DataSpeedInc Describes Creating MVIS LIDAR Jeep

Sharma/Verma Conference Transcript


MicroVision, Inc. (MVIS) CEO Sumit Sharma on Investment Community Webcast and Press Conference (Transcript)

MicroVision, Inc. (NASDAQ:MVIS) Investment Community Webcast and Press Conference January 5, 2022 5:00 PM ET

Company Participants

Sumit Sharma - Chief Executive Officer

Anubhav Verma - Chief Financial Officer

Drew Markham - General Counsel

Sumit Sharma

Welcome to 2022, and our first ever virtual CES. I hope everyone remains safe through these unique times. I'm excited to be here today and share our big plans and how this will change our trajectory as a company. I'm excited for us to start unlocking business opportunities that would see us becoming a top-tier ADAS safety company.

This year, we intend to show the world how our hardware and software technology will enable ADAS safety, which remains the biggest market for the next decade and beyond.

We started our hardware development journey 2.5 years ago, trying to achieve a best-in-class sensor. I am proud to say that our hardware specification exceed expectations and are allowing us to unlock ADAS safety with our proprietary software and future ASIC.

Our engineers have enabled innovative and proprietary features like dynamic field of view, which allows us -- dynamic field of view. This is analogous to having the eyes of an eagle that can see details near and far at the same time. Competitors with static field of view may have high resolution in near field, but have to deal with big gaps in point cloud at range, which have to shore up with software, which isn't adequate performance to deliver highway pilot safety.

The range of a sensor is important but the ability to deliver a dense point cloud at low latency is paramount. Future ADAS safety systems will want sensors and software to help them detect, process, plant and start maneuvering a vehicle in less than 150 milliseconds. This is faster than the response of a Formula 1 driver who'd have to avoid an accident.

Current highway pilot systems take significantly longer and thus operate at lower speeds and are suitable for traffic genesis features only. With our hardware and software running from a single ASIC inside our LiDAR, we will output a perceptive point cloud with drivable and nondrivable space tagged in the point cloud streaming. Our teams are working to demonstrate a first high-speed highway pilot system on a test track to some of the most challenging scenarios that OEM are interested in.

Our proprietary hardware developed over the last 2.5 years allows us to achieve the most important safety feature. We have a great opportunity to become the benchmark for highway pilot operating at 130 kilometers per hour with seamless integration of LiDAR and radar data within our ASIC at the lowest relative system cost. With our solution, we expect OEM to require fewer overall sensors and controllers at vehicle level.

A very important additional advantage our technology creates for them is saving significant development time and cost by reducing time required to train their algorithms. Overall, we will simplify the hardware and software stack and give OEM more control to develop safety features for their customers. There are huge advantages to our approach.

Current camera module-based systems run algorithms that require lots of training and even then operate at limited scenarios. Classification of the scene takes a lot of processing time and compute costs and those systems are not able to perform better than average drivers already achieved. In the future, every vehicle equipped with our solution will make safe driving standard from low-speed surface roads all the way to full highway driving speeds.

ADAS safety remains the biggest market segment where huge volumes are being planned, and this requires our best work and full attention. Our approach of directly pipelining radar data to our LiDAR and providing a fused and tagged data stream, makes us instrumental part of the OEM solution stack.

They will develop and leverage algorithms and architectures they have built to support camera module-based solutions where we provide a seamless way to get to next level of safety with new LiDAR sensor that are expected to be part of the Level 3 ADAS vehicles.

It has been exciting to start seeing safety regulations and standard testing come online. We have also structured our business and go-to-market strategies to work with the OEMs directly and promote our technology and have the opportunity for custom development of features for them on our platform, while also connecting with Tier 1 partners that would do final integration of systems. It is a complicated ecosystem where we have worked hard to remain aligned with the best path forward.

We have achieved a lot on technology front over the last year and now are positioning ourselves to create commercial success.

Now, I would like to invite Anubhav to provide color on how we are positioning our business and planning for our future. Anubhav?

Anubhav Verma

Thanks, Sumit. As we all know, a superior product is just 1 of the 2 most important factors for a successful commercialization. The go-to-market strategy is the other element that is required to drive a higher adoption rate amongst the OEMs, ultimately translating into a predictable and recurring revenue stream for MicroVision.

As Sumit highlighted earlier, MicroVision is strategically positioned by the virtue of our superior LiDAR hardware capabilities powered by the proprietary software on our custom ASIC. This makes the go-to-market strategy equally or, in fact, more important than having a superior product. This is indeed critical to develop a solid business with strong foundation and attractive financials.

Our go-to-market strategy has 3 pillars: Pillar #1, which is the most important and the cornerstone of our strategy, direct partnerships with the OEMs. We are directly marketing our products to OEMs, aiming to secure co-development deals eventually leading to directed buy agreements. The end goal of these directed buy agreements is to lock MicroVision's product as the LiDAR solution for the respective OEMs fleet production.

Now let's talk about the second pillar. Before discussing this, we have to highlight one very important fact. OEMs rely heavily on Tier 1 suppliers for ADAS solutions because of their ability to successfully produce and package both the hardware and software solutions required by the OEMs on a mass production basis. The second pillar of our strategy is directly a result of this very deep and strategic OEM Tier 1 relationship.

We will be partnering with the Tier 1 once the directed buy agreement is signed with the OEMs. This partnership will make Tier 1 suppliers our revenue-generating end customers. We expect to generate revenue both from the hardware and the software components, which I will talk about in a bit more detail shortly.

Lastly, pillar #3. We plan to launch partnerships with key silicon companies to support our hardware on their compute platforms. This will be included as part of the reference design with them. To summarize, this 3-pronged go-to-market strategy differentiates us from some of our competitors and clearly derisks MicroVision from taking on a heavy OpEx profile and risks associated with mass production of the sensors in-house. In short, we're playing to our strength of being a high-tech hardware and software company and do not want to pivot to be a manufacturing company instead.

Now let's talk about some numbers as we drill down on how to quantify the future for us and how it translates into an attractive business model. We're providing some directional parameters for the investor community to estimate how big is the market and then walk down from there potentially modeling the future.

Now let's start at the top with revenue, which is the starting point of the business model. We believe that there's at least $80 billion of cumulative revenue opportunity for this market through 2030.

The SAM or serviceable addressable market revenue figure is derived from the estimated LiDAR sensors required for all vehicles to be produced with L2+/L3 capabilities through 2030. However, we truly believe this $80 billion may be a conservative estimate of the SAM because we estimate LiDAR sensors will become even more widely available in cars with just L2 features, which is likely in the second half of this decade, and that will translate into a much bigger number than $80 billion.

The second most important variable in the $80 billion revenue figure is ASP or average selling price. We have assumed an ASP of $800 per unit, which is an estimate obtained after pulling several industry leaders and executives. Like any other hardware product, we believe the ASP will be higher in the early years and will decline in the subsequent years as their LiDAR hardware becomes more commercialized. This is what happened with the camera modules in the past decade and is very typical of any hardware in its life cycle as mass adoption picks up pace.

Now with the starting point of at least $80 billion, let us discuss some more parameters and the associated assumptions to drill down on MicroVision's revenue profile. Now going back to the most important pillar of the go-to-market strategy, we estimate on the conservative side that we will have directed buy agreements with at least 2 OEMs. We estimate the market share of MicroVision can be anywhere starting from 15% and gradually rising to 40% depending on the adoption by the number of OEMs.

As I mentioned earlier, the end customers for MicroVision will be Tier 1s. The revenue from Tier 1s attributable to MicroVision will primarily come from 2 streams. For the purposes of being even more conservative, our estimates for the cumulative revenue profile of $2 billion to $4 billion through 2030 only models $500 as the ASP, much lower than the $800 pulled from industry experts I talked about earlier. In other words, the $80 billion number has now been estimated to be closer to $50 billion as a starting point.

Let us go one step further down into the 2 streams: stream #1, the hardware revenue from Tier 1s once a directed buy agreement has been secured with an OEM and a manufacturing partnership has been established between the OEM and Tier 1. Mathematically, this revenue stream can be modeled as a gross profit sharing arrangement with the Tier 1s and MicroVision. On an ASP of $500, we believe that the gross profits to be in the 10% to 15% range gradually tapering off through 2030 as the hardware becomes more and more commercialized after mass production.

MicroVision can be expected to share 50% of these gross profits. The revenue stream is expected to grow with the number of LiDAR units being produced. The tapering off gross profits is a direct consequence of the phenomenon I described earlier, which is typical to any hardware product in its life cycle.

Stream #2, the software revenue stream from Tier 1s. The revenue model will be a fixed fee per every LiDAR unit delivered by the Tier 1 to OEM. This revenue is for the proprietary software on the custom ASIC. Based on the superior software and custom ASIC, we believe we will be able to command 15% to 25% of the ASP, $500 in our assumptions, as I discussed earlier, as this is the software engine that controls the hardware and associated sensor fusion with radar to build the world model for the OEM.

This revenue stream will continue to grow in proportion to the number of LiDAR units being produced and shipped to OEMs. The pricing of this will not have the same headwinds as the hardware product life cycle because the software will need to be [Technical Difficulty] upgraded by the MicroVision team.

To summarize, the $2 billion to $4 billion number is simply a very conservative estimate. Our estimates have 2 big upsides. First, the average ASP of being higher than $500, which we consider the total market, expanding with LiDAR sensors just needed for L2 vehicles on top of L2+/L3 vehicles.

Now let us discuss the OpEx or the operating expenditures and how to model them. The single largest cost for MicroVision's business model will primarily include headcount for scaling the team of engineers to enhance the software with any functionality updates in the hardware, in the life cycle of the product. Let me discuss a simplistic way to model this from our publicly reported numbers for the third quarter 2021 earnings.

The R&D and G&A expenses for the year-to-date period ending September 30, 2021, were $17.6 million and $15.6 million, respectively, totaling to $33.2 million. If we back out the noncash components like stock comp and D&A adding up to $14 million in total, we estimate $19 million of cash OpEx for the 9 months ending September 30, 2021. Using our average headcount of 80 to 90 FTEs in the same period, we can roughly estimate that the fully loaded annual cost of an engineer to be between $250,000 to $300,000.

The number of partnership with OEMs will be the most important driver in scaling of the engineers and hence, the OpEx. There may be some modest increases required in the sales and marketing efforts as the company scales its business. As a result of this, the EBITDA profile of the company is expected to quite resemble that of a typical software due to the business model. The revenue growth is directly tied to the number of LiDAR sensors required by the OEMs, while the OpEx growth is a more linear to account for the demand in the number of engineering resources.

With these general guidelines and assumptions, we estimated the revenue to be between $2 billion to $4 billion and EBITDA to be $1 billion to $2 billion on the conservative side.

These illustrative figures should help you to quantify what success may look like for MicroVision until 2030.

Please note that while these are not forecasts, I hope these assumptions help you understand why we are really excited about the future. We are truly transforming MicroVision's core technology to make it the most prolific and advanced LiDAR sensor out there in the market.

Thank you. Now I would like to invite Drew Markham, our General Counsel, to start the Q&A session with Sumit and I.

Question-and-Answer Session

Q - Drew Markham

Thank you, Sumit, and Anubhav, for presenting your views on management's business strategy and product plans. Now we have several questions that were submitted by the investment community and the media.

First, though, I want to share that our listeners understand that this presentation contains forward-looking statements relating to expectations regarding our business strategy, future market position, product plans, potential partnerships and future product performance. All such statements reflect our expectations, assumptions and estimates as of today and are not guarantees of actual future performance or results, which could differ materially.

We encourage listeners to review MicroVision's SEC filings for more information, in particular, factors that could cause our actual performance to differ from our expectations.

Finally, except as required by law, we assume no obligation to update any information in this presentation to reflect events or circumstances in the future, even if new information becomes available.

I'll turn now to the submitted questions.

Drew Markham

Congratulations on MicroVision's participation in the LiDAR Sensor Standards Consortium announced in December 2021. Can you please provide color on MicroVision's LiDAR technology milestones for 2022?

Sumit Sharma

I think that's a great question. I think, first of all, being part of this Consortium is an important step. Most of the LiDAR sensors are not commoditized, and therefore, it's kind of important that all the different features that people talk, about all the different specifications, they start -- they have to get benchmarked in a more unified manner. So being part of this is actually a pretty important step, and I'm actually excited for us to be part of it.

As far as 2022 is concerned, as I tried to highlight, we have a hardware that we can leverage and we can actually enables us to do things that others cannot. And we actually look forward to adding software to it to start showing some of the features that will be possible to enable ADAS safety. So if we can move the conversation further away from just the LiDAR hardware discussion to the actual integrated product, which is ADAS safety.

So what we expect in 2022 is our team is continuing to polish, of course, our hardware as we think about maturity. But the software part of it, we are going to do more track testing to specific OEM test scenarios, that are some of the hardest ones to achieve high-speed highway pilot safety features. We expect to have that on the way somewhere around Q2 and Q3 time frame, right? We're going to -- of course, as data becomes available, shared publicly.

One of the exciting news that happened recently was Mercedes announced their L3 system. And I think that's actually a big moment where you can see that these features are going to be starting to come into vehicles model year after model year. And Daimler always tends to be first to market with these kind of safety features.

I think in parallel, we are going to work with OEMs because there are going to be unique features that every OEM may want to see into our hardware, and we're going to work with those partnerships and start to develop some sort of design wins from there on out.

Drew Markham

From a technology perspective, can you elaborate on the capabilities of MicroVision's LiDAR versus the competitors? And can you tell us how you think about scalability advantages?

Sumit Sharma

I think this question comes up often, right? And I want to take some time on this one. I think the big 2 camps that people always talk about is the 905-nanometer laser versus 1550. I think what we've tried to highlight multiple times in different -- certainly in Munich, we did this, and we've done this on earnings calls as well, what we try to highlight is it's the solution that you're solving and it has to be at a certain cost point. I can personally tell you that every OEM meeting that I've actually attended, one of the first comments that they make is about where do you expect your price to be. This is even before they review any of the feature set.

So from a base level, the 905-nanometer laser technology is mature, it's pretty well known. When we open up our device, the interesting part that I always talk about is everything inside there is known technology. It's silicon that is known, it is lasers that are known, it is sensors that are known. It is plastics and metal, that's all known. And what's valuable about it is our IP of what we are able to take those components and transform them into a great product.

When you talk about 1550-nanometer technology, you're talking about things that require significant investment to mature to the level where they are. They come from other industries, not specifically designed for these kind of high-speed applications that we're talking about. Another advantage that I think we have is -- always going to have is, of course, the capability of doing velocity -- clustered velocity out of our ASIC, not requiring higher level of compute or other domain controllers or other ECUs added to the system. So the overall system cost is maintained lower.

Of course, our feature, one of the biggest features that we always talk about is high resolution at range. This is what's going to enable some of the safety features that highway pilot requires.

I think one way that I described it to -- recently to somebody that asked me this question was, think about -- all of us drive, think about driving on a highway at 75 miles an hour, the easier one, the scenario is somebody is coming with an on-ramp at a different speed. That's a pretty tough scenario. But a tougher scenario is somebody is in the next lane over, maybe 2 car lengths away from you, driving 75.2 miles per hour. So they are actually very close. And if any kind of -- somebody tried to cut somebody off, those are dangerous situations. So from a product standpoint, these are the kind of things that you have to have in to your system to be able to enable highway pilots.

And of course, the last point is like you have to do this in a certain power -- You can't -- you want to think about the power that this system consumes. And we expect that when we are actually going to be in a full ASIC system with all the features in, it's about a 35 watt system, perhaps lower based on the feature set that the OEMs or Tier 1s are targeting. So I think all in all, we have all the feature set baked in. Now the best part about this is the solution by itself is scalable.

Our MEMS have been scalable for a long time. We've scaled them for multiple customers over the years, so we know a lot about that. As far as the ASICs are concerned, our digital ASIC, our analog ASIC, again, these are areas that we are very, very comfortable in, and we've done that before. So we can demonstrate scalability to anybody interested as they project forward of what would be the advantages that we can provide from cost. We don't have to extrapolate cost and scalability. We actually have models that independently could be confirmed. So I think we have all the features that we would need to attack this market and our solution from the ground up is scalable.

Drew Markham

What are the advantages of your integrated hardware and software solution compared to what your competitors are doing? And why do you expect MicroVision to win, given the fact that others have a headstart?

Sumit Sharma

I think when you think about the integrated hardware and software solution, I think the best way to think about it is that we do not utilize complicated ECUs and domain controls, which are very expensive, additional expenses like that. We pipeline everything through our ASIC. And that's actually the biggest benefit that we are able to do it at a very low-cost pipeline through running at full streaming. That's the big advantage. As far as a headstart, I think if you look at what different people are doing, they're going towards classification and other things.

Well, based on our experience, what we know is that those features are things that the OEMs own and they specifically want us to be part of the stack, but they do not want it to be part where they -- the software that they develop is owned by somebody else. So I think for us, our advantage still remains an integrated hardware and software solution that's fully pipelined, low cost, and it's got all the features already baked in that allows us to meet some ASIL B -- future ASIL B requirements that the system will have. So I think we positioned the hardware and the software solution pretty well. And I think we've had very positive feedback consistently on this.

Drew Markham

Why is fusing LiDAR and radar important? And how is a 30 hertz frame important for ADAS? In addition, will your software run on chip platforms like Qualcomm and NVIDIA? Or is there another appropriate architecture?

Sumit Sharma

I think I'm going to answer the second part first. I think the first thing to remember is, as I said, that our software actually runs inside our ASIC, it will when the ASIC has developed eventually. We are not going to be leveraging the full-blown classification suite and features that Qualcomm and NVIDIA and other chipset providers have -- are developing for the full level ADAS. But we are -- we do expect to be part of their ecosystem as a reference design. So our hardware would be something that would plug and play into their domain controllers. And that's an actually pretty important distinction.

Our software will reside on our ASIC, since our ASIC drives our system and also the software, it is a central part, is the heart of our system that digital ASIC cannot be removed from our system and put somewhere else. So that integrated part actually makes a lower-cost solution. Qualification becomes a lot easier and actually plugs with other systems and allows OEMs and Tier 1s to develop other algorithms and software on top on their domain controller.

Now fusing radar and LiDAR, it's important because the current -- in the current architecture, all this fusion is happening at one top level where the algorithm costs are significant to develop, and it takes quite a lot to prove those algorithms out. LiDAR and radar of course, are similar.

The electromagnetic spectrum may be different, but they have similar attributes to it. Our LiDAR, of course, has an extremely high resolution feature, which, of course, radar does not have. But we are able to augment and fuse them together and actually get data with redundancy provided directly to the domain controller or to the stack where the fusion starts happening.

So this is a very important first step that takes a lot of the development cost away, reduces development cost from OEM and actually makes a more streamlined product for them at a lower cost. So it is a pretty important step, and it actually will enable us to do more, not less when it comes to working with silicon partners that are going to provide the domain controllers in the future.

So I think long term, the architecture that we've picked, we've actually validated it, we've talked and presented. We get positive feedback on it. The architecture by itself represents lower cost, better development times and people can own their IP that they've already developed. And MicroVision's hardware becomes central into their system now, allowing them to reduce the number of sensors that would be inside a device.

Drew Markham

Can you elaborate more on your approach to silicon partnerships and how this will give MicroVision an advantage?

Sumit Sharma

I think as I said, we intend to work with the top silicon partners out there that are going to -- that are planning to provide a Level 3, Level 2 system domain controller, and we intend to work with them and make sure that our sensor is part of the reference design that they provide. Our solution eventually will plug and play with these partners, therefore, enables the OEMs to pick any domain controller that they want, any partner that they think for the model year that they want and start building their technology, their software on top of that architecture, but our -- it will be agnostic to how we actually connect to the domain controller.

Drew Markham

Okay. And Anubhav, how will direct marketing and potential co-development work with OEMs if final sales in the future would be to Tier 1?

Anubhav Verma

So direct marketing and co-development with OEMs, as I mentioned earlier, will directly lead to directed buy agreements. So this is an agreement where the OEM locks in the MicroVision's LiDAR as part of their fleet production. So as I mentioned earlier, we would be focused on marketing this product to the OEMs. And once we get the directed buy agreement, we would then be partnering with the Tier 1s for the manufacturing or mass production of the same sensors. Ultimately, that would be a commercial agreement between the Tier 1s and the OEMs for the number of -- because as you can imagine, it will run into millions of units, depending upon the model, the year and the make of the OEMs. So that's why our focus is directed at the OEMs because that's a single point of entry to get our products locked in with the respective OEMs.

Drew Markham

Okay. This question is back at Sumit. Why is MicroVision focusing on highway pilot and when did our focus turn to this?

Sumit Sharma

Actually, if you go back and think about the earnings calls for the past 18 months that we've had, I think we've always talked about our hardware and software stack. I think the highway pilot is a term that is becoming more common in the industry, but our path has always been edge computing, our algorithms, our software running on our hardware. So I think we've not actually deviated from it. I think it's just a finer point of a highway pilot title that is becoming very dominant in the industry as far as the features has been developed.

I think if you think about the safety system that everybody is looking for, they're looking for a solution. If you just have a LiDAR or just have a camera module or just have a radar, that's not adequate and sufficient because somebody, OEM, Tier 1, some company has to fuse it all together and do the safety.

So our system now is, again, more elegant in the sense that it provides them the one big step that they need that allows them to make the fusion core to what they know right now, which is camera module based. So therefore, we ease the burden of utilizing our technology. So for highway pilot, again, just to reiterate, highway pilot is just a term that is becoming dominant in the industry right now, but it's always been our path. And we've always been consistent about it that this is something that we're going to do, remain on the edge computing side, which is our ASIC. And we're now going to actually expand ourselves into developing full classification models.

So I believe we're still consistent with what we've said for the past 18 months.

Drew Markham

Okay. A little further on this topic. What do you see as the advantages of MicroVision's highway pilot system?

Sumit Sharma

I think the Daimler system is very interesting. But if you think about it, it is limited to about 60 kilometers per hour, about 36 miles an hour. That's not a system that one could see as having full-blown safety going into highway speeds. Now there's a race. Everybody is trying to develop the next system that would actually be able to achieve full highway pilot speeds.

We are planning to showcase something running at 130 kilometers per hour. That's a pretty big statement. It's a pretty big achievement, and we intend to do it this year, and our team is working very hard for that. And we always set the path towards that because that's the final goal, and that's where our LiDAR shines the most. It actually is able to do lots of things that come from the low speed, which is about 30 kilometers per hour, all the way to 130 kilometers an hour, which is what's expected.

There's a significant amount of lower relative costs that we can expect from this. And that's an important point to think about it. There's a certain amount of sensors that will be required for a Level 3 car that people will visualize. By adding our LiDAR, by integrating the software in it, effectively, we believe that the number of sensors required will be less and that the overall system cost goes down, which, of course, increases the penetration into the market, the numbers that Anubhav actually talked earlier, that penetration requires that the system cost has to be kept in check. You cannot have a system that's tens of thousands of dollars. So it's not just about the cost of the LiDAR, it's also about the cost of the overall system. So by having the software that our team is developing, the overall system costs will come down.

So therefore, it gives us other opportunities, like you said, we have some conservative numbers in our modeling. There's other opportunities to look at, what the right number would be at the right scaling. So that relative system cost is something we're enabling beyond just our LiDAR cost.

Again, of course, cost is also about engineering costs on not our side, but also on our partner side. The seamless integration by partnering with the silicon companies. This, by itself, of course, saves significant amount of engineering cost on other side as well, makes it seamless for our sensor to be integrated into solutions potentially. And of course, finally, if you think about it, like development cost is about training right now, and this is a paradigm shift where you can actually see a system using a MicroVision LiDAR, the development costs will reduce because we would provide a tagged point cloud that shows drivable and not drivable space, while their algorithms start doing their work and the load has been shifted from the domain controller and their computing over to MicroVision's proprietary ASIC.

So I think like this is actually a big advantage that we will provide, and of course, all at low latencies. So not utilizing big GPUs and big CPUs to do this work and doing it in ASIC would always give us an advantage. And our proprietary technology would stay within the boundaries of our digital ASIC.

Drew Markham

Sumit, can you please comment on the expected timing of MicroVision's partnerships with OEMs and Tier 1s? And do you anticipate any restrictions as to who MicroVision can partner with?

Sumit Sharma

I think I answered this before. We own our IP. Our investors have helped us fund it for so many years. I do not see any restrictions for us to work with anybody out there. There's no restrictions out there whatsoever.

Every OEM wants to see hardware and solution integrated with software, but all of them have different scenarios that they're looking at. And we work very closely with them to understand all the scenarios. We go through simulation to show them how our technology would have an advantage in those scenarios. Then of course, we do track testing. And then beyond that, of course, we would engage them and do it at their track when these -- the test scenarios are specific to them, we will demonstrate at their track to them.

So I think those things are in play. As I've said before, by June 2022, we expect to have track testing done and some data that we would be providing publicly. And of course, a lot of this data is also shared with our OEM and Tier 1 partners. As far as the overall OEM -- every company is raising demonstrated capability, but it's important to get the scenarios that they are actually focused on, and that's what we feel very comfortable that we have a very good understanding of the most challenging scenarios that they are faced with, and we feel confident that we are able to actually address their issues in those scenarios. So I'm excited about that.

The work is actively going right now. And of course, in parallel, we're actively promoting the solution to the OEM, meaning that we demonstrate what we can, simulation data, testing data as we go based on each specific need that they have. But I think that from a time line standpoint, I think nothing has changed. I still expect our team is very confident that we expect that by June 2022 this year, that we would be able to demonstrate something. And of course, we'll talk more publicly about it as we are closer to that.

Drew Markham

Okay. Anubhav, I think this next one is for you. What was the company's head count at the end of 2021? And can you share any expectations for 2022?

Anubhav Verma

Sure. At the end of 2021, we had about 93 employees, including our Germany office. We have almost grown 2 times since March of 2021, when our headcount was approximately 50. We continue to put significant effort into recruiting and expect to add our employee base as we scale our business next year.

Drew Markham

Okay. A somewhat related question. What are you doing to enhance your sales and marketing efforts to make potential customers and partners aware of MicroVision's product capabilities?

Anubhav Verma

So we're now actively building our Germany presence, which is evident from the headcount growth that I talked about. This is to support business development with the OEMs. Now our goal is to actively engage with the OEMs and engineering teams so that we can showcase our highway pilot, and also their test case scenarios that Sumit just talked about. We expect to ramp up efforts in G&A as we see more momentum from OEMs, both -- on both sides of the ponds in North America as well as Europe.

Drew Markham

Okay. And Sumit, I think this next question is for you. What can we expect from the company's demonstration of its ADAS solution by June 2022?

Sumit Sharma

I think what I highlighted before, I think let me just give a little bit of finer point to that. I think the test scenarios are very specific to highway pilot and some of the toughest ones that you would think that would cause accidents on a highway scenario. What we expect to do is we will run those scenarios and publish some of those data, if it's appropriate, if there's nothing proprietary from anybody else in there, if it's our data, of course, we'll publish it. But by June 2022, we would have track testing data, ground-truth data that demonstrates our capability to meet the features and start engaging with the OEM of what their requirements will be.

I expect that this is a big moment because these features and these scenarios, the story starts lining up better for what a highway pilot demonstration or a system would have to be. And this is not common out in the market yet. There's no clear understanding of -- because there's no regulations yet of what are the exact scenarios that you would have to achieve to be able to qualify yourself as a Level 3 feature at the high speeds. And therefore, we work very closely with the OEMs on that one. And again, I think we intend to share nonproprietary data, data that the company generates with the market, with our investors.

Drew Markham

Okay. A finance-related question here. Can you give us a sense as to what level of cash you feel is necessary to support the business? Why continue to keep the ATM open?

Anubhav Verma

So I feel good about the $125 million cash balance that was reported at the end of September 30, 2021, in the last 10-Q. Compared to our peers, I feel we're one of the better positioned companies compared from a cash burn and market cap perspective. ATM program is actually very strategic to us. The open ATM program gives us flexibility to raise capital as and when required. This ATM program actually allows us to compete with our peers who have raised significant capital we expect transactions in the last 18 months.

Also, the high liquidity in our stock being one of the highest average daily trading volume positions us quite well as compared to our peers in accessing capital markets in the future as well.

Drew Markham

So Anubhav, is MicroVision actively pursuing or investing in any non-LiDAR technology?

Anubhav Verma

At this point, we are actively pursuing the automotive LiDAR market because we feel confident about our strategy of partnering with the OEMs. However, as Sumit has previously discussed, there is significant value in some of our other verticals as well, and we stand ready to support potential customers, if needed, in those verticals as well.

Drew Markham

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

Anubhav Verma

Look, at this point, I feel confident about our strategy to pursue directed buy agreements with the OEMs, as Sumit and I discussed in detail. With our $125 million cash balance as of 930 and high average daily trading volumes as a public company, we get regularly approached to evaluate strategic alternatives, which we continuously do on an ongoing basis. But as we have previously disclosed, we currently have no agreements or commitments to engage in any specific transactions at this time.

Drew Markham

Okay. For those in the audience who may have further questions, who should they contact for more information about MicroVision?

Anubhav Verma

I would highly encourage you to contact our IR consultants, Jeff Christensen and Matt Kreps. Their contact information is in our press release. Please feel free to reach out to them with your questions, and we'll be sure to cover them in the upcoming events in 2022.

Drew Markham

Sumit and Anubhav, thank you for addressing these important questions. And a big thank you to the members of the MicroVision team for being here to demonstrate the clarity of our LiDAR sensor for today's presentation. And for those of you joining us from outside of MicroVision, thank you. Our employees are doing innovative work aimed at making our roads safer, and we appreciate your continued support of MicroVision.