Innoviz at Rosenblatt Summit: AI and LiDAR Drive Future

On Wednesday, 11 June 2025, Innoviz Technologies (NASDAQ:INVZ) participated in Rosenblatt’s 5th Annual Technology Summit - The Age of AI 2025. During the event, CFO Eldar Segla provided insights into Innoviz’s strategy focusing on LiDAR technology and AI integration for autonomous driving. While the company is optimistic about its growth potential, challenges such as market competition and production scalability remain.

Key Takeaways

• Innoviz is evolving from a technology provider to a Tier 1 supplier, emphasizing AI’s role in autonomous driving.
• The company is targeting both automotive and non-automotive markets, leveraging partnerships with Mobileye and NVIDIA.
• Level 4 commercial applications are expected to boost Innoviz’s volumes significantly by 2026.
• Market research forecasts a 10% penetration for autonomous vehicles by 2030, highlighting growth opportunities for LiDAR providers.
• Innoviz collaborates with Fabrinet to enhance production capacity and maintain flexibility.

Innoviz Overview and Strategy

• Founded in 2016, Innoviz focuses on LiDAR technology for autonomous driving.
• Transitioned to a Tier 1 supplier after qualification by Volkswagen.
• Initial partnerships with BMW and Magna provided significant automotive project experience.
• Expanding focus includes Level 4 commercial applications like robotaxis and shuttles.
• Aims to increase production capacity through collaboration with Fabrinet.

Level 4 and Robotaxis

• Level 4 applications deploy nine LiDARs per vehicle, enhancing content value despite lower volumes.
• Government support is facilitating deployment opportunities.
• Next SOP for Level 4 is planned for the next year, with volume acceleration expected in 2026.

AI Integration and Perception Software

• AI is essential for processing LiDAR data and enabling autonomous driving decisions.
• Innoviz offers a software stack with AI algorithms for object detection and tracking.
• Clients can select specific software components to suit their needs.

Partnerships with Platform Players

• Collaborations with Mobileye and NVIDIA are critical for OEMs seeking autonomous solutions.
• Innoviz is integrated into Mobileye’s Chauffeur and Drive platforms and serves as a reference design on NVIDIA’s platform.
• Integration helps OEMs save time and resources.

Non-Automotive Market

• Innoviz is expanding into non-automotive sectors, targeting smart cities and security applications.
• Leverages automotive-grade LiDAR for enhanced performance and cost-effectiveness.
• Focuses on applications that understand LiDAR’s value, such as smart junctions and security monitoring.

Fabrinet Partnership

• Fabrinet provides production capacity and flexibility, helping Innoviz stay capital expenditure light.
• Facilities in the US and Asia support global production needs.
• Fabrinet assists with working capital management.

Market Outlook

• A 10% market penetration for autonomous vehicles by 2030 is anticipated, equating to 8-9 million LiDARs sold annually.
• Every major brand is engaged in autonomous driving programs.
• Autonomous features are driven by safety, differentiation, and margin opportunities.

For more detailed insights, please refer to the full transcript.

Full transcript - Rosenblatt’s 5th Annual Technology Summit - The Age of AI 2025:

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Morning, everyone, and welcome to day two of Rosenblatt Security’s fifth annual Age of AI Technology Summit. My name is Kevin Garrigan, and I am one of the semiconductor analysts here at Rosenblatt. We were pleased to have with us Innoviz’s CFO, Eldar Segla, for this fireside chat. We have a a buy rating on Innoviz with a $4 price target, and we are bullish on the company because of their leadership in the automotive LIDAR space, design win traction, and inflection coming in 2026. So throughout the the fireside chat, we’re gonna ask for any questions from the audience.

To ask a question, you can click on the quote bubble in the graphic on the top right hand of your corner. I’ll then read the questions to Eldar. So with that, thank you, Eldar, great to see you again.

Eldar Segla, CFO, Innoviz: Thank you for having me. A pleasure always.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: So for for anyone listening that may not know the Innoviz story, I thought we’d just start out with a brief overview of of the company and, you know, what is Innoviz win in the market?

Eldar Segla, CFO, Innoviz: Yeah. Sure. So, I think when we started, we started back in 02/2016. Our main thought was that there is this new emerging technology, autonomous driving, and it’s missing a very important part in order to enable autonomous driving, in order to have the the driver really disengage from the driving. The system needs more sensing capability.

It had the camera. It had the radar. But still in order to disengage the driver and who have full redundancy for the system, you needed a type of sensor, and it was the LiDAR. LiDAR is basically a three d sensor or a three d camera, and this is how we set ourselves to, this mission. And on top of it, and very importantly, was the AI software, which basically takes the data and turns it into something meaningful for the rest of the software stack in order to have these feature available, in order to have driving decisions.

And I would say that these kinds of AI technology that were emerging were actually the enabler on top of the hardware that enabled this technology and these features to come into market, not only on the sensor side, but also on the software that they’re driving decision platform side. And once we started and to develop these technology both in the software and the hardware side, we gained the traction with the customer BMW. We were a very young company, a very young startup, so BMW requested to have another partner, a tier one partner to some extent buffer between BMW, the OEM, the carmaker to the technology provider, and we partnered with Magna back then. And during this process of, bringing this technology into the market and the BMW vehicle rolled out, last year, you can actually buy this platform or this car, I seven cars as of last year. We gained during the process, the development process, we gained a lot of knowledge, a lot of experience of how to run such an automotive sort of technology project.

And we understood that it’s very important for the OEM, this direct connection with the technology provider because of the different, flexibilities that we can provide, the different tasks that you take upon yourself in qualifying the technology. And we decided following the BMW project, as said, is already SOP ed. It’s already in production. We decided to turn and become a tier one. And our client was Volkswagen.

And when we competed on the Volkswagen programs, we approached them and offered them to be a direct supplier, give all the benefits of a tier one in terms of flexibility and the services that we can provide based on the experience we gained with BMW. And on the other hand, offer a more a better cost structure because basically you are eliminating at the middle tier one, which adds to the margin stack. And, it’s something that Volkswagen, after a very rigorous, audit that they did to Innovus that took more than a year, basically, which in which they audited every aspect of the company, not only on the technology side, but how we manage the company, risk management, quality, production, and so on and so They have qualified us as a tier one. And since then, the industry has accepted Innoviz as a tier one. And today, when we are approaching project, basically, we are approaching it as a tier one.

And I think the the maybe the the the last step, the the latest step that we we took is in two two two aspect. One is we started when we started the company, we were more focused on level three application, consumer applications because we thought it’s the biggest market. Around 90,000,000 vehicles are being sold every year to consumers, So we thought this is the biggest opportunity. But over time and together with projects, specifically Volkswagen project, it turned out that the level four, not consumer, but commercial applications, right, like robotaxis, shuttles, buses, and so on, are gaining traction because the technology is maturing. Maturing.

Mobileye, NVIDIA have put in place level four platform for commercial applications which are maturing. And on one hand and on the other hand, our technology matured as well with the capability of maturing our production capacity, and all this came together. And, we are today offering both level three applications mainly for consumer and level four for commercial application, which basically doubled our business opportunity. And today, we are looking at two main goals. A, win additional programs with our software and hardware, and b is to ramp our production line capacity, which basically we are using contract manufacturer, FabriNet.

It’s ramping up as we speak and will be ready before the SOPs, the main SOPs that are planned already for next year for the Innovus two. So this is, I I think, a short introduction to Innovus.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: I I appreciate that overview. So, you know, sticking with the l four and robotaxis, you know, they become a a big buzzword, you know, recently, and we’re seeing more and more investment. So how do you how do you kinda see that market playing out? And I I know you talked about it’s it’s becoming, you know, more mature. So do you see it kinda becoming full scale before kinda l three does?

Eldar Segla, CFO, Innoviz: So, so of all, I think there are already level three application consumer application that are rolling into the market, mainly, on the high end vehicles like BMW, Volkswagen, Mercedes, and maybe soon soon to come other OEMs as well. Having said that, we learned that and we’re seeing it happening as we speak that the level for commercial application are getting a lot of traction. And the reason is, I think, from two direction, a, the technology matured, but the business model makes a lot of sense because, basically, you have here a platform that eliminates the professional driver, like in a taxi or a bus or a shuttle, and it’s very easy to justify, putting a lot of sensors and technologies and softwares, into such a vehicle and having it ride all along in addition to the fact that it’s getting ever more, hard to get professional drivers, for these kinds of application, including trucks, by the way. So this makes a lot of sense. So technology maturing, and a good business model.

On top of it, there is some, I think, boost from the government from, I think the new administration has allowed, to deploy a greater number of vehicles per year. It was restricted until this government came the Trump administration came into place. So I think the restriction caused it to to not not to some extent, to slow down a little bit the the the penetration. But once these restrictions were lifted, we feel there is a certain land grab war between the different platform. You you see you hear announcements from Uber.

You hear announcement from Lyft. Obviously, Waymo, which is very far ahead as well at this. So we see a lot of acceleration. And in fact, for Innoviz, the next SOP, next platforms that will be deployed are the level four. The level four applications are planned for next year to the SOP start of production.

There will be already vehicles tested this year, this year and the beginning of next year. And then as of the half of next year, they will be deployed, which means for Innoviz, a sort of acceleration and additional volumes that will be expected already in 2026, and, hopefully, this will, even grow faster in 2027. On the level, three front for consumer application, we see it happening, or the next deployments will happen as of 2027 and beyond. So, actually, the level four we are expecting is the next, big step for Innovus, the next big volumes to be provided to the market.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Makes sense. Can you just kind of frame, you know, the opportunity for Innovis between, you know, l l three and l four, you know, ASPs, you know, volumes on on cars?

Eldar Segla, CFO, Innoviz: Sure. Sure. So the the level three applications that we see in front of us, as I the consumer opportunities are deploying one LIDAR per vehicle. The level four commercial application are deploying nine LiDAR per vehicle, three long range and six short range LiDARs all provided by Innoviz. And at ASPs, roughly speaking, between for for these kinds of application at the earlier year, let’s say between 600 to $800, then for the commercial applications, it means for Innovis, on average, you know, nine lighters times the ASPs, let’s say, few thousands of dollars, 6,000, $7,000 per vehicle.

So it’s very meaningful. So even if the expected volumes of vehicles is lower than the level three applications, the consumer application, still because of the multiplication of the number of LiDARs, this is very the content per vehicle is very meaningful. So level three is one LiDAR, few hundreds of dollars. Level four commercial application is nine lidars, few thousands of dollars. Very meaningful, even if the volumes are lower.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Yeah. Makes sense. Yeah. So so good good content for for Innoviz. So relating it, you know, back to AI, you know, how how have you guys seen automotive companies trying to incorporate AI or or machine learning, you know, into their platforms, into their cars?

And, I mean, has it kind of helped expedite any any processes at all or or not really?

Eldar Segla, CFO, Innoviz: So I I think without AI and without this, let’s say, the the these these platforms, these algorithms, the new algorithms, you don’t have autonomous driving. It’s simply impossible. And this is a significant breakthrough, and it goes in every level. So when Innoviz started, it was very clear, and it’s one of our differentiators that we are not only providing the hardware, the LIDAR, the three d, the missing component of a three d sensor that is required in order to reach autonomous, you feature. You have to put in top of it as some AI, deep learning algorithms, that take the data and turn it into something meaningful that this the the driving decision software or platform can use in an effective way in order to have driving decision.

And so this was very meaningful and it as said, it started from the sensor level. But then you have additional components, software components along the way that are also AI driven, let’s say, like the sensor fusion, and you can do sensor fusion, low levels fusion, high levels fusion depending on the architecture. And then even when you go to the driving decision. And there is a lot of AI both, let’s say, traditional classical AI, which starts very low at the very raw data, then may maybe the the perception software, is taking the the output and turns it into something meaningful object detection, classification, tracking, drivable areas can drive above, under, and other additional, important features and goes up to the stack. So without and going back to the opening statement, without AI, you don’t have autonomous driving.

It’s fundamental, and it’s fundamental in every, level, in the system.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: So very, very important for moving forward, I will say.

Eldar Segla, CFO, Innoviz: Yeah.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Okay. Perfect. So I’ll I’ll stop here real quick and and see if we have any any questions from the audience. Again, if you wanna ask a question, click on the the cool poll on the graphic on the top right hand of your screen, and then I’ll, I’ll read out to Elvar. Okay.

Yes. So one one other question that I I kinda had, you know, your your recent wins and and their their importance, especially with the the platform players, so, you know, NVIDIA, Mobileye, and even, you know, Qualcomm. Can you just talk about, you know, how important those are for for helping you guys out?

Eldar Segla, CFO, Innoviz: Yeah. So I I I think it’s helpful for us in more than one aspect. It’s it starts with that with the fact that I think these platforms, are an important key in order to have, these solution in an effective way because, putting a platform in place is is a costly, a very, complex task, and not every OEM is up to the task. I would I would say that maybe two, three years ago, the industry thought, okay, everybody will have a project. Everybody had some kind of autonomous driving project, and they tried, to get to the solution themselves with partners, without the partners.

But but the the problem is it’s a very difficult problem to crack. You need a lot of a lot of time, cover a lot of edge cases, a lot of engineers, a lot of cost. There in order to reach for a safe qualified system, it takes a lot. And I guess, many of the in the past, many of the project failed. And and today, basically, you have few very strong players like Mobileye, like NVIDIA that took this task upon themselves and are basically offering a solution that saves time and saves risk and cost to the OEM.

So basically, it’s an important maturity step for the industry. Today, when an OEM needs to go wants to go into these kinds and they are seeking, to offer these kinds of features, they have already the main building blocks ready for them. They have the sensor suite ready like a LiDAR, you know, with LiDAR, which is ready and mature and already deployed, the software in place, the platform themselves. So being integrated into Mobileye platform both on the level three, the chauffeur platform, or the drive platform, being integrated and being sort of, I would even, dare to say a sort of a reference design on the NVIDIA level, helps Innoviz to win business because we can say, okay, we are already working with these platforms or integration compatible to these. And, the OEM saves time and saves resources.

He doesn’t have to start all over, and he can make a decision and have his solution ready on time and in a reasonable, cost. So it’s it’s you see that the whole technology, all the components are maturing and are ready. And we I think we today, we are at if a few years ago, we are in a certain hype phase. Today, are in a certain maturity phase and production phase, which is much better for all everybody, all stakeholders, in the industry.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: That that makes sense. And your your partnership with Mobileye, you guys are are the sole provider that, you know, if if they get a design win and the the customer says, hey. I I wanna I wanna use a a lidar, they would go specifically to you guys compared to, you know, NVIDIA who has a couple of different partnerships. But, you know, you you may be trying to do the same thing with them. Am I am I thinking about that right?

Eldar Segla, CFO, Innoviz: Yeah. So I I would say the following. It’s NVIDIA, by the way, has more than one platform. They have the Orion and they have the drive, the the Hyperion drive platform. And the the it’s more to, how the this industry is working.

Usually, Mobilize offering a closed box solution. It doesn’t mean that some OEM cannot decide that for his own reason he wants to use different sensors, not only Innoviz, different camera, different radar, but the cost of doing this and the risk of doing this and the time it takes in order to qualify a new platform with new components, also on the NVIDIA side, it’s even though it’s, let’s say, it’s more open, eventually, at the end of the day, the de facto logic is, we go with what is already available, what was already qualified, the technology that is already deployed and is has gained, some experience in the market because we we have always to think what this technology does. This technology drives cars without the attention of the driver, and we cannot have that this car will do an accident, run over people, and so on. So this is a mission critical functional safe component or feature, and it and once something was qualified, so usually the OEMs tend to stick to the what’s working and not try to, a, spend money more money, more time, and a lot of risk in qualifying different technologies.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: That makes a ton of sense. So, you know, it it looks like you guys are are making a little bit of a bigger push into the the nonautomotive market. So how do you how do you view that kind of market developing? And, I mean, do you guys feel like you can be a winner in that market as well?

Eldar Segla, CFO, Innoviz: Yeah. So I I I think it has to do something in the fundamentals that or the way Innoviz thinks Innoviz always, I would say, took the longer, more strategic route to to to reach its goals simply for the fact because there are no easy shortcuts. And we decided when we started strategically to focus on the automotive market because we thought this is the biggest opportunity, but it came with the price. It’s much more, difficult to provide for the automotive space. You you need to meet very stringent qualification and requirements, and also you need to meet a very, aggressive, price point, ASP.

And we decided to focus there. But once we reach maturity in automotive, and now we are ramping up our capacity, we are starting to look at other opportunities as well because we can provide for them. So and and there are already applications that over time, other application like in security, like in smart cities, smart junctions, smart infrastructure, industrial that are already using lidars and they are looking for better and cheaper, more cost effective solutions. And Innovus can today provide them because we have an automotive grade lidar, which is very good, top performance. But on the other side, it has, the the the cost effectiveness of an automotive solution.

So, we are looking to tap into applications that already, understood the value of sliders and already use sliders, and it’s relatively basically, they approach us. It’s not something that we that the whole company is now set to pursue, but rather have very few partners like big integrators that have already projects that are requiring LiDARs and stream or or offer our solution into these ready made application or projects.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: And how does does the how does the LiDAR sensor differ, you know, in in the nonautomotive market compared to automotive? I mean, can you use the same the same hardware for both markets? You just change out the software, or how does that kind of how does that kind of work?

Eldar Segla, CFO, Innoviz: At least our application is a very simple answer. Yes. We are, in many cases, providing more than is required by the industry and in a much more effective price point. So it’s very easy. The LiDAR the performance is very high in many aspects.

So the learned also that most applications are requiring exactly the the the the sort of LiDARs that we are providing, so we don’t see any any, I would say, for us to enter into these kinds of applications.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Yep. Got it. Got it. Yeah. I know yesterday you guys had announced the the Innovus smart, but I think, you know, smart cities are are very interesting use case for for nonautomotive, lidars.

You know, you’re seeing a lot of a lot of governments these days just talk about AI and, you know, incorporating them into, you know, anything and everywhere possible. So I guess, you know, on smart cities specifically, what are the the big kind of use cases you guys are are seeing that you think, you know, LiDAR could could be good for?

Eldar Segla, CFO, Innoviz: Yeah. So since this basically, you can think of the LiDAR as a three d camera. So, basically, wherever you have a camera, you might think, you can you could use a LiDAR, and the LiDAR has few benefits. A, it is an active sensor, so it sees at night, and it’s less prone to, you know, the sunlight, getting direct sunlight so it got it doesn’t get blinded and so on. And in addition to that, it provides instead of two d data, it provides three d data, which is much more easy to process.

So in any, scenario that, for instance, smart junctions to to monitor and control traffic, it’s very clear to understand how the traffic flows because you get the three d data or restricted areas. It’s very easy to monitor areas, for security or other reasons that you want to restrict because it’s a three d sensor. Definitely in in smart monitoring of of crowds, like in airports or in any other such application or security smart smart fences, like the, you know, in The US, There is always the talk about the fence, the smart fence, between The US and Mexico. So so all these kinds of application can benefit from a three d, sensor that can provide much more, much more data points, than a two d sensor and can be more resilient to different environmental conditions.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Okay. Yeah. No. That makes a ton of sense. And then, you know, in your prepared remarks, you know, you talked about Fabrinet and how important, you know, them being a contract manufacturer for you guys is.

So can you just talk about, you know, the importance of them to your your kind of growth trajectory?

Eldar Segla, CFO, Innoviz: Yeah. Of course. So of all, we are a tier one, so we are responsible of the production. In essence, we plan the production line, the process. We, we are responsible on the testers and some, the the machines that assemble a LIDAR or the optics and so on.

So, but then using a contract manufacturer gives us all the benefits of using a contract manufacturer, in terms of relatively staying CapEx light, having a partner that has the capacity or the experience in automotive production and meeting automotive standards. And and, of course, having facilities not only in one place, but giving us the flexibility based on our customer customer needs. FiberNet is deployed in many places in the world, mainly in The US and Asia, And this gives you full flexibility to give, the the required, or answer the required needs of our customers. And the importance, obviously, is once this production line is up and running, then we have the capacity to provide for our clients, mainly the automotive clients, but also outside the the automotive space. And another important aspect of that is that Fabrinet is a partner that can take some of the burden of the working capital needs as we ramp over time.

So having a a strong partner that can take some of the burden, of that is also important. So it answers many needs of the company.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Not having to, not having to spend on on CapEx for for something like that definitely definitely helps cause.

Eldar Segla, CFO, Innoviz: Thanks.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: So, you know, relating relating everything back to to AI, I mean, how how are you guys kind of incorporating AI into, you know, Innoviz Innoviz the business? And on on kind of the the perception software side, you know, you talked about it a little bit before, but, you know, how are you guys using, you know, AI machine learning for for your perception software?

Eldar Segla, CFO, Innoviz: Sure. So Innoviz is providing a software stack which, has, many elements in it starting with very low level, I would say, sort of image processing, which is three d image processing. The output of a LIDAR is what we call a point cloud, but and this is something that needs also processing in order to get a very good point cloud. And then from that, we have additional additional software elements that are using different kinds of AI algorithms up to the, let’s say, the top of the stack, which is the perception software, which is using deep learning algorithms, which basically do the object detection classification and tracking of objects and other important features for the car, understand the way it can drive and where not, where is the sideway. If, I’m driving in front of a truck, can I, how close can I get if it has some kinds of beams outside of it?

So a better understanding of of the environment. Can I drive under something? Can I drive above something if there is some debris on the on on the road? So so there are many aspects that we take care of. And then when we are approaching our clients, they can choose, which part of, the software they they would like to use for their needs.

And, obviously, we price it differently. I I believe it’s a very important differentiator because it’s something very specific to a LiDAR today. LiDAR is still not generic, so each LiDAR is different. And, because we are very intimate with the hardware side, we can provide much better software, which is very well tuned for the hardware and eventually giving a very good software stack to our clients that gives, at the end of the day, gives them them a very good understanding of what the LIDAR sees. So this is, very important.

And, again, I said, we offer many tools. It’s not just one element, but it’s a few elements that we have in this stuff.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: You know, I know there are multiple layers of of the software stack, you know, you know, vehicle, But, you know, is is it easy to to work with, you know, the the ADAS platforms who are also, you know, developing, I know, a higher level of software, but is it easy to just kind of, you know, combine software stacks with them?

Eldar Segla, CFO, Innoviz: Yeah. So it of all, the the answer is, I wouldn’t call it easy in terms of the collaboration. It’s easy. In terms of the technicalities are working, you need to do the integration. Obviously, when you are working with the platform like Mobilize, so Mobilize is an expert in perception software.

But still, they will require from from us some elements of our software. Some of them are AI. Maybe some of them are more traditional AI software systems, but or elements, I would say. But but, yes, they would like us to provide the best output that we can provide them, and it doesn’t end by just the raw data of the LiDAR. They are happy to get from us some additional the the the output from some of our software layer, even not maybe the the perception they can do themselves, but definitely some lower level AI features that we offer, definitely they are using for on their system.

So it’s a nice collaboration and there is a very nice synergies between the hardware, the software that we are providing, and the platform itself, like NVIDIA or Mobileye.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Okay. Yeah. No. That makes sense. Okay.

So I know we only have have a couple minutes left. So I guess just the, you know, the the last question that I kinda had. You know, what are what are some of the most significant trends that, you know, you you foresee impacting the automotive sector, you know, in the the next five, ten years? And then also, you know, how do you view the current state of the LiDAR market today versus, you know, how it how it may be in, you know, five to ten years?

Eldar Segla, CFO, Innoviz: Yeah. So, yeah, usually, what I’m I’m I’m quoting here is the the the the market research that we we have in end. Usually, I’m quoting the IHS number, the SMP market research that is around the consumer application level three, level four. And at least to our understanding, this predicts that in 2030, there will be, something that looks like a 10% market penetration, approximately 10% market penetration, which means for us, you know, if, if the industry is selling 90,000,000 vehicles per year, it means, you know, something like eight, nine million, Lidars, being sold, in 2030. And for us, it’s very good number.

Reaching a few millions of, of sliders a year, is very meaningful, very significant for us. And We think we think the industry is on that path because at least on our side of the pipeline when, you know, when we are looking at the programs, the different programs that we are competing on, basically, every name, every brand name that you can think of, major brand name, has some kind of a program underway at different stages. And the industry definitely is going towards adopting autonomous features from both because of safety consideration, but also because of differentiation and margins. These kinds of new features provide, the margins that the industry is looking for, nice margin. So the the industry is definitely motivated, and the the technology has matured.

We are in a mature much more mature stage. On top of it, definitely and as I mentioned before, we see that the that the commercial application have reached maturity as well. And they as I said before, they are looking at it from a different angle. They they it’s very clear for them the biz the business model that makes a lot of sense, that has a very definite, very clear ROI, return on investment. And, since this has matured quicker than we thought initially, we see it as a very meaningful opportunity that basically doubles our business opportunity that we see in front of us up to 20 thirties.

So we feel very strongly that the market is maturing both on the consumer and the con and then the commercial application. And, hopefully, Innovus, we can be a very meaningful player in this market in these markets.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Yep. Yeah. And as we said before, you know, starting today and even, I think, 2026, we we see an inflection. So we’re, we’re looking forward to kinda seeing how everything plays out.

Eldar Segla, CFO, Innoviz: Sure.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: But, you know, Anurag, it looks like we’re just about out of time. So I I appreciate, you know, you joining us for for the conference today.

Eldar Segla, CFO, Innoviz: Sure. Thank you very much for inviting me. Always a pleasure, and hope to see you soon.

Kevin Garrigan, Semiconductor Analyst, Rosenblatt Security: Yeah. Alright. Have a great day, everyone.

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