MicroVision, Inc. (MVIS) Earnings Call Transcript & Summary

Good afternoon, everyone. Thanks for joining us. I'd like to introduce Sumit Sharma, CEO of MicroVision. And joining him is Anubhav Verma, the CFO of MicroVision. They will have a presentation, 30 minutes long, and we'll take questions at the end of the presentation. You can enter those questions in the Q&A box. Go ahead. Thank you. Please go ahead.

So this is our safe harbor slide. So we will be making some forward-looking statements. We encourage you to read the slide for more details. Sumit?

Thank you, Anubhav. So I think just to give an update that we gave at the last earnings call, one of the key things that we're focused on. There are 3 main areas. Primarily, the update really is that we have ongoing engagement with OEMs and Tier 1s. The key differentiator of our product compared to other products that our competitors are offering are primarily that we're focused on a highway pilot -- high-speed highway pilot capability with our high-resolution LiDAR. Of course, one of our strategic -- sustainable strategic advantage remains a low-cost solution or system level cost solution. And of course, with edge computing powered with our proprietary software and ASIC, clearly, it's a differentiated product and will give advantage on cost and technology and a very strong IP portfolio to our potential customers. From a business update standpoint, what we're expecting to do for the rest of the year, by Q2 2022, we expect to actually start our demo car demonstration with this highway pilot feature from track testing, making that available to OEMs and Tier 1s and of course, some parts of them that we are going to share publicly with our -- with the market to really make the point of why this highway pilot feature is actually more important and valuable than other features that people are developing and why OEMs and Tier 1s are much more engaged and interested in it. We also expect that in Q3, we are going to get our Class 1 certification done from a third party. So our product will be completely fully qualified for Class 1. And following that, in Q4, of course, we would expect to start some small strategic sales of samples to OEMs and Tier 1. From a financial update profile, of course, we had a wonderful year last year as far as raising money and making sure the company is capitalized correctly, probably that we ended the year in the strongest position in the history of the company. And of course, if you think about how much cash we used in operation, it was right around where our guidance was to market. Next slide, please. So in a nutshell, as we think about what is MicroVision, MicroVision is a nearly 30-year-old company, but it's had great technology for a long time. And we've built upon that for over 27 years of the company has been at it, started with product development for the military. Since then, we have actually deployed our technology for customers in the consumer space, very large OEMs like Microsoft and Sony and Sharp. We are a fabulous company. Our business model is pretty direct. We develop, we invest and develop some of the highest quality features and products at a system level. But we work with other fabs and silicon partners like Osram, SC, GlobalFoundries, UMC and so on. But we utilize components that are cost-effective and known entities, apply our IP and make a more valuable product and feature that's very cost competitive. As far as the pedigree of the company, I think we have -- we're very fortunate that we have engineers that have been here for a very long time that are the core development that they've done, and that's all home grown. We continue developing and innovating. And of course, we have other additions to the leadership team that helps us understand how the market will play out, and we have confidence in the plans that we're putting forward. Next slide, please. So as we think about the company, right, there's 4 areas that are very compelling and advantageous to the OEM. And I refer to these as our sustainable strategic advantages. So number one, of course, is what we're developing as a product in this very valuable space for ADAS and LiDAR specifically is a Superior Highway Pilot functionality. And we're talking about speed capabilities of 130 kilometers per hour, which is where OEMs and Tier 1s specifically, OEMs specifically are focused around, which is at the next level to deliver. And the solution we're going to deliver for that, that we believe that is going to enable that is a combination of our LiDAR and fusing the RADAR data, which significantly improves their development cost in time. So by -- the second advantage that we give them is overall development costs for them actually reduces because we are able to take our LiDAR data, high-resolution, low-legacy data and fuse it with RADAR data simultaneously and provide them the pre-fused data so they can own the next tier of automation, which is effectively the full sensor fusion and the world view that they could create. We do this on top of a platform that we've created, a technology platform, which is the -- which will provide a lower relative system cost to our potential customers. What I mean by that is if you think about the overall cost in the system, it's not just the number of LiDAR in there. It's the number of LiDAR, number of RADAR, number of camera modules, number of ECUs, number of domain controllers, cables. All that combined is the actual cost to the system. We expect our sensor to be a very competitive price, and the cost of it is much easier to validate because we use scanner components. And as Anubhav will talk a little bit later, we have modeled that out of what the expected target ASP would be and what the upside could be from there based on volume. But we feel pretty confident in saying that the overall system cost will be relative -- lower relative to any other solution that's out there. So we're very excited about this, and we expect to show this forward. And -- can you step back on the one slide, please?

Yes.

So the last slide is, if you think about it, is the seamless integration. By doing this point cloud, this perceptive point cloud with obstacle/free space within our ASIC and providing a low-cost solution, integrating the LiDAR and RADAR data directly to the domain controller, this -- all 4 of these combined are our sustainable strategic advantages. Excellent. So let me just talk a little bit here, and then I'll turn it over to Anubhav on this slide. So as we look ahead, ADAS still remains the biggest market with the biggest volume and the biggest opportunity in this space. I think autonomous driving will be big, but there is significant amount of regulation and sensors and other things to be figured out in that market. And that's going to take time to deliver. We certainly believe that our sensor can enable those markets as well, but we are choosing to focus on a market which is specifically, clearly, when we actually poll OEMs and other top management advisory companies in the world that are building models out for what the space will look like, these kind of volumes that are coming ahead, these are things that can be actually verified from multiple sources. And this is the big opportunity, Level 3 and also what we believe is a cost-competitive solution for Level 2+ where larger volumes exist. And of course, by proxy, that potentially there could be other Level 2 features that we could enable, which are significantly higher volume than in the models here. So I think with that, I'll turn it over to Anubhav because we are focused on a market segment that we believe is going to be the most lucrative to focus our technology. Anubhav?

Thank you, Sumit. So I think just to sort of reiterate the point here, the $80 billion revenue opportunity is the cumulative opportunity that is based on 2 assumptions. Assumption number one, Level 2+ cars will have one LiDAR box. Assumption number two, Level 3 cars will have 2 LiDAR boxes on the cars. And the ASP that has been assumed in this chart is $800, which translates into a $80 billion cumulative potential revenue opportunity in this space. Now moving on to the next page. This slide essentially captures what the business model will essentially translate into from a metrics -- from a financial metrics standpoint. Let's talk about the revenue. We expect a revenue of $2 billion to $4 billion based upon the market that we established earlier. And please keep in mind, this $2 billion to $4 billion is assumed to have an ASP of only $500 just to be conservative on the conservative side as a contrast to the $80 billion opportunity on the slide -- on the earlier side. This is based on an assumption that we would have at least 2-plus OEM partnerships where our market share will be rising from 15% to around 40% by the end of this decade, which essentially translates into 25 million to 30 million units that MicroVision sensors or perception sensors units would be in the OEM fleets by this time in 2030. Now let's talk about EBITDA and why this translates into a high EBITDA. The reason for that is simply because of 2 revenue streams that comprise the $2 billion to $4 billion. Stream number one, which is the hardware, which approximately comprises 25% or 1/4 of the total revenue. This revenue stream will be a gross profit sharing agreement with the Tier 1s we would -- which would essentially be -- ultimately be supplying the sensor units to the OEMs. The 3/4, the remaining part of the revenue stream or 3/4 or 75% of $2 billion to $4 billion is going to come from the software that Sumit described earlier, which is written in our custom ASIC. This is the software that is hovering the LiDAR and also enabling the features that Sumit talked about and which essentially gives the ability, give the competitive edge to our LiDAR product, the highway pilot and the high resolution at its low latency. And most importantly, the software runs on edge computing, which essentially reduces the computing requirements and the chip sizes required in the LiDAR box because for the OEMs, it's extremely critical to keep the cost, which is going to be one of the most important factors for choosing their LiDAR partner to be their next-generation LiDAR partner in their cars. And that's sort of why the edge computing that we have gives us the competitive advantage over our peers because of the ability to include all the computing power in the size of the chip that we're working on in our LiDAR box. This schematic essentially shows where our LiDAR unit will essentially fit into the broader ADAS solution. On the chart here, you see the left box here, which essentially is what MicroVision is working on. And as Sumit described, this is the part of the company in the broader ADAS solution that our LiDAR will go into because ultimately, camera -- camera modules are being controlled by the OEMs, and our LiDAR essentially helps us build -- helps build the OEM a world model, which is essentially a free space cluster versus obstacle. What that means is essentially, LiDAR is shooting off lasers, and what comes out after the bouncing of the obstacle building a point cloud, essentially determining whether it's drivable or not drivable, whether it's an object that you can drive over or you cannot. This gives us the ability to have the computing power at its lowest possible and from a sizing standpoint, lowest possible so that the OEMs -- so that we can control the costs and that OEMs can have the design and the world model that they want to go with for the fully autonomous car. This slide essentially captures what our LiDAR specs are as compared to some of our peers. And as you can imagine, the data rate and the latency remains to be the key edge by which our product essentially beats the market at this point in time. I think Sumit mentioned, we are on track to demo our cars in Q2 2022, where our sensors will be fitted on these cars both in the U.S. and Germany, where we would be demonstrating the data from these cars to the OEMs, which would essentially help OEMs to understand and validate what the technology is capable of. This slide essentially represents some of the investments that we have been making in the last year in our R&D infrastructure and our laboratories to ramp up our efforts with the OEMs. Now let me quickly summarize before jumping to the Q&A for the 2021 financial results. From a revenue standpoint, we had $2.5 million revenue, which was attributable to the contract with Microsoft that was signed in 2017. R&D expense was $24 million, which included about $6 million of stock-based -- noncash stock-based compensation. We believe this number would be slightly higher in 2022 as we ramp up our efforts with the OEMs. SG&A expense totaled about $22.3 million, which includes about $9 million of stock-based compensation. And essentially, we expect that this number would also be slightly higher in 2022 as we accelerate our efforts with the OEMs. From an ATM standpoint, as Sumit mentioned, 2021 was the best year in our history. We raised about $68 million in the first half of 2021. We did not issue any shares in the second half of 2021 as the broad LiDAR market was -- experienced weakness, along with most of our competitors. From a liquidity position, we believe that we are very strongly positioned with $115 million of cash and cash equivalents, including marketable securities, with our burn rate last year of $29 million, which we expect to be slightly higher in 2022 as well. With that, I will open the question to the operator for the Q&A session.

Okay. We do have some questions coming in. And you have mentioned MicroVision has real-world evidence that showcases its significant advancements over the competition, including validation of your core technology and revenue with a major OEM. Please provide additional commentary on how investors should think about that.

I think it's a good question. I think if you think about the space we're in, which is ADAS and specifically LiDAR-focused ADAS for Level 3, there's lots of companies out there, some with a higher valuation than us, some with a lower valuation than us, but they are all technology companies with smart solutions. But if you look to think about MicroVision, this is -- we're a public company for a long time. Some of those companies went public through SPAC recently, but MicroVision has been a public company for a long time. And we have had significant market validation about our core technology over the years from multiple -- from -- starting with the military projects that we did early on, developed the core technology. And after that, in the consumer space, which is actually much more aggressive than the automotive space with people like Microsoft being a core piece of technology that enables the HoloLens product, things that we did for Sony, things that we've done for Sharp. But our core technology has actually shown its pedigree over years, over decades multiple times. So when OEMs in the automotive space consider us, it actually does give them some confidence that we know how to deliver technology to a demanding application, and we've actually already done it. And therefore, as we adapt something for the automotive space, our core technology, that for the automotive space, it is not a far reach for us because it's something that we've already done. And so I take it actually as a very big validation that over decades, we've done that in multiple parts of it. Now what we expect to do, what we work very hard to do, what we endeavor to do is to enable OEMs with our technology in the automotive product. And as we have announced, our A-Sample is focused towards the automotive only. And all the efforts within the company are focused on that. So that's the real evidence that I would like to offer investors that as you think about a company, they have technology that's been proven out over years with some very demanding applications, and that evidence remains.

Sumit, I have another question. You've discussed the OEMs will also get your edge process point cloud as an advantage versus the competition. Can you help us better understand that?

Yes. So what MicroVision will do is we are going to take our LiDAR data, our fused -- fuse it with the RADAR data, which you just stitch it together. And effectively, it will be running on a real-time operating system on our ASIC within our sensor. And of course, out of that is also going to be drivable, not drivable space or obstacle/free drivable space. But it's coming right out of our ASIC. And so when we get the point cloud out, all of this is segmented and annotated, point cloud comes out. Whereas other people, they have effectively signed some deals with, let's say, a silicon partnership where all their algorithms reside within that silicon. And therefore, they're just a hardware provider. So they're developing their software on, let's say, a domain controller. But that makes them not really a tightly integrated hardware and software company. It's going to -- the ownership of who owns the hardware and who owns the software has actually broken apart. So I'm surprised when I hear about that because the most cost advantage -- the solution with the most cost advantage will be the one with a cheaper ASIC that does all of this, and it is running real time. It is running low power. So our sensor is completely differentiated. It's truly an integrated hardware and edge perception software solution that we're going to be offering to the OEMs that allows them to take our point cloud, which is really -- has a lot of annotation and segmentation already done and takes the heavy lift out of any kind of domain controller and comes right of our ASIC. So that's the big differentiator product that we would have.

Okay. The cumulative metrics from 2025 through 2030 seem too low on Slide 6, cumulative revenue of $2 billion to $4 billion. Can you comment on that?

Yes. So I'll take that question. So I think like I said, and let me perhaps point this to take you back to the slide. So basically, as I mentioned, the $2 billion to $4 billion is based on an average selling price of only $500 as compared to $800 on the other side. The reason why we did that is just to be conservative from a public company standpoint. And I think there is a lot of upside -- actually upside from 2 perspectives. One, the ASP for any hardware of this kind would perhaps be in the $800 to $900 in the beginning, and then it will taper off as the hardware becomes more commercialized. And I think we have seen that happen with camera modules. It's going to happen with LiDAR as well. But ultimately, in the starting, we believe that the ASP would be more in the $800 to $1,000 price point. And it will taper down gradually as the LiDAR product becomes more and more commercialized. The second aspect or the second upside that we haven't baked into this number is, I think as Sumit mentioned in the slide before, we did not take into factor, we did not take into account any LiDAR sensors that will be used in the Level 2 cars. This market only includes L2+ and L3. So that's a second upside that we believe we have in the $2 billion to $4 billion from a cumulative revenue perspective. Now the third aspect is the market penetration, the market share penetration and also the number of partnerships, which essentially will also drive a bigger chunk of the $80 billion revenue share that we have on the prior side. So all in all, if the recap of this is the upside that exists in the $2 billion to $4 billion is A, the ASP being $800 instead of $500; B, the upside from the L2 vehicles; and C, the partners, the number of partnerships and the market share that we expect MicroVision to have in the next 3 to 5 years. Because obviously, as Sumit mentioned, the advantages of the specs clearly make us one of the best products out there, which is what the OEMs are looking for at the cost that they want it to be. Because please keep in mind, cost is -- costs will continue to remain the most important driver from a decisioning standpoint for the OEMs because no OEM would want to spend a lot of money to include LiDAR because LIDAR will always be the secondary perception sensor after the camera modules.

So a few more questions. Can MicroVision truly reference $80 billion from 2025 through 2030 if the car companies planned 2 to 3 years out and your product will not be ready for sample shipment until Q4 of '22? This will make the earliest install into a vehicle 2025, '26. Shouldn't MicroVision adjust their outlook and focus on the potential market in '25 through '30?

So I think the way we're approaching this market is because I think you have to think about this. This is the most immediately available, monetizable market out there for the perception units. Because ultimately, L2, L2+ and L3 will continue to dominate this decade from an adoption standpoint. Now obviously, I think as Sumit talked about the autonomous driving, Level 4 and Level 5 will always continue to be on the back burner for a lot of the company. However, our focus is driven towards companies, the OEMs who are expecting to roll out these vehicles in 2025. And as you can imagine, from a sales cycle standpoint, the adoption or the directed by agreement with the OEM has to happen with a subsequent manufacturing partnership because at any point in time, the OEM would want to make sure that the number of units that are going to be needed for the sensors for the car has to be locked down. And we believe that these partnerships will happen in the next 12 to 18 months so that when the cars get rolled out from a production standpoint in 2024, 2025, everything is locked in from a partnership standpoint. Because obviously, from this point in time, until 2024, all the OEMs would be looking to make sure that the sensor cost, the design and the location of the sensor are all locked in by -- and have buy-in from both the design and the production teams at the respective OEMs. And that's sort of why our strategy is to focus on this market as compared to some of the Level 4 and Level 5 markets.

Okay. We have a lot of questions, and I'm sure we won't get to all of them, but here's another. Do you anticipate that any supply chain issues in the near future may impact your time line, especially considering there's current Russian military action? Is Taiwan a source? What countries will be involved in your sourcing?

I think -- I'll take this one. I think we're not talking about our supply chain value chain yet. But as I said, we work with global fabs. We have partnerships with them. These are companies that are really well embedded and like very, very big, cell phones, automotive markets, right? So at this point, we're pretty confident in our supply chain because that's the benefit of our technology, right? Really it's wafers at different fabs, assembly process that we control with partnerships that are in the middle. So I think like we -- right at this point, we don't have any data to say that there's any big impact to our supply chain or an impact that will be -- that is not being felt globally. So I think we're okay for now. I think there's another question that I see in there that I actually want to feedback on to this one if you don't mind, Laura?

Okay. Sure.

And the question is, what is the reason why Class 1 certification cannot be done now. I think perhaps this individual is tying it into the supply chain question, right, because of anxiety within the market. So Class 1 certification goes through a step-by-step process. You can finish the product, you have to do cell certification, then you have to go out and get third-party certification and then you can provide the report. So there's a whole process to it. And it's a process we're very good at. We've done that multiple times with global OEMs for their projects. So it has to go step by step to develop, and you cannot put the cart before the horse. You have to finish the product, demonstrate it, do the cell certification and so on. And so what we have laid out is probably the most aggressive time line to get a certification that allows us to start putting it on -- providing it for strategic demo sales. But that does not preclude us from actually collecting data on a close test track or demonstrating it to a potential customer at their test track. So we continue to find those opportunities and connect with people there. But the Class 1 certification is something very, very specific that prescribed and is regulated, and we have to go through that process.

Okay. One more question. We probably only have time for 2 more of it. Can we expect any revenue on the non-LiDAR technology from Microsoft or other verticals after the prepayment from Microsoft is closed? Had there been any Tier 1 OEMs showing interest outside of Microsoft? And any other comment about the Sharp relationship?

Yes. So let me take that question. So I think obviously, in my prepared remarks, we do expect that there would be another $2.5 million revenue in 2022 from the Microsoft contract. However, I think as we talked about, the AR market is still in its infancy. And I think we have the product, we have the technology, and we are ready to support our customers when they need it. But we believe that what the market is going through is it will still take some time for this market to mature and show the revenue opportunity, which we are seeing in LiDAR space. The discrepancy between that is quite a bit. And we still continue to invest our efforts and resources into the automotive LiDAR because that's the market that is immediately monetizable in the near -- mid- to near, time range from a timing standpoint. And that's why we are investing in the automotive LiDAR. But we continue to be ready to support our customers in the AR space as they're needed.

Okay. One last question. What can you share about your process to identify potential strategic alternatives?

So I think, look, we are a public company. And I think as you can imagine, we always are making sure from a value creation perspective, we are making the best use of the cash that we have because we are very well capitalized. And we're investing our cash in the right focus areas. So we continue to look for opportunities that accelerate and enhance shareholder value from a growth standpoint. And I think as Sumit mentioned, the focus of the company remains in the automotive LiDAR space and our ability to drive adoption rate amongst the OEMs. So we will be pursuing all options available to us to accelerate those efforts to land as many partnerships as we can with the OEMs.

And I'd like to add something on to that, Laura, if you would allow me just a couple more seconds.

Sure.

We're a public company. We have a 20-plus year history of very strong IP, core development, sustainable strategic advantage. And we're developing something that is completely in tune with what the automotive space is looking for. If anybody sees there's ADAS companies out there that are multibillion dollar deals that are getting done or at least one that is out there for everybody to digest, we're open to anything that comes into as far as strategic alternatives. I think I've said that consistently in every earnings call. Nothing has changed there, right? I think we work very closely with our Board to evaluate every opportunity as a public company that would enhance shareholder value.

Okay. Great. Thank you so much for your time and for your presentation. If anyone has any other questions, unfortunately, we cannot get to all of them, please put them on the MeetMax platform, and we will certainly forward them to MicroVision. Thank you very much for your time, everyone. Have a good afternoon.

Thank you so much.

Thank you so much.

Thank you.

Thank you. Bye-bye.