All right. We got a few late entrants coming in. Oh, I didn't get the safe harbor. All right. Good morning, London. I want to see how everyone's doing, but it's probably not appropriate. Let's start off with a safe harbor. Today's discussion will contain forward-looking statements, including Cadence's outlook on future business and operating results due to risks and uncertainties. Actual results may differ materially from those projected or implied in today's discussion. With that out of the way, it's now my pleasure to introduce Anirudh Devgan here, CEO of Cadence Design Systems. Anirudh, welcome to London.
Yeah, it's great to be here.
Always great to see you as well.
You guys are so fashionable here, I was saying. Everybody's so well-dressed.
For those listening in, everyone stood up and did a twirl at that point. Well done, London. Let's maybe get down to things here. For those who are maybe new to the story, let's level-set everyone. Would you mind just giving us a brief overview of Cadence and where it sits within the semis and systems ecosystem here?
Yeah, I think for those who are not familiar, basically we make products, mostly software products, some IP and hardware or full-stack products to basically design chips and electronic systems. Almost any chip design in the world today uses some form of Cadence products. About 45% of our customers are now system companies, like phone companies, car companies, hyperscalers, and 55% are semiconductor companies. They're also increasingly becoming full-stack companies on the semi side.
Then one key thing about our software, which is very unique, is we are involved in the build-out of AI. There are multiple phases of AI I have talked about for years, but when all these companies design chips, they use our software, which is not true for most software. Then on the other side, that is design of AI. Then we can put AI in our design software to improve our own products and then make them, I would think, about 5X-10X more efficient, 10%-20% better performance, power, performance, and area.
There are two ways we are benefiting from AI. We are lucky to work with all the big players, all the Mac 7, and about 60%-70% of the revenue is coming from about 60 companies. These are all the who's who in the tech world. That's like a brief summary of Cadence.
That's pretty good. Maybe just playing on that AI drivers and themes, maybe could you break down for us what are the actual underlying structural trends as it relates to the three businesses you have, EDA, systems, and IP? How does that change as AI-driven demand really hits the road over the next few years?
I mean, AI, of course, is changing a lot of things, but especially semiconductors and systems. The projection is that semi revenue will cross $1 trillion in a few years. Then system revenue already is like $3 trillion, growing faster. All these things, the amount of design that is happening is immense. We are seeing that, of course, in infrastructure AI. I always believe there are, I believe this for several years now, that there are three phases of AI. There is the infrastructure phase, which is what we are in now. That's data centers, of course, semiconductors, LLMs. It's more horizontal technologies.
Then I think it will transition to more vertical monetization. Vertical phase, I think one of the biggest phases would be physical AI. That's cars, drones, robots. That's already started, but I think it will pick up more. Then science is AI, which is applying AI to real science, like drug discovery or material science, things like that. In these three phases, I want to make sure Cadence is very well positioned. But the amount of design activity is immense, all these companies, and we are working with all of them.
Now, how it applies to the, it helps all the three. Actually, at this point, all the three businesses are doing well. They're growing pretty well. We also, for those who are not familiar, are always looking at growth and margin. Our operating margin this year is about 44.5% or something. Our revenue growth last year is 14%. That's rule of 58%. I'm pretty sure I think we'll cross 60% in the near future, and that's our goal. We want to obviously have growth, but profitability at the same time.
Makes sense.
All this, we also keep an eye on SBC, stock-based comp. That's about 8.5% or something. Because a lot of people will want to get stock instead of cash. Real margin is, of course, operating margin minus SBC. That also we have kind of controlled it, and it will increase a little bit, but not a whole lot. Overall, I think the company is in great financial shape and should improve going forward.
Got you. Good leverage in the model here. I wanted to maybe talk about specific business segment next in IP. We saw some of the, let's say, misstep perhaps with Arrival recently in this space. Some of it customer-driven, some of it regional aspect, but can you maybe help us understand what are the differences here between yourselves and other players in this market as far as end markets you focus on, then also, what do you see as the sustainable growth rate perhaps in IP going forward?
Yes. We are at $5.2 billion-$5.3 billion this year. IP is about 15% roughly, and systems is about 15%, and EDA, which is our core business, is about 70%, rough numbers. Like I said, all three are doing well. Now, IP is good, but it's always slightly less profitable than software. IP means we design certain things and pre-made and sell like DDR, critical IPs, PCI, things like that. I always was careful how much to invest in IP over the years because first we wanted to make sure that we are very good in EDA, which we are. We have the broadest portfolio in EDA. We have very good customer traction.
Then over the last few years, I have invested more in IP for multiple reasons. One, I think we have a much better team now. Because these are protocol-based IPs like DDR or HBM, the functionality is kind of basic, it's given. How customers choose IP is based on PPA, power performance in area. Our PPA, especially for TSMC nodes, has improved significantly in the last few years, primarily because we have a much stronger team. R&D is much better in IP than before. That's one reason we are doing well. We focus more on what I would call HPC IP and more at advanced nodes.
Basically, TSMC's advanced nodes. There are five main IPs there. There is UCIe, which is, I'm sorry for all the technical lingo. UCIe is chip to chip, HBM memory, DDR memory, PCIe, and SerDes. At this point, we have all the five key IPs at the most advanced nodes. That is doing well. We don't do a lot of older nodes or a lot of consumer kind of IP. Then part of our IP business is also Tensilica, which is like a core. This is like ARM, like ARM-class scores. Tensilica is number two in that kind of CPU and DSP IP. The good thing with Tensilica is that it's growing and it will be more important in physical AI, but it's almost software-like margins.
Our IP business is first is Tensilica, which is like software. Second, on the design IP, it's more HPC AI focused, and PPA has improved significantly. Then now there are a lot of new foundries apart from TSMC, like Intel, Samsung, Rapidus. They also need IP. I feel at this point IP will do well. We have done well for two years already. First year, I didn't talk about it because one year doesn't make a trend. Then this year also we are doing well. I think 2026 should be good.
I expect IP business to grow faster than Cadence average, which it should, given that the margin is slightly lower. Margin is not that bad, but it's not as good as EDA. I feel good about IP. We do always some strategic M&A in IP from time to time. Try to build out the portfolio. We bought the Artisan business from ARM. We bought Secure IC. We bought HBM from Rambus. Yeah, I think IP and the customers want more Cadence IP.
Sure. Okay. Full portfolio, focus on PPA, leading edge focus as well. Maybe double-digit growth is what we're looking at here for the business.
Yeah, that should definitely.
Got you.
Our focus always is win with the winners. We always focus on the top first. Their portfolio has to be big enough, but they always buy best in class. There is very little bundling at the very top because they have enough money and resources, and they're looking for best in class. If we are able to succeed at the top, we can always scale it down. I think IP business, the other thing, sometimes we can publicly talk about the customers, sometimes we can't, but IP business is doing very well at the winners, at the top companies.
Okay. I wanted to touch on M&A, but maybe before we go there, maybe if we could touch on China. I think you've been pretty clear that China is a region where you're seeing growth. It's not slowing. You're not seeing any sort of issues. Is that still the case as we turn into 2026? How would you characterize the opportunity set there, let's say for the next two, three years?
Yeah, I think China is back to normal is what I would say. When we guided, because we are always prudent in our guide, when we guided earlier this year, we said China will be flat. Now it turned out that China is growing this year, which is good. It's always good to surprise positively. The reason I said it will be flat is when I went to China in last November, they said, "Oh, 2025 will be a very difficult year. It'll be the worst year for U.S.-China relationship." I think China has always been well prepared in this kind of for 2025. Then they say, "Oh, by 2026, by end of 2025 or beginning of 2026, there'll be a deal."
They just want to make sure they are not, after the deal, they are not overly reliant on U.S. They're like three steps ahead of the game, which is kind of interesting. We were very prudent in our, because we didn't know exactly what will happen in 2025, but we said, "Why? We should be more prudent." That's what happened. There were a lot of other things that happened in terms of we were banned for six weeks and all that. But I think even in the ban, the customers were fairly calm, I think.
Overall, we had some issue of some revenue moved from Q2 to Q3. But if you step back, China will be in 11%-12% of revenue, which is down from 16%-17% a few years ago, but still it will grow from last year. Going forward, right now I think the situation is somewhat stable. The customers are designing a lot of things. Infrastructure AI, of course, all these big companies, Alibaba and all those are designing chips. Also physical AI, they are huge. They're like five big car companies. They're all our customers designing chips. Then there are all these consumer companies like Xiaomi, which is also doing cars, phones, Lenovo, they're all doing chip design. It seems stable at the moment.
Yeah, that's pretty good. That's pretty good. Again, I think I said I'd want to touch on M&A and maybe two parts to this question on Hexagon in particular, which looks like a good deal. Where's your integration priorities here with this business? What are the main milestones we should be focused on? Then maybe secondary to that, is there genuine revenue synergies you can talk to today that maybe benefits your position in physical AI applications?
Oh yeah, I'm very excited about Hexagon and working with Ola, who's the Hexagon chairman. I think it's like a diamond in the rough, the simulation business of Hexagon, because Hexagon wants to focus on other things. It was like only one simulation asset, whereas we can integrate it much better in the Cadence portfolio. We are always very careful about M&A, because anyway, organically we're going to go well, and that's the most profitable way. But from time to time, we will do M&A if it makes sense. The reason for Hexagon was primarily for physical AI. The 15% of our system business is anyway growing like 20% plus for five, six years.
I started all this in 2018. That time was not clear. People say, "What is the system simulation and EDA? “What is SDA and EDA?” But we knew what the customers were doing, both on the system side, doing silicon, and silicon companies doing systems. Now it's like obvious. But one thing that is, but 25 is not 18, right? Things are changing in the system business. The growth part of the system business, we don't need all of the, we have enough portfolio, but the exciting part of the system business to me are two parts, and that's what we want to focus on. I think we will cross a billion run rate in systems reasonably soon, assuming M&A closes and all that.
One part of system business, which is high growth, is 3D IC, which is close to the chip. We have a very good position with Allegro, because 3D IC is another word for system in a package. Now there's 3.5D also, did you know? That's possible, right? There's 3.5D ICs, which is a combination of 2.5D and 3D-IC. But anyway, I think that one focus will be 3D-IC, which is Allegro, packaging, Clarity, thermal, electromagnetic, all that. Then the second focus, which is going to be high growth anyway, because all the segments in semiconductors will go towards 3D-IC or 3.5D IC. Then the other part will be Physical AI.
I talked for a long time about the three-layer cake. People say, "Are you like a bakery or something?" If you don't, yeah. The reason talk about three-layer cake is because unless you're like two years old, when you eat cake, you eat all the layers together or consume all the layers together. What are the layers of the three-layer? There's AI, of course, top. Middle layer, which a lot of people forget, is principle, ground truth, how transistors work, how molecules work. Bottom layer is silicon or domain-specific silicon. Then there are three phases of that, infrastructure, physical, sciences.
In my mind, there's like this three by three matrix, three horizontal technologies, and three vertical applications. Now, we can talk about this a lot. People who graduated just a few years ago, they said, "Well, all I need is AI. What do I need? Anything else? I can fit a model for everything in life." People who graduated 30, 40 years ago, they said, "What's all this curve fitting? I need ground truth. I need to know how things really work, not a model." I said, "Well, I don't want to take any sides. You need both." Actually, in our algorithms, always there was fundamental algorithms and data-driven algorithms.
Of course, they're not much more powerful with AI. Anyway, we need all these three things. Now, with physical AI, all the three layers of the cake will get transformed. The bottom layer, which is silicon, is of course different. Just look at Tesla or BYD. The chips are much lower power. They're all custom chips for physical AI, whether it's for cars or robots or drones. They will be more mixed signal, and they will be lower power. Anyway, we are very well positioned for that. We didn't need Hexagon for that. We were already very well positioned. All the big auto companies, semi companies are big Cadence customers.
Then all the newer ones we are working with, like I mentioned. But the other two will also change. I know this for a while anyway, but what the AI model, what will fundamentally change in the AI model, and there's more and more talk about this, is the AI model will move from a text model, like an LLM model, or a word model, W-O-R-D, to a world model. My kids say my word and world sound the same. This is the one with the L, W-O-R-L-D model, or the physical model. All these companies are working on it.
What happens in a physical world model, like in the LLM model, you can train, if you train the transformer, you have all the data on the internet, because you have all the text on the internet. But on a physical world model for robotics or cars, the data is not available. You have to gather it. You have to hold this bottle. Either you put sensors and do that, so that's very slow, or you have to put simulation in the loop to generate data. First, the model will change to a world model with the LLM.
Then you can put the middle layer, the physical simulation in the loop and accelerate with AI. The main technology you need there is what is called multibody dynamics or simulation of robots and cars. Hexagon has the best multibody dynamics simulator, number one in the market. That's the reason to acquire Hexagon, so that we can be as relevant in the physical AI world as we are in the infrastructure AI.
Got you. Maybe if we stay on that point there, because I think that's quite interesting. It almost sounds like you're saying we're utilizing transformers to make models. But as we move to context awareness in the physical world, there's two possibilities. We could have simulation readiness in the loop, or we could have a real-time sensor appreciation. But it's a software solution is what you're advocating.
Yeah, both of them. Yeah, we'll have sensors anyway on the silicon side. The silicon will change, but the inference will change, because the thing is that the physical AI will reinforce infrastructure AI. Because even like Tesla or BYD, if they run the inference on the car or on the robot, of course the silicon is different, the inference is different, but the model is trained on the data center. It helps, it might pay for the.
But the thing will be that you just want to make sure we are completely ready for this phase. Like in the infrastructure phase, we are working with all the leading players. This one, we needed some pieces, especially I think simulation in the loop will become even more critical. That's why. Hexagon is a great asset for that. Then we can integrate with Beta. Beta is the other acquisition we made, which is also doing very well to make a full flow for this kind of physical AI.
Got you. Okay, so good integration with Beta. The other question I wanted to ask, maybe I'll open up the floor after. We are getting used now to collaborations NVIDIA is having with the ecosystem broadly, and two in particular that are relatively close to home. NVIDIA's partnership, first of all, with Intel, and what opportunity that might bring for you guys. Maybe there was a non-exclusive deal done or collaboration with Synopsys. What your views were there, and should we focus on that non-exclusivity in that deal when thinking about yourselves?
We worked with NVIDIA and Jensen for years. Actually, we even released some of this recent news, like porting their software to GPUs and all. But I've been doing that for years. If you look at even Cadence announcement from two years ago, it covers most of these topics. We do it in EDA, we do it in SDA, we do it in bio drug discovery. We are glad to have NVIDIA as a great partner. Our business with NVIDIA is growing. I actually had a joint statement with Jensen ready for last week, but we didn't release it because we didn't think we needed to release it.
Our partnership with NVIDIA is fabulous, and we cherish that. In terms of investment, we would like to get business from NVIDIA and investment from you guys. That's why I'm here. That's our style. Then we also want to be, even though NVIDIA is an amazing company, I think like I said, there will be a lot of, as AI evolves, there'll be a lot of other great companies. We want to make sure we are, the benefit of EDA is horizontal technology. We want to work with all the great companies.
Makes sense.
Intel, yeah, we'll see. We have, of course, my predecessor is there. We have a lot of discussion ongoing with Intel, see how they progress, especially as they focus on 14A.
Precisely. Maybe with that, we'll open it to the floor, see if anyone's got burning questions. Not at this point. Maybe just one with a minute to go. Clearly, there's a little bit of margin pressure as you transition to annual subscriptions and some of the SDA business. Help us understand, what is that? Why are we doing it? What sort of margin pressure should we expect?
No, we always do things for the long run. We have recurring business in EDA, which is great. I think what happened in SDA is that the accounting treatment is different than EDA. EDA by nature is recurring. SDA by nature, because of the accounting rules, is upfront. At least some of the business we are buying are upfront or we bought. We can't change that, but what we can change, which is a very good business practice, is annual subscription. Because then we report annually. What you don't want is multi-year deals and you take upfront. That's not healthy for the business long term.
If we get Hexagon, I think they were already doing the subscription conversion to annual subscription like 60%-70% of the way. We'll take it all the way, but that, in the end, you recover all that revenue and more in the future. There might be some one-year impact, but still, it's not going to be that significant given our scale. The other thing is our incremental margin on our organic business is close to 60%. Our goal, of course, is 50% plus incremental margin, which we have done for eight years now. Even this year, it should be pretty good. Now, last year it was slightly less incremental margin because of Beta acquisition.
But then we made it up this year. If you combine 2024 and 2025, our incremental margin is 53% or 54%, because it was slightly less last year and it's more this year. Maybe 2026, 2027 will follow a similar path. But in any case, our incremental margin will be more than our operating margin, no matter what, with M&A. Whatever transition we do for the long run, we will recover that in 2027.
I think we will not do any M&A that destroys this fundamental financial model. That our margin goes up, of course, revenue should keep improving. Then we buy half of our, use half our cash flow to buy back stock, primarily to make sure there is no dilution. If we do like 8%-9% SBC, we buy back more than that. That is not going to be changed based on M&A. That is intact. But there may be some movement, like one year slightly less incremental margin, another year slightly more. But it'll be more than what our operating margin is.
Sounds clear. Anirudh, thanks very much. Clock's taking our time. Thank you.
Thanks.