Cadence Design Systems, Inc. (CDNS) Earnings Call Transcript & Summary

All right. Good morning, London. I want to say how is everyone doing, but it's probably not appropriate. Let's start off with the 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. So with that out of the way, it's now my pleasure to introduce Anirudh Devgan here, CEO of Cadence Design. Anirudh, welcome to London.

It's good to be here.

Always great to see you as well.

You guys are so fashionable here, I was saying. Everybody is so well dressed.

It's -- for those listening in, everyone stood up and did a twirl at that point. So well done London.

Let's maybe get down to things here. For those who may be 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?

Yes. 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. So almost any chip design in the world today uses some form of Cadence products and about 45% of our customers are now system companies, like phone companies, car companies, hyperscalers and 55% are semi companies, semiconductor companies, so they are also increasingly becoming full stack company on the semi side. And then we are -- I mean, 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. And then on the other side, we -- so that is design of AI. And then we can put AI in our design software to improve our own products and then make them -- I would think about 5x to 10x more efficient, in a 10% to 20% better performance, power performance in the area. So there are 2 ways we are benefiting from AI. And we are lucky to work with all the big players, all the MAX 7, and about or like the 60%, 70% of revenue is coming from about 60 companies, and these are all the rooms who in the tech world. So that's like a brief summary of Cadence.

That's pretty good. I mean maybe just playing on the AI drivers and themes. Maybe could you break down for us what are the actual underlying structural trends as it relates to the 3 businesses you have, EDA systems, and IP. And 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. So the projection is that semi revenue will cross $1 trillion in a few years, and then system revenue already is like $3 trillion, growing faster. So all these things, the amount of design that is happening is immense, right? So we are seeing that, of course, in infrastructure AI. So I always believe there are -- I believe this for several years now. So that there are 3 phases of AI. So there is infrastructure phase, which is what we are in now. So that's data centers, of course, semiconductors, LLM, so it's more horizontal technologies. And then I think it will transition to more vertical monetization. So vertical phase, I think one of the biggest phases would be physical AI, so that's cars, drones, robots. And that's already started, but I think it will pick up more. And then science is AI, which is applying AI to real science, like drug discovery or material science, things like that. So in these 3 phases, I want to make sure Cadence is very well positioned. But the amount of design activity is immense, right, all these companies, and we are working with all of them. Now how it applies to the -- it helps all the 3. So actually, at this point, all the 3 businesses are doing well. They're growing pretty well. And we also, for those who are not familiar, always looking at growth and margin, so our operating margin. This year is about 44.5% or something and our revenue growth last year is 14%. So that's a rule of what, 58%? So I'm pretty sure, I think we'll cross 60% in the next -- near future, and that's our goal. So we want to obviously have growth, but profitability at the same time. And all this, we also keep the eye on SBC, so stock-based comp. So that's about 8.5% or something. So because a lot of people will want to get stock instead of cash. So real margin is, of course, operating margin minus SBC. So that also we have kind of controlled it. And it will increase a little bit, but not a whole lot. So overall, I think the company is in great financial shape and should improve going forward.

So good leverage in the model here. I wanted to maybe talk about specific business segment next in IP and we saw some of the, let's say, misstep perhaps with a rival 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? And then also, what do you see as the sustainable growth rate perhaps in IP going forward?

Yes, so we have about $5.2 billion, $5.3 billion this year. So IP is about 15% roughly, and systems is about 15%, and EDA, which is our core business, is about 70% rough numbers. And like I said, all 3 are doing well. Now IP is good, but it's always slightly less profitable than software. So IP means like we design certain things. And premade and sell like DDR, critical IPs, PCI, things like that. So 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. And over the last few years, I have invested more in IP for multiple reasons. One, I think we have a much better team now and our -- so because these are protocol-based IPs, like DDR or HBM. So the functionality is kind of like basic, it's given and how customers choose IPs based on PPA, power performance and area. So 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. So that's one reason we are doing well. And we focus on, more on what I would call HPC IP and more at advanced nodes. So basically, TSMC is advanced node and there are 5 main IPs there. So there is UCI, which is -- I mean, sorry for all the technical lingo. UCI is chip-to-chip, HBM memory, DDR memory, PCIe and SerDes. So at this point, we have all the 5 key IPs at the most advanced nodes. So that is doing well. And we don't do like a lot of older nodes or a lot of kind of consumer kind of IP. And then part of our IP business is also Tensilica which is like a core. This is like ARM cells cores. Tensilica is #2 in that kind of CPU and DSP IP. And the good thing with Tensilica is that, I mean, it's growing, and it will be more important in physical AI, but it's almost software-like margins. So 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. And then now there are a lot of new foundries apart from TSMC, like Intel, Samsung, Rapidus, so they also need IP. So I feel at this point, IP will do well. I mean, we have done well for 2 years already. So first year, I didn't talk about it because 1 year doesn't make a trend. Then this year also, we are doing well. And I think '26 should be good. So I expect IP business to grow faster than Cadence average, which it should, given that the margin is slightly lower. I mean margin is not that bad, but it's not as good as EDA. So I feel good about IP. And we do always some strategic M&A in IP from time to time. So we try to build out the portfolio. Like we bought the artisan business from ARM. We've got secure IC, we bought HBM from Rambus. So yes, I think IP, and the customers want more Cadence IP.

Okay. So a full portfolio, focus on PPA, leading-edge focus as well, maybe sort of double-digit growth is what we're looking at here for the business?

Yes, that should -- now our focus always is win with the winners. So we always focus on the top first. And there, portfolio has to be big enough, but they always buy best-in-class. There is no -- there is very little bundling at the very top because I mean they have enough money and resources, and they're looking for best-in-class. So if we are able to succeed at the top, you can always scale it down. So 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. And 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 '26? And how would you characterize the opportunity set there, let's say, for the next 2, 3 years?

Yes. I think China is back to normal is what I would say. And when we guided -- because we are always prudent in our guide, okay. When we guided earlier this year, we said China will be flat, okay? And now it turned out that China is growing this year, which is good. It's always good to surprise positively. So the reason I said it will be flat is when I went to China last November, they said, oh, '25 will be a very difficult year. It will be the worst year for U.S.-China relationship. So I think China has been always been well prepared in this kind of '25. And then they say, "Oh, by '26 by end of '25 or beginning of '26, there will be a deal. And they just want to make sure they are not -- after the deal, they are not overly reliant on U.S. So they are like 3 steps ahead of the game is kind of interesting. So we were very prudent in our -- because we didn't know exactly what will happen in '25, but we said like, why we should be more prudent. And that's what happened. I mean -- and there were a lot of other things that happened in terms of, we were banned for 6 weeks and all that. But I think even in the ban, the customers are fairly calm, I think. So overall, we had some issue of like some revenue moved from Q2 to Q3. But if you step back, China will be in 11%, 12% of revenue, which is down from like 16%, 17% a few years ago, but still, it will grow from last year. And going forward, right now, I think the situation is somewhat stable. The customers are designing a lot of things. I mean infrastructure, AI, of course, all these big companies are Alibaba and all those are designing chips. And also physically, they are huge. I mean there are like 5 big car companies. They're all our customers, designing chips. And then there are all these consumer companies like Xiaomi, which is also doing cars, phones. Lenovo, they're all doing chip design. So it seems stable at the moment.

Pretty good. Again, I think I said I want to touch on M&A and maybe 2 parts to this question on Hexagon in particular. It looks like a good deal. Where is your integration priorities here with this business? And what are the main milestones we should be focused on? And then maybe secondary to that, is there a sort of genuine revenue synergies you can talk to today that maybe benefits your position in physical AI applications?

Oh yes, I'm very excited about Hexagon and working with Ola, who's the Hexagon Chairman, and because they're -- I think it's like a diamond in the rough, the simulation business of Hexagon. Because Hexagon wants to focus on other things. And it was like a one -- only one simulation asset, whereas we can integrate it much better in the Cadence portfolio. And 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. So the reason for Hexagon was, is primarily for physical AI. So the 15% of our system business is anyway growing like 20% plus for 5, 6 years. I started all this in 2018. That was not -- that time was not clear. People said like, 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. So now it's like obvious. But one thing that is -- but '25 is not '18, right? So things are changing in the system business. And the growth part of the system business, I mean, we don't need all of the -- we have enough portfolio, but the exciting part of the system business to me are 2 parts. And that's what we want to focus on. And I think we will cross like $1 billion run rate in systems reasonably soon, assuming M&A closes and all that. So one part of system business, which is high growth is 3D-IC which is close to the chip, right? And we have a very good position with Allegro, because 3D-IC is another word for a system in a package. Now there's 3.5 DIC, did you know? That's possible, right? It's 3.5 DICs, right, which is a combination of 2.5 and 3D. But anyway, I think that one focus will be 3D-IC, which is Allegro, packaging, clarity, thermal, electron, all that, okay? And then the second -- which is going to be high growth anyway because all the segments in semiconductors will go towards 3D-IC or 3.5 DIC. And then the other part will be physical AI. So I talked for a long time about the 3-layer cake. I don't know, people say like, are you like a bakery or something? So if you don't -- the reason talk about 3-layer cake is because unless you are like a 2-year old, when you eat cake, you eat all the layers together or consume all the layers together. So what are the layers of the 3 layers? So there AI, of course, stop with a layer, which a lot of people forget is principal ground truth, right? How transistors work, how molecules work, and bottom layer is silicon or domain-specific silicon. And then there are 3 phases of that infrastructure, physical sciences. So in my mind, this is like the 3 by 3 metrics, 3 horizontal technologies and 3 vertical applications. So now I mean, we can talk about this a lot. Like people who graduated just like a few years ago, they said, "Well, all I need is AI, right? What do I need anything else? I can fit a model for everything in life. And people who graduated 30, 40 years ago, they said like, what's all this [indiscernible] ." I need ground truth. I need to know how things really work, not a model, okay? I said, "Well, I don't want to take any sides. You need both. And actually, in our algorithms, always there was fundamental algorithms and data-driven algorithms, okay? Of course, they're not much more powerful with AI. So anyway, we need all these 3 things, okay. Now with physical AI, all the 3 layers of the cake will get transformed, okay? So the bottom layer, which is silicon is, of course, different. Just look at Tesla or BYD. The chips are much lower power. I mean they are all custom chips for physical AI, whether it's for cars or robots or drones. There will be more mixed signal, and there will be lower power. So anyway, we are very well positioned for that. We were -- we didn't need Hexagon for that. We were already very well positioned. All the big auto companies, semi companies are big Cadence customers and then all the newer ones we are working with, like I mentioned. So -- but the other 2 will also change, okay? And I know this for a while anyway, but what the AI model, what will fundamentally change in the AI model, and there is more and more talk about this is, the AI model will move from a text model like an LLM model or a word model, WORD to a world model. Okay, my kids say, my word and world sound the same. So this is the one with the L, WORLD model or the physical model. And all these companies are working on it. So what happens in a physical world model, like in 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. So you have to gather it like you have to hold this bottle. And so either you put sensors and do that. So that's very slow or you have to put simulation in the loop to generate data. So first, the model will change to a World model with an L. And then you can put the middle layer, the principal simulation in the loop and accelerate with AI. And the main technology you need, there is what is called multibody dynamics or simulation of robots and card. So Hexagon has the best multibody dynamic simulator, #1 in the market. So then that's the reason to acquire Hexagon so that we can be as relevant in the physical AI as we are in the infrastructure.

Got you, yes. Maybe if we stay on that point there because I think that's quite interesting. If we are -- 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 2 possibilities. We can have simulation readiness in the loop or we can have a real-time sensor appreciation. But it's a software solution is what you're adding?

Yes, both of them yes, we'll have both. You'll have the answers anyway on the silicon side. The silicon will change. But the inference will change because -- and 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 the robot. Of course, the silicon is different. The inference is different, but the model is trained on the data center, right. So it helps the -- it might pay further. But the thing will be that we just want to be -- make sure we are completely ready for this phase as we are. Like in the infrastructure phase, we are working with all the leading players. And this one, we needed some pieces, especially I think simulation in the loop will become even more critical. So that's why. So Hexagon is a great asset for that. And then we can integrate with the 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. So good integration with there. The other question I wanted to ask, maybe I'll open up the floor after. We are getting used now to collaborations for, NVIDIA is having with the ecosystem broadly. And 2, 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? And maybe there was a nonexclusive deal done or collaboration with Synopsys and what your sort of views were there? And should we focus on that nonexclusivity in that deal when thinking about yourselves?

Well, we worked with NVIDIA and Jensen for years. So actually, and we even released -- some of these recent news is like porting their software to GPUs and all. But I've been doing that for years. So if you look at even Cadence announcement from 2 years ago, it covers most of these topics, okay? And we do it in EDA, we do it in SDA, we do it in biodrug-discovery. So we are glad to have NVIDIA as a great partner. And our business with NVIDIA is growing. And 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. But our partnership with NVIDIA is fabulous, and we cherish that. But 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 how 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 will be a lot of other great company. So we want to make sure we are -- the benefit of EDA's horizontal technology. So we want to work with all the great companies. And Intel, we'll -- I mean we have, of course, my predecessor is there. We have a lot of discussions ongoing with Intel to see how they progress, especially as they focus on [indiscernible]

Precisely. Maybe with that, we'll open it to the floor and see if anyone's got burning questions. Not at this point. Maybe just one with a minute to go. Clearly, with -- there's a little bit of margin pressure as you transition to annual subscriptions and some of the SD&A business. Help us understand what is that? Why are we doing it? What sort of margin pressure should we expect?

No, this -- I mean, this is -- we always do things for the long run, okay? So like we have a recurring business in EDA, which is great. I think what happened in SDA is that the accounting treatment is different. Then EDA by nature is recurring. SDA by nature because of the accounting rules is upfront. At least some of the business we are buying upfront or we bought -- so 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 like multiyear deals and you take upfront, that's not healthy for the business long term. So 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. So there might be some 1-year impact. But still it's not going to be that significant given our scale. And the other thing is our incremental margin on our organic business is close to 60%. And our goal, of course, is a 50% plus incremental margin, which we have done for almost 8 years now. So 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. So if you combine '24 and '25, our incremental margin is 53% or 54% because it was slightly less last year and it's more this year. So maybe '26, '27 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. And whatever transition we do for the long run, we will recover that in '27. So I think we'll not do any M&A that destroy this fundamental financial model that our margin goes up, of course, revenue should keep improving. And then we buy half of our -- use half of our cash flow to buy back stock, primarily to make sure there is no dilution. So if we do like 8%, 9% SBC, we buy back more than that. So that is not going to be changed based on M&A. So that is intact. But there may be some movement like 1 year, slightly less incremental margin other years slightly more, but it will be more than what our operating margin is.

Sounds clear. Anirudh, thanks very much. Clocks taking our time. Thank you.