discussion, but the capability that differentiates us is exactly the same. And we believe that going to trucking first in some ways is going to give us a huge advantage in automotive.
John Roy
Great. Thanks, Blair.
Operator
This concludes our question and answer session. I would like to turn the conference back over to Blair LaCourte for any closing remarks.
Blair
Well, I just want to say thank you for everybody. We had a record number of people on our call. I don't – I – It's amazing, and we appreciate everyone that came through. And, you know, for those of you who are celebrating a holiday tomorrow, I hope you have a great long weekend. So thank you. Thanks, everybody. Have a great day.
Operator
The conference is now concluded. Thank you for attending today's presentation. You may now disconnect.
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