Good morning London. I want to say how's everyone doing but it's probably not appropriate. Let's start off with a safe harbour. Okay, 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 Anrud Devgan here, CEO of Cadence Design. Anrud, 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. So well done, London. Okay, 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?

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. So almost any chip design in the world today uses some form of cadence products and about 45 percent of our customers are now system companies you know like phone companies car companies hyperscalers and 55 are semi companies semiconductor companies so they're also increasingly becoming full stack company on the semi side and then you know we are i mean one key thing about our software is 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, 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 5 to 10x more efficient, in a 10% to 20% better performance, power performance in the area. So there are two ways we are benefiting from AI. And we are lucky to work with all the big players, all the Mac 7, and about 60%, 70% of revenue is coming from about 60 companies. And these are all the who's who in the tech world. That's like a brief summary of cadence.

That's pretty good. I mean, 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, you know, EDA, systems, NIP, 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. So we are seeing that, of course, in infrastructure AI. So I always believe there are, I believe this for several years now, that there are three phases of AI. So, there is infrastructure phase, which is what we are in now. So, that's data centers, of course, semiconductors, LLMs. 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 three 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 three. So actually at this point, all the three businesses are doing well. They're growing pretty well. and we also, for those who are not familiar, are 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 near future and that's our goal. So we want to obviously have growth but profitability at the same time.

Makes sense.

And all this, we also keep an eye on SBC, so stock-based comp. So that's about 8.5% or something. 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, you know, we saw some of the, let's say, you know, 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? And then also, what do you see as the sustainable growth rate, perhaps, in IP going forward?

Yes, yes. So we are at 5.2, 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 three are doing well. Now, IP is good, but it's always slightly less profitable than software. So IP means we design certain things and pre-made 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. So because these are protocol-based IPs, like DDR or HBM, so the functionality is kind of basic. It's given. And how customers choose IP is 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 more on what I would call HPC IP and more at advanced nodes. So basically TSMC is advanced nodes. And there are five main IPs there. So there is UCI, which is, I mean, sorry for all the technical lingo. UCI is chip-to-chip, you know, HBM memory, DDR memory, PCIe, and CERDES. So at this point, we have all the five 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, you know, like ARM cell scores. Tensilica is number two 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 two years already. So first year I didn't talk about it because one 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 got Secure IC. We bought HPM from Rambus. So yeah, 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.

Yeah, that should definitely be. Gotcha. No, our focus always is win with the winners, so we always focus on the top first. And there, you know, portfolio has to be big enough, but they always buy best in class. You know, there is very little bundling at the very top because, I mean, they have enough money and resources and, you know, 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, you know, sometimes we can publicly talk about the customer, sometimes we can't, but IP business is doing very well at the winners, at the top companies, yeah.

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're being pretty clear that China's 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 two, three years?

Yeah, I think China is back to normal, is what I would say. And, you know, 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, right? So the reason I said it will be flat is when I went to China in last November, they said, oh, 25 will be a very difficult year. It will be the worst year for US-China relationship. So I think China has always been well prepared in this kind of 25. And then they say, oh, by end of 25 or beginning of 26, there will be a deal. okay and and they just want to make sure they are not after the deal they're not overly reliant on u.s so they're like three step ahead of 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 why you know we should be more prudent and that's what happened i mean you know and 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. 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 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, you know, designing a lot of things. I mean, infrastructure, AI, of course, you know, all these big companies. You know, Alibaba and all those are designing chips. And also, physically, they are huge. I mean, there are like five 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. 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 and what are the main milestones we should be focused on? And then maybe secondary to that, is there sort of 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, you know, who's the Hexagon chairman. Yeah. And because they're, I think it's like a diamond in the rough, you know, 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, you know, 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 five, six years. You know, I started all this in 2018. But that time was not clear. People say, like, what is this 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, you know, 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. And I think we will cross a 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 3DIC, which is close to the chip. And we have a very good position with Allegro, because 3DIC is another word for system in a package. Now there's 3.5D also, did you know? That's possible, right? It's three and a half DICs, right? Which is a combination of two and a half and 3D. But anyway, I think that one focus will be 3D IC, which is, you know, Allegro, you know, packaging, clarity, thermal, electromagnet, all that. And then the second focus, which is going to be high growth anyway, because all the segments in semiconductors will go towards 3D IC or three and a half DIC. And then the other part will be physical AI. So, you know, I talked for a long time about the three-layer cake. I don't know. People say, like, are you like a bakery or something? So, if you don't, yeah. The reason I talk about three-layer cake is because, unless you are, like, two-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 three-layer? So, there's AI, of course, top. Middle layer, which a lot of people forget, is principle, ground truth, right? How transistors work, how molecules work. And bottom layer is silicon or domain-specific silicon. And then there are three phases of that, infrastructure, physical, sciences. So in my mind, it's like this three-by-three matrix, three horizontal technologies, and three 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 is anything else? I can fit a model for everything in life. And people who graduated 30, 40 years ago, they say, like, 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. And actually, in our algorithms, always there was fundamental algorithms and data-driven algorithms. Of course, they're not much more powerful with AI. So anyway, we need all these three things. Now, with physical AI, all the three layers of the KIG will get transformed. 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'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. So anyway, we are very well positioned for that. We didn't need a 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. But the other two will also change. And I know this for a while anyway. But 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 word model. Okay, my kids say my word and word sound the same. So this is the one with the L, you know, W-O-R-L-D model or the physical model, you know. And all these companies are working on it. So what happens in a physical word model, like in the LLM model, you can train, you know, 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 word model for robotics or cars, the data is not available, you know, so you have to gather it, like you have to hold this bottle and, you know, 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.

Yeah.

So first the model will change to a world model with 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 is what is called multibody dynamics or simulation of robots and cars. So Hexagon has the best multibody dynamic simulator. Number one in the market. So then 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.

Maybe if we stay on that point there because I think that's quite interesting. And if we're, 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 for.

Yeah, both of them. Yeah, we'll have both. You'll have sensors anyway on the silicon side. The silicon will change, but the inference will change because, you know, you, 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. So 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 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. You know, beta is the other acquisition we made, which is also doing very well to make a full flow for this kind of physical AI.

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 for NVIDIA's 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. And maybe there was a non-exclusive deal done or collaboration with Synopsys. And what your sort of views were there, and should we focus on that non-exclusivity in that deal when thinking about yourselves?

Well, we worked with NVIDIA and Jensen for years. So actually, you know, and we even released, you know, 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 Caden's announcement from two years ago, it covers most of these topics, okay? And we do it in EDA, we do it in SDA, we do it in bio drug discovery. So we are glad to have NVIDIA as a great partner. and our business with NVIDIA is growing. And 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. But our partnership with NVIDIA is fabulous and we cherish that. But in terms of investment, you know, we would like to get business from NVIDIA and investment from you guys. That's why I'm here, you know. That's our style. And then, you know, we also want to be, you know, 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 companies. So, we want to make sure we are, you know, the benefit of EDA is horizontal technology. So, we want to work with all the great companies.

Makes sense.

And Intel, yeah, we'll see. I mean, 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 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 SD&A business. Help us understand, what is that? Why are we doing it? And what sort of margin pressure should we expect?

No, I mean, 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 a front. At least some of the business we are buying are a front 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 multi-year deals and you take a front. 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. So we'll take it all the way. But in the end, you recover all that revenue and more in the future. So there might be some one-year impact. But still, it's not going to be that significant and 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 50% plus incremental margin, which we have done for, God knows, eight 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 percent because it was slightly less last year and it's more this year. So, you know, 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, you know, with M&A. And whatever transition we do for the long run, we will recover that in 27. So, I think we will not do any M&A that destroys this fundamental financial model, you know, that our margin goes up. Of course, revenue should keep improving. And then we buy half of our, you know, use half our cash flow to buy back stock, primarily to make sure there is no dilution. So, you know, 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, you know, one year is slightly less incremental margin, another year is slightly more. But it will be more than what our operating margin is.

Sounds clear. Anruud, thanks so much. Clock's taking our time.

Thank you, yeah.