Welcome to day two of Citi TMT Conference. My name is Kelsey, one of the analysts here at Citi covering U.S. semis. We are very excited here today to have Fermi Wang, CEO of Ambarella, here with us to discuss more about the company and to share the outlook. Perhaps to level set, Fermi, could you give us an overview of the company's heritage, portfolio, and also what opportunities you are the most excited here today?
Right. Thank you, Kelsey. First of all, thank you for joining us today. Ambarella is a fabless semiconductor company started in 2004, and throughout the years we are starting focusing on digital video application. In the last 10 years, we really focused on building solution for edge AI processing. Basically, what we are saying is that we're building an SoC that integrate not only just an inference engine, but also image processing pipeline, CPUs, and the peripheral so that we can become the SoC for the whole system. There are so many different vertical we are targeting at. Anything related to the edge device which will require AI inference, we are basically in there. The biggest markets like enterprise security to the portable video to the telematics for automotive, and now we are talking about robotic application.
In the latest earning call, we talk about how to penetrate edge infrastructure with new partners like Capgemini and Macnica. Basically, we are really focusing on edge AI for the last 10 years, and hopefully the market can start taking off as people expected. But definitely, that's really what we are focusing on.
Right. On that front, what are you seeing today that gives you that confidence that we are reaching an inflection point for edge AI? We have seen a lot of news flow on acquisitions, that big analog companies acquiring smaller edge-related companies. Could you talk about that a little as well?
Right. First of all, I think all confidence is based on our engagement with our customers. In fact, all of the customers we talk to, they all want to put more and more AI performance into the edge device. 10 years ago, it started with a CNN type of neural network, now they moved to transformer, then moved to large language model. All of that are available in our silicon hardware and software platform. The one thing that became very obvious in the last 12, 24 months is everybody wants to continue increase the AI performance on their device, mainly because of the large language model. However, edge AI or physical AI, people have been really talking a lot about, but the biggest problem for this market today is there is no one vertical like coding for data centers, right?
Today, majority data center revenue is generated by one big application, but there is no such application at that edge. That is where our strategy always focuses on multiple different possible vertical, and hopefully one of them will grow. You talk about the acquisition, Analog Devices, Inc. just announced a deal, which will acquire a startup company for $1.5 billion, which has little revenue and their AI performance. By the way, the AI performance we offer at Ambarella is in a family between 1 TOP to 1,000 TOPS. Based on the public information I can find for that company, it is really about sub 1 TOP to 1 TOP type of performance. Yes, they are edge AI company, but there is a little bit overlap. We are generating $400 million revenue versus Synaptics.
I really think that is indication that edge AI is happening and a lot of the company said, "I need a roadmap," and they try to find a way to by using acquisition to fill the gap.
Right. On that front, would you characterize Ambarella's key differentiate?
Mm-hmm. Obviously. Every time we try to build on a design win, the biggest differentiation for us is always performance per watt. That performance can be AI inference performance per watt or video processing performance per watt or other related functions per watt, right? At the end, it's power efficiency. We understand that, in fact, most of our customer, when they build their first-generation product, they use a GPU to do it, because it's easy to program, it's widely available to do that. But when some of the application they are using is really running to the barriers of power consumption, because some of the applications just require battery life or using a very limited power dissipation solution. From that point of view, power efficiency is the most important differentiation for us.
But second one is really that because our heritage is on digital video application, our digital video processing technology is better than I think most of the competitor, maybe all the competitors out there. That's another huge differentiation. But the third, I think a lot of people ignore, is really if we look at our product portfolio, we have 15 AI SoCs that we offer to our customer. But on top of that, there's a unified SDK called Cooper that cover the whole product line. Basically, if you design one product based on our chip using Cooper, you can easily move that same application to different silicon without too much of a modification. And that software architecture, I think, is critically important for our customer who has multiple product line to build and they don't want to reinvent the software from one product to another.
Got it. How should we think about as you compare NVIDIA, they have their related Qualcomm, NVIDIA, Synaptics related offerings, how should we think about you relative to them?
Right. You're talking about three type of competitors. NVIDIA's obviously, they can deliver really high performance. That's their strength. But like I said, GPU's power consumption has been well-documented problem, and we think that for our customer who really want to have a power efficient solution, GPU is not the best solution. From that point of view, we cover all that based on power efficiency. Qualcomm is a little bit different. Qualcomm is definitely more efficient than the GPU. However, when they compare to our approach, we still have a significant power efficiency. But on top of that, we continue. But because they are closer, we definitely have a lot of overlap with Qualcomm. We always view Qualcomm as the biggest competitor to us. Synaptics is different.
Synaptics just, they came into play this AGI two years ago by acquiring product line, and their coverage is really from 1 TOPS to maybe 10 TOPS type of application. Yes, there are some overlap, but it is not a lot. From my point of view, we do not run into Synaptics that much, but when we go out to compete, we run into NVIDIA and Qualcomm all the time.
Got it. The IoT segment currently is roughly about 75%, 78% of total revenue today. Security and consumer video, roughly about 45%, wearables 10%. Could you walk us through the key demand drivers for each of these end markets?
Enterprise security and the.
Yeah. Consumer video.
Oh, got it. Consumer video. For enterprise security is really our largest application that we have been addressing, is really for the security camera in the past. But I think that market start changing. The way it changes is that a lot of security camera become serving different purpose. For example, when we talk to edge infrastructure companies, I just give you example that, for example, in the Starbucks you have a mini camera serve as a security camera in the past.
Now people say, "I want to link, connect all the security camera to a box." And in that box you run a LLM so that now that box can tell you how many people come see, how many people stay there, how many online, and how much time each one of them spend in the store, what they buy and how they pay for it, whether the coffee shop is clean. Suddenly, LLM can start providing customer marketing data as well as operation data. So that changed. But you are using the same security camera hardware. From that point of view, I think that the driver in the past was purely security. Today, we are starting seeing a lot more marketing-driven solution for that. That is one. On the consumer video side, in the past, after iPhone was introduced, cell phone basically replaced all of the still cameras.
Now there is a new trend, right? In fact, people building really high-end video capture device, handheld, stabilized handheld device, and start selling at a very expensive price. But the volume is in the order of 10 million units a year. So those high-end video capture device become a new category that we are addressing. That category can including all the 360-degree camera and the high-end sports camera, pocket, there is those handheld stabilized camera, drone camera, they all pack it into that market by itself, we estimate anywhere between 10 million- 20 million. And ASP is pretty high because not only you need a high-end video processing, but also you need to be able to run AI, a lot of AI on that. From that point of view, it become a sweet spot for us. So that is another driver for the consumer side.
And wearables is about 10%?
Yes.
Any growth driver there?
Well, in fact, in the past, wearable is really for police, law enforcement. Now we are seeing a lot more, for example, a lot of our customer talking to us that the retail stores, all of the people serve in that store wearing the wearable camera, start documenting the conversation and providing extra angles of security. So wearable camera go way beyond law enforcement, and we are start seeing that. And right now that market is really limited by how much power consumption can be made available in that camera, and how long the battery life you can have for this. So that's really play to our strengths.
However, I really think we are still at the early stage of this wearable, because I think when wearable camera become really expand to all of the service category that everybody should wear one so that they can start collecting, become not only for security camera, but like collecting the marketing data, the purchasing habit, all of the customer data can be also become quite interesting for the people who use those kind of wearable camera. I think wearable camera start from the law enforcement now turning to a marketing tool, and it will continue evolve from there.
Is there a way to think about the growth rates for these three end markets?
Right. Those markets, obviously enterprise securities grows at a certain rate because they're very mature.
More bigger.
Consumer market really growing fast in the last few years, and wearable definitely growing much faster pace. However, the base is small.
Yeah.
There is also similar market like robots.
Yeah.
Robotic application, people talk about it all the time, but the base is so small. Most of the customer there is a small, mid-size customer. Although the growth rate is high, the base is low. Another one that we talk about in this time when we disclose our SAM discussion is really the edge infrastructure, which we believe that people will build edge box or edge appliance. In the past, most of them just have a huge, powerful CPU in there. In the future, will be CPU plus a lot of AI inference and engine. So that will become an interesting market, and we think that's definitely another huge growth area for.
Would you talk about how that will play out? Is that on our phones? Is that?
No, I think it's, for example, today, if you go to any retail store, right? If you look at their back end, in the store, they have probably a huge box, huge Intel CPU box sitting there for inventory or for the pricing or for the cash exchange. Most of the people said, "Okay, I have that CPU box, but I need to add a lot of AI, too." That's where we think opportunity. Almost every industrial PC or edge CPU box in the past, when they try to upgrade to the more AI performance into it, that become opportunity for.
Okay. Got it. I know that you guys had a relationship with Hanwha, and signed an LTA deal of about $800 million. Could you share what prompted a move to the LTA deal and why now?
Right. So, in fact, this process is initiated by Hanwha. I think Hanwha is a huge Korean group that has many different subgroup. The subgroup we work closely with is called Hanwha Vision, which is their security camera division. In the past, we sell our chip to Hanwha Vision, but Hanwha Vision also developed their own silicon for the edge video product. They approach us because, as a whole group, Hanwha decided they have to have a unified AI strategy. They want to have one hardware, one silicon, and one platform for the whole group. That make a lot of sense, however, they try to evaluate who can build, help become the partner on that. The requirement is very simple.
They has to be very power efficient, they need a vision processing, they need a very powerful AI inference engine, and they need to access 2nm , 4nm process node. Right? If you look at the combination of that, Ambarella become one of the very few candidates they talk to. We talk to them, we quickly come to the conclusion that it's beneficial for both sides to have collaboration. Obviously, there's other business discussion to come at the end, but at the end, it's really that we help Hanwha to build a family of chips that they can use internally and also give them certain benefit. In return, they basically give us back and making sure that we can become the dominant supplier, semiconductor supplier to the AI strategy.
Are there any other opportunities where you see these kind of long-term agreements will happen?
Absolutely. In fact, when you look at the data center market today, almost all the large companies are looking for their custom chip. Everyone want to build their own chip, and because they can afford it. Google, Amazon, they all can build their own chip. But when it come to edge AI market, there are a lot of large corporations, but if they want to do a custom chip, they will find out that the economy doesn't work out for them because the size is not as big data center, the price is not as big. So the best case is if they want to build a custom chip themselves, they found out that to build 2nm chip is too expensive, they cannot justify. So this is where the semi-custom chip business model comes in.
We believe that we can help those large corporation build a chip they can use, but in exchange, we can sell the same chip to other market that they don't care. I believe that just like in the data center, many large corporation want to control their silicon roadmap, that apply to edge AI market also. When edge AI market become bigger, I expect more and more large corporation to say, "How can I control my own silicon roadmap?" But then, I think that will add to our opportunity to grow in this business.
Got it. I'll pause there for and open it up to the floor.
Yeah.
Questions?
Yes. Go ahead.
Oh. All right. Just wait for the mic for a moment. Yeah.
Thank you so much. So your SoC platform clearly leads in the competition, especially on the energy perspective. Have you received any validations from automotive OEMs, specifically, like your software layer on top of that?
Well, we don't have any design win we can announce. However, we gone through many cycles of evaluation. So from the auto OEM's point of view, we have announced level 4, level 5 truck deal like Aurora. Also we announced automotive OEM, sorry, tier 1, like Continental and Bosch. They are partnering with us. We obviously continue to talk to potential partners in that. So that's on the autonomous driving side. But our total revenue, 30% of total revenue come from automotive. That's come from other areas like telematics for commercial vehicle telematics, several large companies in the telematics using our solution today. Also that electronic mirrors, look at ADAS, DVRs. We have a significant design win. In fact, Q2, we have a record automotive revenue.
But all of this come from the one side of this autonomous driving, we still need to get more design wins from big OEMs. Any other questions? Yes. Between the OEMs? Right. So first of all, we start serving this edge AI with our, we call CV2 family of chips 10 years ago. We start developing that. That family of chips really focus on relatively simple concept compared today is CNN type network, face detection, object detection, those simple task. That's where we start. Then starting five years ago, transformer type of a network come in and large language model happened. That's where you start triggering, figuring fast pace of AI performance requirement. Every time there's a new model coming out, that trigger more AI demand. Just one example, robotics right now talking about using VLM and VLA, now VLX.
Just look at the performance requirement among those models, is tremendously different. Every time the model changes, we constantly engage, say, "Okay, how are we going to handle this?" So from that point of view, different application definitely have different paths of the AI performance requirement, but all of them is on the path of getting higher and higher. In fact, we talk about X7, which is our accelerator product, just in this earning call. The reason for that is when we talk to our existing customers, say, okay, the LLM changing so fast, and in the past, every time we build a product, the product exists for the market for four to five years. Today, nobody believe that for one product defined for one this year, four year down the road, the same LLM still works.
I think then they become how are we going to address that problem because the performance requirement is so big. The easiest way for today is we design a baseline product with one of our SoC chip, and we will leave option to add our accelerator chip like A7, X7 into that board when it is required. You design in a fundamental hardware and software and also add option that you can increase the performance. Those kind of option was not required in the past, and the only reason for that is really that nobody can predict how fast LLM evolve in the next five years. That is just an example how the conversation we have with our customer.
Could you talk a little bit about robotics and humanoids? I think this is a theme that people are just betting on or thinking that it is going to be coming. How close are we or what are some of the customer conversations?
Right. First of all, robotic and humanoid is quite different form. Right? In fact, here is my personal opinion. I think humanoids from technology point of view is more difficult than level 5 autonomous driving car.
Right.
Okay? Elon Musk promised us in 2015 we will have level 5 cars in 2016, and in 2026 we still do not have that.
Yeah.
That just show you that the best engineer team, the best engineer talent still haven't really resolved the level 5 autonomous driving car. I'm not saying humanoid is going to take 10 years to do it, but if I'm right, if that problem is harder than the autonomous driving car, it will not happen next year. It will take more time to evolve. From today to when the humanoid become available, we're going to see multiple generations of different type of robots performing different function at different AI performance level, and that's the opportunity we should focus on instead of trying to really put our eyes on the home run opportunity. Our approach is we engage with humanoid company.
We have a couple design wins in that category, but the volume is not really I won't bet that going to change materially about our financial performance. That's really to try to prepare everything on the roadmap we have, both on the hardware and software side, so we won't miss an opportunity when it happens.
Could you talk about your foundry strategy? You've indicated recently that Samsung capacity is getting tighter. Could you remind us, how do you work with fabs? Is it all across the board, and is there any risk to you securing more if demand exceeds?
Right. We have a strong relationship with Samsung Foundry. There's one fact I don't know whether people are familiar with. There are so many design houses there, private and public. We are the only one exclusive with Samsung. That has been one of the things that we think is right thing for our size of company, because think about this, we are doing 2nm chip. Our first full nanometer chip will be in production. If we stay with TSMC, we won't be able to get much allocation because there are a lot of big guys in front of us. Staying with Samsung, as long as they can give us the technology that we need for our market, we are happy that they can give us more attention, and this will get much better allocations.
From that point of view, I think we are happy with Samsung's not only the allocation, but also support. I am not saying we will get everything we got, but every time the conversation is that if we have a demand, we talk to them early enough, Samsung will find a way to work with us. That relationship definitely matter. I think that is just like any other business. When you have a good relationship with your supplier or your partners, the conversation is easier.
Yeah.
I really think this is a time that I hope that we will take advantage of that, because the overall semiconductor supply chain become extremely tight. Not only foundry, packaging, testing, everywhere is becoming tight. We hope that the relationship we have with our suppliers, that we have been exclusive not only with Samsung, but OSATs, that with this kind of a strategy to partnership, we can continue to get a little better treatment than others.
Got it. You have guided to 10%-15% revenue growth for fiscal 2027. How do you think about the growth drivers we have discussed today? What is going to drive upside, downside, or the range of outcomes?
Well, upside, we talk about this whole thing, right? It is really about edge AI. The downside is only one, it is memory, right? This is well-documented, and the problem is when I talk to our customer for Q3, we are comfortable with the current forecast with a little bit of uncertainty. But in Q4, when I talk to our customer, they told me that none of their memory supplier can even give them commitment about allocation for November, right? They do not even know how many memory or what is the price they are going to get in November. How can they commit to us? That is the biggest variable, in my opinion, the biggest uncertainty that I think everybody is dealing with, it is not just us, everybody is dealing with.
How do you see that as we look out to next year?
I don't think it will end this year. It will definitely go to next year. Who knows how long, but hopefully it will not be too long, because otherwise, it's going to eventually impact us.
Mm-hmm. I believe you've noted that the SoC ASP for a company is about $15 in fiscal 2026. How should we expect ASP to lift?
It will continue to go up. In fact, the reasons we just talk about, the AI performance continue to increase, and that means we have to build bigger die so that we can deliver better AI performance. Therefore, people understand they have to pay more to get AI. So the ASP is going up. It's not that we're going to increase our gross margin. Our gross margin probably stay the same. It's just that the ASP growth is proportional to the AI performance growth.
Got it. And just to make sure, if the foundry were to increase pricing, you are able to pass on that to customers?
I have no choice. I know that our customer is going to hate me for that, but we have to. Just like my supply chain just increased price to me, and I was extremely unhappy with it, but that is just a fact that we have to deal with.
Got it. We have not touched on automotive yet. That is roughly about 30% of our total revenue. You did mention a little about the drivers, telematic safety. How should we think about a growth prospects, and which area are you targeting for content expansion?
We definitely believe the few market that we.
Yeah.
We target at will continue to grow. We are going to grow with the market. From that point of view, I think our automotive revenue should grow. That also reflect on our SAM discussion. I think the biggest wildcard for us is I still want to scale some design win on the automotive OE or consumer view on the level 2 plus, level 3 cars. I think that's the biggest wildcard. We have talked about this for years, but we haven't really delivered that. That is where I think we still continue to focus our current engineering resource on, so hopefully we can deliver on that.
What is the kind of content step-up that we can expect?
Any consumer car design win, we are talk about a few hundred million dollars per design win. That is meaningful for our revenue stream.
As you move from L2 to L3, is there a rule of thumb to think about what is the potential content increase?
The content increase for sure, but L2 plus has a lot more value.
Right.
L2 plus definitely is where the biggest opportunity for us moving forward.
Okay, got it. Could you provide us with an update on the design wins? You mentioned about $13 billion of automotive opportunities. Is Ambarella better positioned with Western or Chinese OEMs right now?
It's Western. We know that for Chinese OEMs, they want to select the domestic solutions. For us, really that Western OEM is our target. However, we still stay in China. The reason for that is we believe that for the AI applications, China innovate fast, and they have a lot of ideas how to use silicon to morph into different product line. We want to stay in China to understand how the new application popping up, all the technological requirement, and that will continue to help us to position our silicon worldwide. We are still optimistic staying in China for that. We also believe with current supply chain being so divided, that China for China, there will be different supply chain for Western. However, I think for Chinese customer want to do export business, they also realize they need a totally different supply chain.
That is our opportunity. There are two reasons for us to stay in China.
Okay. In terms of the near-term growth for auto, which region is it coming from right now?
It is all Western.
All Western.
Yeah.
Okay. Got it. Would you walk us through a typical timeline from design win to revenue production? Is there a design win from automotive.
Automotive.
To revenue?
Right. It's different from application. For telematics, those are non-ASIL type applications, 12 to 18 months is good enough. For the OEM type of autonomous driving car, usually three years, four years. However, I really think that become a problem for Western OE. China turning the product line every 18, 24 months
Yeah.
while we still stay at three, four years, that definitely create a problem for us. I think although I still think all the design win on the Western OEM, we're still looking at three, four years to production. I think as an industry, we need to start considering how to move faster then.
Okay, got it. Just to be clear, the majority of the revenue from auto today is coming from Western?
Mm-hmm. Right.
As we think about, you mentioned a little, geographical, geopolitical risk, China localization, how is that changing relative to a year ago? Is that getting worse? Are there any areas where you think that you're better positioned.
No.
To grow with?
Yeah, I think it is similar to last year. I do not think it is getting worse or improving. I hope we do not get any worse than right now. However, I really think that when we do business, the only thing we ask is predictable environment. I hope if they stay like today, it is okay, because at least I am dealing with predictable future not try to worry about all the changes all the time.
Okay. So, based with the conversation we have had so far with investors, what are the top three things Ambarella is often misunderstood, unappreciated, based on the conversations you have had so far with investors?
Well, I think everybody understand we are focusing on AGI, and the biggest question is what is one vertical, one application that is going to drive, be the first one to drive tons of revenue for you?
Yeah.
We don't have answer for that. Also, we don't have a timeline for how fast the AGI going to develop. I think everybody is looking for an indication of the timing and the application, but unfortunately, we just don't have a solution for it.
Okay. Got it. Any key message for investors to take away from?
I think it's really that we spent 10 years to build the AGI applications, and we believe we have very differentiated technology for AGI and physical AI. I also strongly believe when the market start taking off, we'll be one of the few that going to stay and start take advantage of it.
Thank you. Thank you, Fermi, for joining us.
Thank you very much.