Good day. My name is Jen, and I will be your conference facilitator. I would like to welcome everyone to Aeva Technologies S econd Quarter 2023 Earnings Conference Call. During the opening remarks, all participants will be in a listen-only mode. Following the opening remarks, we will conduct a question-and-answer session. As a reminder, today's conference call is being recorded and simultaneously webcast. I would now like to turn the call over to Andrew Fung, Director of Investor Relations. Andrew, please go ahead. Thank you. Welcome everyone to Aeva's second quarter 2023 earnings conference call. Joining on the call today are Soroush Salehian, Aeva's Co-Founder and CEO, and Saurabh Sinha, Aeva's CFO. Ahead of this call, we issued our second quarter 2023 press release and presentation, which we will refer to today and can be found on our investor relations website at investors.aeva.com. Please note that on this call, we will be making forward-looking statements based on current expectations and assumptions, which are subject to risks and uncertainties. These statements reflect our views only as of today and should not be relied upon as representative of our views as of any subsequent date. These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations. For a further discussion of the material risks and other important factors that could affect our financial results, please refer to our filings with the SEC, including our most recent Form 10-Q and Form 10-K. In addition, during today's call, we will discuss non-GAAP financial measures, which we believe are useful as supplemental measures of Aeva's performance. These non-GAAP measures should be considered in addition to, and not as a substitute for or in isolation from GAAP results. The webcast replay of this call will be available on our company website under the Investor Relations link. With that, let me turn the call over to Soroush. Thank you, Andrew. Good afternoon, everyone. Aeva in Q2 continued to make good progress on the path towards commercializing our unique 4D LiDAR-on-Chip technology. I am excited by developments with existing collaborations as well as new opportunities and would like to highlight our key accomplishments, which are summarized on slide 4. First, our collaboration with a top 10 OEM is going very well. We are deepening our engagement and integrating further into their AV stack. In Q2, we signed a strategic collaboration agreement where Aeva would provide our perception stack, as well as join the work with the OEM on neural network-based machine learning models in order to optimize the OEM's AV stack and achieve important use cases that previously challenged 3D time-of-flight LiDAR. In addition, the OEM has decided to expand its on-road deployment with Aeva 4D LiDAR on the back of the milestones we have delivered. Second, I'm happy to share that Aeva secured our first win in rail with Railergy, a leading supplier of railway automation solutions, including to Europe's largest freight carrier. Aeva's 4D LiDAR was selected due to our unique velocity data that delivers superior perception capabilities compared to the conventional 3D LiDAR supplier we will replace. Third, we reached critical milestones with our industrial automation partners that keep us on track for a 2024 SOP, including the validation of the LiDAR-on-Chip module for the first industrial product by Nikon and progressing on track with our development milestones with SICK AG. I would now like to provide more color on our recent business developments, which begin on slide six. This past quarter, we significantly deepened our collaboration with the top 10 OEM on a number of fronts. The first is around perception software. We signed a strategic collaboration agreement to provide Aeva's perception stack, built around our unique velocity data, to help the OEM safely operate under important use cases. We will also join the work on neural network-based machine learning models, incorporating data from Aeva's 4D LiDAR to optimize the performance of the overall AV stack. As mentioned last quarter, Aeva's FMCW technology successfully enabled a key safety use case for highway driving that this OEM was unable to achieve previously with 3D time-of-flight LiDAR. Through our ongoing work, we have been able to demonstrate additional ways how FMCW's advantages over time-of-flight, such as direct velocity measurement and long range, without the need to push high optical power, enables new levels of perception that can help the OEM more reliably achieve their high standards for performance and safety. To provide an example, by leveraging velocity for every pixel, Aeva's Ultra Resolution differentiates stationary from dynamic points and brings camera-level resolution that can be up to 20 times that of a conventional resolution. As a result, our LiDAR can detect small hazardous objects, like a tire fragment, at outwards of 50% greater range. Because we can instantly measure the velocity for every pixel, Aeva can more quickly and confidently classify objects as compared to 3D time-of-flight LiDARs that require multiple frames and points to infer velocity. Perception capability like this is critical to safely operating applications such as highway automation. We're thrilled that the OEM has decided to further leverage Aeva to accelerate development of perception software to enable its highway speed autonomy use cases. The second is that as we continue to achieve perception and development milestones, the OEM has decided to expand on-road deployment with our LiDAR further into 2024. This includes plans for additional vehicles equipped with Aeva 4D LiDAR that will be used to validate our perception software and overall AV stack in order to bring it to market. Overall, we are very encouraged by our progress with the OEM. Our focus will continue to be on supporting this OEM to achieve the requirements and positioning Aeva to be selected for the production vehicle program. Moving now to slide seven, where I would like to share more about our first win in rail. Aeva 4D LiDAR has been selected by Railergy to enable their autonomous train solutions. Notably, we believe Aeva replaces a conventional 3D time-of-flight LiDAR supplier because our velocity data, Ultra Resolution, and other benefits of FMCW enable Railergy to accurately and reliably identify obstacles on and around the rails. Critical use case requirements that could not be achieved with 3D LiDAR. The first application with Railergy is for the largest freight operator in Europe to automate shunting activity, which is when trains are separated, moved, and linked together with new cars. Railergy's solution is intending to incorporate multiple Aeva LiDARs per locomotive to safely enable these actions autonomously. We are excited to work with Railergy and see opportunities to broaden deployment to Railergy's other customers, which include other major rail operators. As the rail industry and regulators look to bring safer and more efficient transport, we are beginning to explore opportunities for different types of applications with leaders throughout the rail ecosystem, including locomotive OEMs, technology innovators, and operators. From our engagements, it is clear that Aeva's combination of long range, instant velocity, and immunity to interference can offer unique advantages for rail automation applications, and we look forward to pursuing these opportunities to bring scaled deployment of 4D LiDAR in rail. Let's now turn to slide 8. I am happy to share that we are on track to begin startup production for our industrial automation programs in 2024, and I would like to provide some color on our recent progress with Nikon. This past quarter, we completed development and validation of our LiDAR-on-Chip module for the first product with Nikon. As previously mentioned, this first product is an industrial metrology solution that enables automated inspection during high-volume manufacturing. It requires micron-level precision, where we will leverage our same core 4D LiDAR chip used for automotive applications, but with different algorithms to achieve ultra-high precision. Due to our unique LiDAR-on-Chip module, we are able to offer these capabilities at a lower cost and a much smaller size compared to the current solutions utilized today. With all performance specifications confirmed, this paves the way for us to progress to the next stage, where we will work on the production qualification of our first industrial product together with Nikon ahead of SOP in late 2024. Switching gears now to the opportunities we're pursuing, let's turn to slide nine. Railergy represents a new win this year, and we're making progress on further expanding our number of program wins. In automotive, we continue to advance on large series production programs with a number of leading vehicle OEMs. Feedback has been consistent and encouraging as more OEMs, including especially ones who have previously selected time of flight for initial pilot deployments, are appreciating that Aeva's differentiated FMCW technology can help safely enable their next generation, broader scale deployments. In industrial automation, we have multiple ongoing engagements with large industrial sensing companies to leverage our perception platform for industrial measurement applications. Our focus as a company remains on programs for large-scale deployment with SOPs in the mid-decade, where each of these opportunities offer significant revenue potential for Aeva, and we continue to expect additional award decisions over the next six to 12 months. With that, I'll turn it over to Saurabh. Thank you, Soroush. Good afternoon, everyone. I would like to discuss our Q2 2023 financial results, which are summarized on slide 11. Revenue for Q2 was $0.7 million on account of continued deliveries of Aeries II to existing and new customers. Non-GAAP operating loss was $31.1 million, reflecting our ongoing discipline and strategic approach to R&D and other operating spend. Gross cash use, which we define as operating cash flow less capital expenditure, was $28.5 million, which primarily consists of use of cash for operating expenses. We finished the quarter with cash, cash equivalents, and marketable securities totaling $261.2 million, and weighted average shares outstanding was 220.5 million in Q2. In summary, Aeva continues to maintain a solid financial position as we progress on our objectives. We are very encouraged by the commercial momentum in Q2, and looking ahead, we will continue to execute with a strategic approach to allocate resources and optimize spend to further our existing programs and new opportunities. I will now turn the call back to Soroush for closing remarks. Thanks, Saurabh. Halfway into 2023, we have made strong progress on our objectives for the year, I am extremely excited about where we stand on a number of our advanced stage opportunities. The entire Aeva team is incredibly focused on converting these engagements into additional wins. As I conclude, I want to thank each member of the Aeva team for their ongoing dedication, as well as our stakeholders for their continued support. With that, we will now open the line up for questions. Thank you. If you would like to ask a question, please press star one on your telephone keypad now. You'll be placed into the queue in the order received. Please be prepared to ask your question when prompted. In the interest of time, please limit yourself to one question and one follow-up question. Once again, if you have a question, please press star one on your phone now. Our first question today will come from Antoine Chkaiban with New Street Research. Hi, guys. Thanks a lot for taking my question. Can you maybe provide more detail on the strategic collaboration with the top 10 OEM that you just announced? Any indication on volumes and, are there any other LiDAR vendors in the pipeline for that specific project? Maybe also, when in 2024 do you expect to expand on the road deployment, and what key milestones do you still need to achieve to get there? Yeah, Antoine, happy to answer the question. First of all, we are very encouraged, you know, that OEMs in the automotive space, and especially with this top 10 OEM, are seeing, you know, continued value and significance in our perception software, right? Let me first, you know, before I answer the question at a high level on how we got here. First, you know, we first started on the hardware side, delivering Aeries to hardware to this OEM and then integrating in their vehicles. From there, starting the on-road deployment in the past quarter or so that we had mentioned. From there, with additional units and additional, you know, vehicles built, we continued to hit on our milestones for the hardware. We've been able to really address some of the most challenging use cases, using our 4D LiDAR technology, in which previously this OEM, you know, was having challenges to address with time-of-flight 3D LiDAR technology. Now we are further deepening our relationship into software. With that, we have signed a strategic collaboration agreement to include Aeva perception software, really built around our velocity data, to achieve some of those key driving scenarios that have been quite difficult to achieve. This includes, for example, driving scenarios at highway speeds. You know, we're talking here, you know, not 30 or 40 miles per hour, but, you know, really highway speeds, 60+ miles per hour. Being able to have the vehicle come to a safe stop, especially in those corner cases in which it's difficult to perhaps detect objects that are small or very low reflectivity on the roadway, such as a tire fragment and the like. That's, I think, where, you know, 4D LiDAR really shines and been able to provide those capabilities. We're now working with them on neural network-based machine learning models, as I mentioned, to really address some of those corner cases that are not really possible before. Looking ahead, as you mentioned, we plan to expand our development fleet with our technology, with this OEM into 2024, on the road with multiple vehicles, you know, starting in 2024, beginning 2024. In a nutshell, really deepening our engagement with this OEM moves us from hardware into the software stack, which we believe, you know, creates a flywheel effect for further embedding, Aeva's perception stack and the velocity data into the heart, heart of the AV software stack with this OEM, and we're pretty encouraged by it. Okay. Thanks a lot for, for the color. Maybe as a, as a quick follow-up, can you maybe update us on, on how scaling capacity and, and taking costs down is, is, is playing out? Have things trended as you expected over the, the last 90 days? Yeah, yeah, happy to. We have continued to progress on delivering our Aeries II product to multiple customers, you know, and, you know, including, of course, automotive as well as industrial space. Case in point is really, you know, our ability to do that has led us to make meaningful advances and progress with a number of customers. For example, the top 10 OEM with us being able to get into the software stack and putting this, you know, strategic collaboration in place on that front. For example, for us, being able to secure our first win in rail with Railergy, and which we're pretty excited about as well, and others. I think, our ability to continue on deploying Aeries II is, is obviously critical to our progress with customers across both automotive and industrial applications, as well as, you know, around some of the metrology applications. You know, as I mentioned on the call, we have also completed the development milestones for, for Nikon, our customer, for the first target deployment in 2024, SOP in 2024, with the metrology application. We feel pretty good about that, and obviously, you know, we're working towards our SOP targets with some of these customers. Thank you very much. Your next question will come from Colin Rusch with Oppenheimer. Thanks so much, guys. You know, with the relationship with Nikon, and the ability to pull the time frame forward, can you talk a little bit about how that happened and what elements are going a little bit better than you anticipated? Yeah, Colin, happy to answer that. You know, as we have said before, you know, I guess maybe at the beginning of the year, you know, we had planned to find opportunities in which we can pull forward our industrial automation launches. With Nikon, we have really been able to deliver on milestones on or ahead of, ahead of time and, and really focus on our ability to actually achieve the micron-level precision. That's one of the unique advantages of FMCW, is that, you know, we can, we can tune the software with the same core chip module and LiDAR that we have in automotive, but different and, and, you know, for different applications, different software. Instead of maybe, you know, going hundreds of meters of range, we can trade that down to a lower distance, but then achieve a, you know, ultra-precise accuracy, which it gets us to micron-level precision. We have now completed that. Nikon has completed also their validation and verifying the performance specs and the key metrics that, you know, really matter for their industrial metrology manufacturing inspection applications. You know, they've been pretty pleased with that, and that's, that's allowed them to build further confidence for us to move now to that next phase of industrializing and getting the product ready for late next year. I think, really one of the key reasons for us to be able to do that is because we have been doing this for a while already with our Aeries II product. It's the same hardware. We have had significant experience in developing and releasing new software functionality and validating that with the key customers. You know, that's, that's one of the key factors that, that's led us to be able to do that, as well as our ability to actually produce those modules in the sufficient quantities that Nikon needed to qualify this product. That, that's super helpful. Then with the, the OEMs, you know, congratulations on continuing to move forward with some of these vehicle OEMs. Certainly seen some of the other emerging lidar providers struggle with actually delivering on some of their roadmaps. Can you talk a little bit about how your conversations are changing with those OEMs? Because I assume that you're at the table with most everybody talking about, you know, future-proofing some of their platforms. And how, you know, tangible some of those programs are getting in terms of the potential to move forward in the sales process for you guys. Yeah, sure. Look, we are generally quite encouraged, very pleased with the progress we're making, you know, across the automotive space and vision industrial. I think, as you mentioned, where we also see a lot of interesting developments is especially in areas where a number of OEMs in the past have had experience with time-of-flight or 3D LiDAR, and where, you know, for initial deployments. Since engaging with us, seeing some of the key unique selling points and advantages of FMCW, and how this is really the, the next generation technology that's coming to market, working with us and measuring our capability and aptitude to deliver on the milestones, on the requirements over time. These two, I think, factors have really helped us to, you know, be able to make meaningful progress with a number of automotive OEMs in the space. I think, you know, we've always talked about that with where we believe the industry is headed. You know, some of that is starting to form shape with the progress that we are making, as is the case with top 10 OEM, as is the case with Railergy, you know, both of which have had experiences with the time-of-flight LiDAR are now deciding to really replace and implement us with as the technology of LiDAR. That's what I can share. Okay, that's super helpful. Appreciate it. Our next question comes from Joe Moore with Morgan Stanley. Great, thank you. I wonder if you could talk a little bit more about the win with with Railergy, and particularly, you know, when you think about the, the train market, you know, how, how, how big is that? Is it, and I think are there opportunities to expand beyond that into other, sort of autonomous train efforts? Yeah. Hey, Joe. Happy to answer that. First of all, yeah, we're pretty excited about our, our first win in rail here. Again, this is another example of how unique capabilities at FMCW can enable scenarios for automation that are currently challenged when, you know, we use time-of-flight technology. This is, you know, exciting for us because it's our first expansion into rail applications, and we're really starting to see some of the breadth of apps and applications that FMCW can help end customers solve. I can give you some context on the overall opportunity in rail here. The overall opportunity in rail, you know, globally, is about over $1 billion in the market opportunity. We're talking about 100,000 locomotives globally, and of that, it's about 15,000 locomotives in Europe alone. We're talking about multiple LiDARs per locomotive. The opportunity with Railergy, specifically, is really with the first deployment in Europe, with the largest European freight carrier, you know, about 2-4 LiDARs per locomotive, and ASPs of multiples higher than in automotive. You know, we're beginning in 2025 for deployment of our LiDAR for the rail with Railergy. Separately, you know, we are engaged with some of the leaders in the space, you know, that include train OEMs, that includes technology providers and some of the leader operators that we see potential to expand further in the rail, rail application. Railergy alone also is working with other major rail operators beyond Europe to deploy their solutions to various applications, including in Europe and the, in the U.S. and other global markets. Thank you. We'll move next to Suji DeSilva with Roth MKM. Hi, Soroush. It's Saurabh. Just trying to understand, Soroush, the additional auto customers that could follow this tier one you're working with, would those engagements take the same form of this in terms of a development engagement and then weaving the software together? Would they have a different shape? Concurrent with that question, you know, the ability of Aeva to handle multiple of these engagements concurrently or, you know, kind of focusing resources on one and then have it kind of flow forward sequentially. Be curious to understand how it would waterfall from here? Yeah, Suji, happy to answer that. I think, you know, we're here building a, a, a framework and a, and a platform in which we plan and intend to deploy in collaboration with multiple OEMs over time, with the focus of, of creating kind of one, you know, core product with FMCW hardware technology. Our approach to software, you know, is being in a modular way in which we can build, you know, the, the key software features on top of our hardware in a way that can be qualified, you know, with, let's say, the, the, the first OEM, including with this top 10 OEM. Can also be then from there, scaled and deployed across multiple other programs. That's something that, that has always been in line with us, and that's something that we have here with our collaboration. You know, I think it's very important to start early on with, you know, the, the vehicle manufacturers, so that especially bringing a new technology with, you know, automated driving, so that you can ensure timely validation, ensure addressing the corner cases, and, and really making sure it works before it comes, you know, too close to production. That's the example that we have. You know, we're hoping that we can leverage this playbook with other, other OEMs as well. Of course, each, each customer is going to be different. Sometimes it may not make sense to provide all the modules of, of the perception software, but that modular approach, I think, is a critical part of our strategy. To your second part of the question about, kind of, our ability and resources to support multiple OEMs. You know, today we have the sufficient staff to be able to support all the engagements that we have today. As we, of course, go along, we're continuing to hire and expanding on the team so that we can support some of those key programs on the OEMs. Again, our strategy is not to, you know, go and spray and pray across many, many opportunities. We're focused on a number that is a confined number of program opportunities with large scale, that each of which, you know, provide meaningful opportunities for us and potential for the company. You know, with a focused approach, we think that's the right way to go about with our first deployment, and then from there, we can expand. Okay, great. Thanks, Soroush. My other question is on the industrial auto, the Nikon engagement. I guess start of production sometime calendar 2024. Just curious what the shape of that initial unit ramp might look like or just the size of that opportunity, if you want to talk about it that way, for a run rate. Just competitively, I know there's, you know, other industrial LiDAR vendors out there with high unit run rates already. Obviously, a less featured one than yours. Maybe you could talk about the pricing strategy here versus those guys, just to contrast what's already out there in the market versus what you're going to bring to market. Yeah, absolutely. Look, first of all, you know, the, the planned launch is, is towards the late 2024, and then, you know, starts with volume and scale up from there. Obviously, industrial, you know, the, the volume and, and pricing is quite different than in automotive, but, you know, just to give you a sense here, we're talking about orders of magnitude in terms of differences in our ASP between automotive and what, what is really feasible here. And I think one of the key factors for us is that we're using the same core technology that we're developing already for automotive. We can use the economy to scale, the same manufacturing line, of course, with some customizations and certain things that may not be needed as, as, for example, long range or such, and different software to allow for that. But, you know, from a development perspective, it's also investment for years to multiple iterations of our chip module. Because we have been able to integrate everything down to the Silicon Photonics module basis, we're able to achieve such lower costs at an ability to, you know, build these for Nikon and also help them reduce the size and the form factor of the end product and provide additional benefits to the end customers. That, that's what I can say here. Okay, great. Thanks, Soroush. Our next question will come from Richard Shannon with Craig-Hallum. Hi, guys. Thanks for taking my questions. I didn't get a chance to listen to your prepared remarks, so apologies if I'm overlapping with some previously asked questions. I think the first one I want to follow up with is actually a part of Suji's question, which is how to think about the size of this opportunity with Nikon specifically. I think the time frame is, I think, is well understood. Obviously, the ASPs are quite a bit higher, but it's hard to think about what kind of volumes are here. Maybe if you just want to take it up to the TAM or SAM level here and get a sense of, you know, a couple of years after this ramps, what kind of opportunities does this, does this offer for Aeva? Yeah, I think. Look, what I can say is, you know, maybe I can give you, yeah, high-level figures about the business. Nikon itself is, you know, doing about, you know, $500 million-$600 million a year business in, in the industrial metrology space. You know, they're one of the leaders and, in the space, in, in the automotive manufacturing and the aerospace and others, customers, including BMW, Stellantis, and others. We really see opportunity there, starting with automotive and expanding further into high volume manufacturing. With that, obviously, what we're looking to do is, is, you know, a, you know, a part of the system, right, which is the chip module plus the software. you know, at a high level, if you think about ASPs, from in the space for a full entire solution, we're talking about $100,000+ per unit in terms of some of those ASP in the industrial solution. Obviously, we take a portion of that, which I cannot comment on specifics, but that should give you a rough, some rough sense about opportunity and the scale. This is just for the industrial metrology applications for high volume manufacturing. We do see opportunities further from there over time around other applications, for potential around general volume, electronics, manufacturing, and such, wherever you need to actually inspect, and be precise about that, can't comment on right now, but that's, maybe should give you some general guidelines around that. Okay, fair enough. That's a, it's a reasonable answer. Follow-on question here was, getting more in the industrial space here with, with SICK, and I think your investor presentation says, some, let's see, progressing on development milestones with them, with being on track for 2024. Does that mean you're expecting to start generating some revenues with them? If that's not the case, please correct the time frame there. Then what are some of these milestones you have to progress through to get to that point? Yeah, no, I, you, that's correct. We're obviously working with them currently on the hardware, and, you know, we do expect, from a revenue standpoint, that's continuing to scale in 2024. That's correct. I think from a milestone standpoint, that we have been working closely with SICK AG around ensuring that the, you know, performance metrics for the industrial end customers across different configurations. One of the key things there for us is, you know, we're working also across software configuration, a configurability with SICK, in which in industrial differences, there's multiple different types of customers, with all, each with different types of requirements. I think one of the unique advantages for FMCW and Aeva is that we can tune those the performance of the system with software, and basically, configurability into the actual system without touching the hardware. That's one of the selling points, in which SICK, you know, was eventually decided to work with us after I gave us, as, for this product segment. We're working with them around, you know, ensuring to define, validate, and qualify those different configurations for some of the lead customers, there on the industrial sector. That's the work that we're doing for now and later in 2024. So far, we're progressing good on that. Okay, fair enough. That's, that's all from me, guys. Thank you. There are no further questions at this time, and we will now conclude today's conference call. Thank you for attending.