Welcome to Day 2 of Citi TMT Conference. My name is Kelsey, one of the analysts here at Citi covering US 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 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.

Thank you for joining us today. Ambarella is a fabless semiconductor company starting in 2004, and throughout the years we have been starting focusing on digital video application.

Now, in the last 10 years, really focus on building solution for edge AI processing. Basically, what we are saying is that we're building a single SOC that integrate not only just an inference engine, but also image processing pipeline, CPUs, and the peripherals so that we can become the SOC for the whole system.

There's so many different vertical we are targeting at, anything related to the edge device which require AI inference, we are basically in there. The biggest market 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 a new partners, partners like Capgemini and e-con Systems. Basically, we are really focusing on edge AI for the last 10 years, and hopefully the market is going to start taking off as people expected, but definitely that's really what we are focusing on right now.

Right. On that front, what are you seeing today that gives you that confidence that we are sort of 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. I think all confidence is based on that our engagement with our customers.

In fact, all the customers we talk to, they all want to put more and more AI performance into the edge device. In the 10 years ago, it start with a CNN type of neural network.

Now they move to Transformer, then move to large language model. All of that are available in our silicon, hardware, software platform.

One thing that become very obvious in the last 12, 24 months is everybody want to continue increase the AI performance on their device, mainly because the large language model. However, edge AI or physical AI people have been really talk a lot about it, but the biggest problem for this market today is there's no one vertical like coding for data centers, right?

Today, majority data center revenue is generated by one big application, but there's no such application at the edge. That's where our strategy always focus on multiple different possible vertical, and hopefully that one of them will grow.

You talk about the acquisition. This ADI just announced a deal, which acquire a startup company for $1.5 billion, which has little revenue.

By the way, the AI performance we offered at Ambarella is in a family between 1 TOPS to 1,000 TOPS. Based on the public information I can find for that company, it's really about sub-1 TOPS to 1 TOPS to 1 TOPS type of performance.

Yes, they are edge AI company, but it's just a little bit overlap. We are generating $400 million revenue versus son.

I really think that's indication that edge AI is happening, and a lot of company say, "I need a roadmap," and they try to find a way by using acquisition to fill the gap.

Right. On that front, could you characterize Ambarella's key differentiators?

Obviously. Every time we try to bid 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.

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. When some of the application they are using is really run into the barriers, power consumption, because some of the application 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. The 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 our competitor, maybe all the competitors out there.

That's another huge differentiation. 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.

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 modification.

That software architecture I think is critically important for our customer who has multiple product lines 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 types of competitors.

Nvidia is obviously, they can deliver really high performance. That's their strength.

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, kind of we carve out that based on power efficiency.

Qualcomm is a little bit different. Qualcomm is definitely more efficient than the GPU, but however, when they compare to our approach, we still have a significant power efficiency.

On top of that, 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 they came in to play this edge AI 2 years ago by acquiring product line.

Their coverage is really from 1 TOPS to maybe 10 TOPS type of application. Yes, there's some overlap, but it's not a lot.

From that point of view, we don't 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% each, wearables 10%. Could you walk us through the key demand drivers for each of these end markets?

Enterprise security and the-

Consumer video-

Consumer video. For enterprise security, it's really our largest application that we've been dressing for.

It's really for the old security camera in the past. I think that market start changing.

The way it change is that a lot of security camera become serving different purpose. For example, when we talk to edge infrastructure companies, I just give you an example that for example, in Starbucks, you have many 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 comes in, 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's clean." Suddenly, LLM can start providing customer marketing data as well as operation data.

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 start seeing a lot more marketing-driven solution for that. That's one.

On the consumer video side, in the past, after iPhone was introduced, cell phone basically replace all of the still cameras. Now there's a new trend, right?

In fact, people building really high-end video capture device, stabilized handheld device, and start selling at very expensive price. The volume is at order of 10 million units a year.

Those are high-end video capture device become a new category that we are addressing. That category can including all of 360-degree camera and the high-end sports camera, handheld, stabilized camera, drone camera, they all package into that.

That market by itself, we estimate anywhere between 10 to 20 million units. ASP is pretty high because not only you need 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. That's another driver for the consumer side.

Wearables is about 10%. Any growth driver there?

Yes. Yeah.

In fact, in the past, wearable is really for police, law enforcement. Now we're seeing a lot more, for example, a lot of our customers 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.

Wearable camera go way beyond law enforcement, and we are start seeing that. Right now that market is really limited by how much power consumption you can be made available in that camera, and how long the battery life you can have.

That's really played to our strength. 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 collecting the marketing data in the purchasing habit, all of the customer data can be also become very quite interesting for the people who use those kind of wearable camera.

I think wearable camera start from the law enforcement, now turn into 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 security is grows at a certain rate because it's very mature.

I think that the- Consumer video.

Consumer market is really growing fast in the last few years, and wearable definitely growing in much faster pace. However, the base is small.

There's

also similar market like robots. Robotic application, people talk about it all the time.

The base is so small. Most of customer there is a small, mid-sized customer.

Although the growth rate is high, but 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 engine.

That will become an interesting market, and we think that's definitely another huge growth area for

us. Could you talk about how that will play out?

Is that on our phones? Is that-

No, no. For example, today, if you go to any retail store, right, if you look at their back end, in the store, they have a probably a huge box, huge Intel CPU box sitting there for inventory or for the pricing or for the cash exchange.

Most of people said, "Okay, I have that CPU box, but I need to add a lot of AI to it." That's where we think opportunity is.

Almost every industrial PC or kind of edge CPU box in the past, when they try to upgrade more AI performance into it, that become opportunity for

us. Got it.

I know that you guys had a relationship with Hanwha and signed an LTA deal of about $100 million. Could you share what prompted the move to the LTA deal, and why now?

Right. In fact, this process is initiated by Hanwha.

I think Hanwha is a huge Korean group that has many, many different subgroup. The subgroup we work closely 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 products. They approach us because as a whole group, Hanwha decide they have to have a unified edge AI strategy.

They want to have one hardware, one silicon, one platform for the whole group. That make a lot of sense.

However, they try to evaluate who can help become the partner on that. The requirement is very simple.

It 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 to talk to.

We talk to them, we quickly come to the conclusion that it's beneficial for both sides to have a collaboration. Obviously, there's other business discussion to come at the end, but at the end is 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 spec and making sure that we can become the dominant supplier, semiconductor supplier to their edge AI strategy.

Are there any other opportunities where you see this 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 chips.

Everyone want to build their own chip, and because they can afford it: Google, Amazon, they all can build their own chip. When you come to edge AI market, there are a lot of large corporations, but if they want to do a custom chip, they'll 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. The best case is, if they want to build the custom chip themselves, they found out that to build 2nm chip's too expensive, they cannot justify.

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 corporations 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 will say, "How can I control my own silicon roadmap?"

Then, I think that will add to our opportunity to grow in this business model.

Got it. I'll pause there and open it up to the floor.

Any

questions?

Yes. Go ahead.

Oh, and wait for the mic for a moment.

Thank you so much. Your SOC platform clearly leads in the competition, especially on the energy efficiency perspective.

Have you received any validations from automotive OEMs specifically, like your software layer on top of that?

We don't have any design win we can announce, but however, we gone through many cycles of evaluation. For the auto OEMs point of view, we have announced Level 4, Level 5 truck deal like Aurora, and also we announced Tier 1 like Conti and Bosch, they are partnering with us.

We are obviously continue to talk to potential partners in that, so that's on the autonomous driving side. But 30 our total revenue 30% of total revenue come from automotive.

That's come from other areas like 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 wins.

In fact, Q2 we have a record automotive revenue. All of them come from the one side of this autonomous driving, we still need to get more design wins from big OEMs.

Any other questions? Yes.

[unclear] the between the OEMs, oh sorry, the- Right. 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 compared to today, it's CNN type network, face detection, object detection, those simple tasks.

That's where we start. Then starting 5 years ago, Transformer type of of network come in, and large language happen.

That's where you start tricking triggering 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, then VLA, now VLX. Just look at the performance requirement among those models, it's tremendously different.

Every time the model changes, we we customer will engage, say, "Okay, how are you going to handle this?" From that point of view, different application definitely have different pass of the AI performance requirement, but all of them is on the pass of getting higher and higher.

In fact, we talk about N1, which is our accelerator product, just in this earning call. The reason for that is when we talk to our existing customer, say, "Okay, the LLM changing so fast, and in the past, every time we build a product, the product exists for the for the market for 4 to 5 years.

Today, nobody believe that for one product defined for one this year, 4 year down the road, the same LLM still works." I think then it become how are we going to address that problem, because the the performance requirement's so big.

The easiest way for today is we design a baseline product with one of our SOC chip, and we leave option to add our accelerator chip like N1 into that board when it's required. You you you design in a fundamental hardware and software, and just and also add option that you can increase the performance.

Those kind of option was not required in the past. The only reason for that is really that nobody can predict how fast LLM evolve in the next 5 years.

That's just give you a 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 starting on or thinking that's going to be coming.

How close are we, or what are some of the customer conversations?

Right. Robotic and humanoids is quite different form, right?

In fact, here is my personal opinion. I think humanoid on technology point of view is more difficult than Level 5 autonomous driving car, okay?

Elon Musk promised us in 2015 we will have Level 5 cars in 2016, and in 2026, we still don't have that. That just show you that the best engineering team, the best engineering talent still haven't really resolved the Level 5 autonomous driving car.

I'm not saying humanoid going to take 10 years to do it, but if I'm right, if that problem is harder than 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. That's 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 of design wins in that category, but I won't bet that going to change materially about our financial performance.

That's really to try to prepare everything, all the roadmap we have, both on the hardware and software side, we won't miss the 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 securing more if demand exceeds expectations?

Right. We have strong relationship with Samsung fab.

There's one fact, I don't know whether people are familiar with, there are so many design houses there, in private and public. We are the only one that 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 4nm 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 also get better allocations. From that point of view, I think we are happy with Samsung's not only the allocation, but also support.

I'm not saying we'll 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's just like any other business. When you have a good relationship with your supplier or your partners, the conversation is easier.

I really think this is a time that I hope that we'll take advantage of that, because the overall semiconductor supply chain become extremely tight. Not only foundry, packaging, testing, everywhere is become tight, and 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 strategy partnership, we can continue to get a little better treatment than others.

Got it. You've guided to 10% to 15% revenue growth for fiscal '27.

How do you think about the growth drivers we've discussed today? What's going to drive upside, downside, or the range of outcomes?

Upside, we talked about this whole thing, right? It's really about edge AI.

The downside is only one: it's memory, right? This is well documented.

The problem is, when I talk to our customer, for Q3 we're comfortable with the current forecast with a little bit uncertainty. 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 don't even know how many memory or what's the price they're going to get in November, how can they commit to us? That's the biggest variable in my opinion, the biggest uncertainty that I think everybody is dealing with, it's not just us, everybody dealing with.

How do you see that as you 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 that it will be too long, because otherwise it's going to eventually impact us.

I believe you've noted that the SoC ASP for the company should be about $15 in fiscal '26. How should we expect the ASP to shift?

It will continue to go up. In fact, the reason's just we talk about.

The AI performance continue to increase, and that means we have to build bigger die, and so that we can deliver better AI performance. Therefore, people understand they have to pay more to get the AI.

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. Just to make sure, if the foundry were to increase pricing, you're able to pass on that to customers?

I have no choice. I know that our customer 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's just a fact that we have to deal with.

Got it. We haven't touched on automotive yet.

That's roughly about 30% of total revenue. You did mention a little about the drivers, telematics, safety.

How should we think about the growth prospects, and which area are you targeting for content expansion?

We definitely believe the fuel market that we target at will continue to grow. We're 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 wild card for us is I still want to get some design win on the automotive OEMs for consumer vehicle, on the Level 2+, Level 3 cars. I think that's the biggest wild card.

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, 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 talking about a few hundred million dollars per design win. That is meaningful for our current revenue stream.

As we 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 however, L2+ has a lot more volume

than L3.

L2+ definitely is where the biggest opportunity for us moving forward.

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 lines. That we want to stay in China to understand how the new application popping up, what kind of technology requirement, and that will continue to help us to position our silicon worldwide.

We still optimistic staying in China for that, but also we believe with current supply chain be so divided that China for China, and 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's 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's all Western.

All Western. Got it.

Could you walk us through a typical timeline from design win to revenue production? A sort of design win from automotive to revenue- Automotive.

Right. It's different from application, right?

For telematics, those non-ASIL type of application, 12 or 18 months is good enough. For the OEM type of autonomous driving car, usually 3 years, 4 years.

However, I really think that become a problem for Western OEM. China turning the product line every 18, 24 months, while we still stay at 3, 4 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 3, 4 years to production, I think as an industry, we need to start considering how to move faster than

that. Got it.

Just to be clear, the majority of the revenue from auto today is coming from Western

OEMs. Western.

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 are better positioned to grow with-

No. I think it's similar to last year.

I don't think it's getting worse or improving. I hope we don't 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 today like today, it's okay, because at least I am dealing with predictable future, not try to worry about all the changes all the time.

Yeah. Based on the conversations you have had so far with investors, what are the top three things Ambarella is often misunderstood, unappreciated?

I think everybody understand that we are focusing on edge AI, and the biggest question is what's one vertical, one application that's going to be the first one to drive tons of revenue for you. We don't have answer for that, and also we don't have a timeline for how fast the edge AI is 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 you.

Got it. Any key message for investors to take away from?

I think it's really that we spend 10 years to build the edge AI applications, and we believe we have very differentiated technology for edge AI and physical AI, and I also strongly believe when the market start taking off, we will be one of the few that going to stay and take advantage of.

Thank you. Thank you, Fermi, for joining us.

Thank you very much.