Ambarella, Inc. (AMBA) Earnings Call Transcript & Summary

Great. Thank you. Welcome, everybody. I'm Joe Moore, Morgan Stanley Semiconductor Research and very happy to have with us the CEO of Ambarella, Fermi Wang.

Thank you.

Fermi, thanks for being here.

Maybe we could start out the AI focus. We talked a lot about edge AI a year ago, but the focus has really shifted to data center, but there's a lot of activity in the edge space, and you guys have pivoted nicely to sort of attack that. Can you talk about that? How -- before we get into the details, just the enthusiasm you have for the edge AI opportunity and what it means to you?

Right. So in fact, that edge AI really developed fast, although data center take all of the investment and focus for AI side, but edge AI definitely really developed very quickly and very nicely for us. First of all, everybody talk about robot today, which is a portion of the physical AI we talk about. We all believe that's going to be a huge market down the road. But today, most of the volume that we are focusing on is still from the enterprise security to the portable video to the drones, those we talk about a lot. But at this earnings call, we talk another thing, which is very important for edge AI is really we believe. In the past, we talk about edge endpoints, cameras. But this time, we talk about building an AI box, not sitting in a data center, but sitting at the edge, which aggregate all of the different sensor input and apply GenAI type of model on top of that to serve totally different purpose. Just to give you one quick example. For example, at the CES, we demoed with one of our software vendors that they collected the security camera feed to this AI box at a retail store. And with the new GenAI, they can turn this security camera into operational tools that can monitor how the customer comes in, what they buy and collect the customer data. So suddenly, security camera become your operation tool for your efficiency. So those kind of new applications that you can think about almost all retail store or any other operation can take advantage of the installed base of video feed and using AI box to turn into a different application. That excites us because that really take a very little investment, you can turn on a huge market opportunity. But the requirement is for each application, you need a software vendor to write software on that. We need to have a system integrator to integrate that box into existing infrastructure of the retail stores. And those things need to be -- we need to find partners to that. So for us, we enable this, we call edge infrastructure business. We are working with ISVs, with system integrators to enable. That's another market. So we feel excited because we're starting more and more edge AI application popping up, and we believe eventually the robots will be there driving huge volume. But before that, we see continuous of new application popping up, and we're going to continue to serve that.

You had some really interesting demos at CES, which is not new for Ambarella. You've had great demos for a decade. What's new about it is the pace of implementation seems really rapid. We talked to guys where you made your software available to them months ago and they're productizing it already versus automakers that have taken many, many years to get to production. Are you surprised by that? Are you seeing opportunities that you weren't aware of as you've opened that up?

First of all, I'm surprised how fast our software vendor can really adopt our platform, but it's by design. 5 years ago, when we start looking at talking to a customer, customer biggest complaint is every time we switch from one silicon to next silicon, I have to port your software over. That's time consuming and waste a lot of resource. Why don't you make your software is portable? And that's where we start coming to do this Cooper Development Platform that will allow us -- our customer to pull application from one of our chip to another chip without too much effort. That takes time for us to build the extra layer so to separate out the hardware layer, but keep all the software layer open so that our customer doesn't need to spend a lot of time to port. It takes a few years to reach that. But as soon as we reach that flexibility, this ISV demo you saw, we give our Cooper SDK to them 3 months before CES, they port the software over from our competitors' platform to us in less than a few weeks and start demoing at CES. So that just shows you when you have this not only a very powerful silicon platform, but a portable software platform that really help our customers to enable new application quickly.

And I shouldn't really say that's new in the sense of Conti and Bosch said the same stuff. It was really fast for them to productize that. Of course, it's taken a very long time for that to turn into revenue, which is a different question. But you've always had that kind of software flexibility built into the system and kind of a software-first mentality to development.

Absolutely. In fact, today, we fully recognize that building 2-nanometer silicon takes time, but it takes even more time for our customers to port software because that's out of our control, make their life easier, it's helping us to get time-to-market.

And what other IoT applications do you see emerging? I mean you've always been near dominant with surveillance camera companies on the professional side, you've always seen a lot of opportunity to do stuff with those kinds of image data. Consumer has been a little harder because of the margins and things like that. But as you see new opportunities, do you think those can open up? What -- and are some of the new opportunities seem like there are opportunities before they are coming back like drones. But just how are you thinking about IoT now as a market?

Well, in fact, for IoT, there's also a market we talked about in the past is a called wearable cameras. In the past, wearable cameras for policemen only. Today, we start seeing the wearable camera goes to the clerk at the retail stores, right? Because everybody wants to document what happened, interaction between the service people to the customers, and that becomes a really big market. But in fact, I want to mention another important application that we never talked about 2 years ago. For example, the edge AI technology going to fleet management. In the past, fleet management is just using GPS to identify where the car is. Today, with AI-enabled camera and the telematics information, not only you can enjoy using AI to help you to detect the environment so like more safer driving environment, but also use that to provide more information about the condition of the drivers, the cars, the products and the storage in the truck. And with those information, they can build even better service to the fleet management customers. So that, for example, Samsara is our biggest customer in that space. We see huge growth from them just in that space, and we're also seeing that almost all the people in that space start adopting edge AI. That's just one simple example that edge AI can apply to almost all the business to help them to get more productivity out.

Okay. Great. Maybe we could talk a little bit about the business. You had a nice growth year in 2025, good product cycles with CV5 and now starting CV7. You sort of started this year with a little bit more of a moderate view of this year's growth. Just how are you thinking about those growth dynamics?

So when we look at fiscal year '26, which is last year, when we started Q1 last year, our first guidance of the year was high teens, but we end up growing 37%. So what happened was that at the beginning of the year -- we were very confident about our own product ramping up growth, and we know that we're going to ramp up the product on time. But what comes to surprise, pleasant surprise to us is our customer ramping up faster than we expected. So that's where we get this really outstanding growth last year. This year, we're standing in a very similar position. Our -- we are very confident in our new product ramping up, including CV75, CV72 and CV7. And in fact, we know that our first 2-nanometer chip will ramp up first half of next year, which we've already seen that. So we are quite confident about our own product ramp-up. Now what we are trying to do is understand our customers ramp up with the new product second half of this year. This will determine how well we're going to perform this year.

So you might be conservative again, but you want to wait and see how that pans out.

You know me. We try to be conservative all the time.

Yes. For sure. Okay. And then maybe just speaking of earnings to clarify the Insta360 lawsuits. Ironically, the night you reported the stock was down a lot on a lawsuit that doesn't seem to have much fundamental impact.

Well, in fact, that somebody -- one of our investors texted us when we're still in that conference, think about that. Fortunately, nobody asked that question because I don't know the answer. But fortunately, after that, we start talking to our customer and also they made a public announcement that there's absolutely no impact to them. Therefore, there's absolutely no impact to us because of lawsuit. They -- obviously we have done a lot of work to work around the patent getting -- the product that involve the patent. So from our point of view, there's absolutely no impact to us.

Okay. Great. That's helpful. I guess going back to IoT, as you think about consumer opportunities, you've had a lot of ramps of drones and then you sort of got priced out of the market a little bit. Same thing on doorbells, things like that. How do you think about that? I mean, on the one hand, the technology requirements in those markets are going to grow as you actually incorporate AI, so you can get those kinds of premium margins. On the other hand, is there a merit to thinking about a lower gross margin model so that you can participate more in those opportunities?

That's absolutely true. We definitely want to play on the lower gross margin to -- as long as they give us better leverage on the operating point. But I also want to point out one of the reasons that people can -- the low-end product or lower-priced product come in because there's no other feature differentiation. Then the price become only matter.

You start putting resources into holding a declining margin.

That's right. So what we are trying to do is we are trying to invest on the market that we continue to see differentiation. AI, particularly edge AI, when we start doing a CV2 family, you need, I don't know, 2 TOPS, 3 TOPS performance. Today, our customers may say need 20, 30, maybe 50 TOPS performance because the applications require more and more AI performance. One is because of application, the other one is because of GenAI model, which is really big, and that requires a huge amount of AI performance. So as long as we can continue to offer differentiated technology and the ASP continue going up, I think that's market we can continue to maintain not only the growth, but also ASP and gross margin. Any market when it happens that the price is the only thing matters, that's where I think we should consider maybe minimize the investment in the market and try to milk it through. But AI, edge AI way ahead of that point yet.

Yes. I mean it seems like when you're incorporating AI features, there's a lot of headroom. It's not like your 4K, 120 frames per second and trying to get to the next thing.

Let me use an example. Our new chip CV7, which is our first 4-nanometer chip and the CV5 is our first -- was our first 5-nanometer chip, CV7 have 2.5x AI performance than CV5. Just within 2 years, our customers are demanding that kind of performance increase. And I can say that for sure that our design-in activity with CV7 is huge in terms of multiple different applications. So you can see that -- we can see that there are definitely applications want to have more and more AI performance and the CV7 hit the right spot.

Great. And other categories within IoT, this portable video and others, and obviously, Insta360 has become a biggest enough customer that we had to worry about that stuff the other day. How do you think about that part of the market? It seems like there's a lot of really cool stuff on display at CES around that.

Right. So first of all, before this kind of the video product coming out, cell phone kind of take over that they become the best video capture devices. But if you look at the product built by Insta360 or DJI for the drone, for the 360 cameras, I think we can argue that they have a much better video capabilities than cell phone can be. So from that point of view, for anybody who are interested in capturing the highest possible quality video or for the YouTuber that want to capture their own production video, that become a popular device. So that's where we see huge growth for the total TAM of this kind of video capture device. So we feel comfortable that the market is going to continue to grow because the differentiation is on AI on the video resolution side. So we definitely think that's a market we want to continue to focus on. But we also realize that it's having one really concentrated customer might not be the best for the company. And the way to do is not to lose revenue from that, but try to create more revenue source on the different market. And that's exactly what we're trying to do, get more AI application that we can address our current silicon and software solution and try to really dilute that concentration.

Great. So I want to pivot and talk about cars. I continue to be a big believer in your technology for ADAS applications and particularly advanced levels of autonomy. And the market just hasn't really gotten there yet. So I still feel like the opportunity is there. And it seems like you guys also are still investing for some of those opportunities even if you're sort of having the burn not talking about it as much. But just how do you think about it? I mean, ultimately, it seems like we can't just ignore what Tesla FSD is doing, what China cars are doing in the autonomy space and just not start to follow down that path.

Right. So first of all, we definitely continue to work on those autonomous OEM design wins. One of the important reasons is that not only we have technology, but also we -- throughout the process, we learned how to compete in that space. Although that we lost VW, but after the VW case, we get more recognition on the space, almost all the new RFQ, RFI tend to invite us to bid on. So from that point of view, we get better visibility even we lost the VW case. And in fact, that reflects on our auto opportunity we disclosed this time, right? We talk about $13 billion total auto opportunity we identified for the next 6 years compared to what happened last year, this number goes up. That just -- that's a fact reflects that we continue to bid on more projects. I also believe that autonomous driving is going to be a very important occasion. I think that any design win can drive meaningful -- sorry, a meaningful revenue change. But more importantly, I really think that the software and the silicon investment we put autonomous driving, now we start seeing that can go to robotic, will go to drone application. Any autonomous drone will require similar software and hardware requirements as we develop for CV3 as autonomous solution. So from that point of view, we are convinced that if we want to stay any kind of mobile robot market, our current investment is important. So maybe the combination of that existing business we need to bid on and also future opportunity, we need to continue to have investment on that.

I mean it still seems like the technology that you showed with Continental and Bosch is better than anything that's been implemented in cars so far, at least outside of Tesla and China. So that was 7 years ago, no? It's been a long time.

5 years ago.

Really big breakthrough kind of technology that has yet to just be adopted. And I guess what -- and you referenced the VW situation specifically. What is the challenge? Is it that people in that world are reluctant to bet on smaller companies from a supply chain standpoint? And what needs to happen to close that gap?

Before VW, I really think that our company size is a problem. And for any design win, we need to go in, not only talking to their purchasing people, engineering people, but also the top management to explain why a company that like Ambarella can compete with NVIDIA and Qualcomm in terms of technology, sometimes hard to convince them. But that -- I think we overcome that problem. For example, VW at the end, we talk about this. We lost the deal because our competitor put a financial deal in front of our customer to offset the decision at the end. So we think that if that happens, again, we know how to counter-offer that. And also that we continue to see more and more deal. I think we are in a better position to address this before. But I still believe that working with Bosch and Conti, those large Tier 1s continue to be important for us.

But if you have progress where you feel a high percentage chance that you're going to win something, you're probably not going to tell us about it until it becomes revenue. Is that fair way?

Actually we learned from the lesson. Until we confirm that, we don't...

So the fact that you're not necessarily pointing to the funnel anymore, it doesn't mean that they're not -- there isn't still a vibrant funnel opportunity.

Well, in fact, that our funnel growth -- actually not funnel, the auto opportunity growth, that's just indication that we continue our effort to make sure that we can win something in the near future.

Yes. Okay. That's very helpful. And then this idea, I mean, you can teach a car to drive itself. There's a lot of other things that you can teach robots to do and devices to do. I guess how much have you thought about those opportunities and the focus on the humanoids robots and all the super futuristic stuff. But when you talk about military applications, defense applications, it seems like your technology would have really viable use cases in those markets.

Right. So anything -- in fact, any mobile robots can take advantage of our technology, both on hardware and software side. So all the applications you talk about, definitely that can use our technology. I want to emphasize is that moving forward, if you want to do any like humanoid, although I think it's going to be far away from the high-volume production, you need to have a very powerful GenAI type model, end-to-end model to control robots. And just from that point of view, my personal belief, humanoid is more complicated than Level 4 cars. Level 4 car drive in an environment is well controlled. You have traffic light, you have sign, you have things. humanoid, you have no limit working environment. Anything could happen. So from that point of view, the model you need to develop so to guarantee not only it works and functional, but also has safety concerns, security concern, all of that, it makes things very difficult. So what I try to say is that's a road map. I think we talk about what kind of market we want to invest. We want to invest -- there's a road map that we can continue to offer differentiated technology. That's where we want to be.

Okay. And your software-first approach is helpful at driving those opportunities?

Absolutely. In fact, that you really don't want to put a water cooling system into your robots, right? You have to have be power efficient. From that point of view, that you have to make sure that you design a chip for this application, right? Obviously, that people are going to using whatever they can access to, most like GPUs to prototype or generate first generation, second-generation product. But when you come to really mass production when the power efficient matter, when the cost matters, you need to have a chip that designed for this application so that it can minimize not only the power, but also minimize the cost. And that's -- and also minimize the DRAM, which has become so important this year. So all of that is the reason I think that a chip that designed for specific application will win at the end.

And you talked about a warehouse robotics win. That's a market that actually historically hasn't used as much vision maybe as what we're starting to see. And you've seen cobots and things like that don't even have vision capability. Is that changing now? Are you starting to see the need for that?

The particular design we mentioned in our earnings call is using a video as a -- and basically, the chip aggregate multiple video camera sensors and along with other sensors and do a sensor fusion for the perception. So that's exactly the usage for this particular application wins. When I talk about robotics, we offer three types of different products. One is just one single camera using to detect object, which is very simple. The second product we are offering is a perception box that taking multiple inputs and doing a sensor fusion, then you identify the environment object. That is the product we talk about in this. The third one is really, I think, the final solution, which is domain controller using one single chip to control the whole robot, not only perception, but also path planning, controller movement, functions of the moving arms. All of that within one controller, that's where is not only you need a powerful AI processor, but you need an end-to-end software model. That's where I think it's...

It's sounds a lot like CV3.

It sounds like CV3 but having more higher performance than that. So we are talking about the design win we just talked about is really about perception box sitting in the middle.

Okay. And does it require -- I mean, you sort of talked about a full stack approach in automotive, but this is going to be a much more fragmented customer base. Does that require allowing them to do more of the heavy lifting on the software side? Or how do you go to market in these kind of more fragmented spaces?

First of all, I think we want to demo. We need to have a software that we can demo the basic function like perception, planning, movement, all of that. But however, like you said, each robot requires different controllers. We -- there's no chance we can develop all applications for all the robots. So what we need to do is really working with our software partners, system integrators so they can help each customer to optimize the software and the models. And that is a new business model we talk about at CES. We want to work with a partner like ISVs, system integrators or the OEMs to build a complete solution for customers, and they can maybe even add their own software on top of that. This kind of overall development platform need to be ready, not only for robots, but also for edge infrastructure box that we just talked about.

Okay. And can you talk about semi-custom ASIC types of products in the context of all of this?

This discussion started with our first 2-nanometer chip that we taped out at the end last year. And when we started this project, one of our customers approaching us, hey, I'm interested in doing a semi-custom chip with you and by adding some of the special sauce into our chip, but they don't want to pay for the whole.

I was going to say they know what a 2-nanometer [indiscernible] cost?

The reason they came to us because nobody wants to afford that 2-nanometer chip payout. However, so the trade-off is they pay for a portion of the fee, but allow us to use that chip to sell to people -- to customers not competing with them. So those arrangements definitely is a win-win because that cut back our R&D cost to develop the first 2-nanometer project. And since then -- since we started talking about this, many customers and many new customers come to us say, we are interested in similar deal. But then they become us is what's our ROI, how do we determine who to engage, who not to engage and how we -- is that a real business for us? We are at the stage now we need to make a decision by engaging maybe 2 to 3 customers to size up the opportunity, understand how difficult it is and also go through the ROI to make sure that we build a business that we can justify in the long term. If we decide to do -- this is going to be a long-term business for us, then obviously, we can ramp up our go-to-market team as well as VLSI team. But most important thing is that we need to make sure any customer come to us, they want to leverage first, our IP, our video processing IP, our AI inference engine, our low-power technology as well as 2-nanometer technology. So if anybody wants to leverage those combinations, it's a good customer. But at the end, it's ROI decide whether that's going to be a business we get to engage or not.

And how are you thinking about 2-nanometer in the sense of CV3 was a really expensive chip that didn't ever get the traction that you wanted? And 3-nanometer, do you have to replicate that investment at 2? Or are you able to sort of focus on these more project-oriented or sort of defined application-oriented 2-nanometer products?

For 2-nanometer, we definitely try to -- when we tape-out any 2-nanometer chip, we need to identify not only just a customer but potential sales, right? So we have been very careful about defining what kind of 2-nanometer chip we want to build. There's a guaranteed customer and guaranteed market for us to enable 2-nanometer. So from that point of view, we are not going to do another automotive chip at 2-nano anytime soon. But we are going to focus on the areas we know there's a customer demand and also have a high-volume potential already. So I think from that point of view, 2-nanometer has become I think important for the power-efficient solution, if you really care about lowest possible power for robotic application for any other edge AI application, 2-nano become must-have.

And the state of your 2-nanometer comes from Samsung, you're very confident in the process technology underlying it.

We are getting a lot more confident than before. First of all...

Does it help that Elon is putting a lot of volume through...

Of course. When Elon announced it, I feel so happy because I don't need to be the only one defense [indiscernible] anymore. But however, I think throughout the last 12 months, working closely with Samsung Foundry on this process technology, we get to a point that we believe their yield will be not only acceptable, but also good enough for going to production. We are going to go production first half next year. I think that will happen. But more importantly, it's not only us saying that, there are multiple other large companies are saying that. So I think from that point of view, we are getting very comfortable that, that will happen. And more importantly, working with Samsung become an advantage to us because that TSMC has been telling people they don't have enough capacity for everyone. Samsung not only have enough capacity for us, we secured all our capacity that required for 2026. And we also secured the 2-nanometer capacity for 2027. So from that point of view, I think that Samsung definitely help us to give the confidence to our customers that they don't need to really worry about the supply chain for many different reasons.

Yes. That's great. I just have one more question and open it up to the audience if there are any. I mean just you've reinvented the company, I think, really for the third time on all of this, starting out is sort of video processing and then incorporating AI capabilities and now sort of pivoting more towards the edge. I guess what is that -- where is the endpoint of that? What do you think the business mix looks like a few years out? I think automotive, given the SAM's commentary is still going to be a big part of it. But how are you approaching resources to automotive versus these other edge AI markets?

So even for automotive, I want to make clear that we are focusing on the project that can generate revenue. In the -- at the beginning, we focused on developing technology and invest heavily. But now we kind of reposition that for automotive, let's focus on the project that we know is going to generate revenue. That is a different -- huge change for us. But I think it's more important to address your first question is what's -- how do we see this company going to evolve in the next 5 years? I really think that edge AI will become a lot more visible in the next 5 years. Today, 95% of AI investment go to data center. I think that will change. And that will change because that you need to deploy real-time location based on AI. Everybody talking about even OpenAI says they want to build the wearable device. Guess what, that's an edge AI device, right? So I think that we still don't know what's the most -- the killer app for edge AI, yet we start seeing a lot of smaller market, but we believe that will happen. So from that point of view that we will continue to invest heavily on the edge AI side, not only just on the video. Video is definitely our cash cow and we're going to continue to milk -- develop project on that. But we also see that on the digital AI going to AI box to aggregate. That's also a huge investment. But edge AI will be the key platform and key area we're going to continue to play.

That's great. Let me see if there's questions from the audience. If not, we can wrap it up there. But Fermi, congratulations. It's been a really successful year for you and everything you've achieved is really putting the company in an interesting place.

Thank you, Joe. Thank you very much. Thank you, guys.

Thank you.