So for those on the broadcast, just letting you guys know, we are now live in session.

Okay, so we're live. So I want to thank everyone for either attending on the webcast or coming in person. We do really appreciate that. And also, for those of you that flew in from out of town or drove down from the city or whatever, we do really appreciate any level of commute that you maybe know. It's not easy to get around these days. And I think some of you came from the East Coast, and maybe you avoided snowstorms, so that's the positive side of that. We're going to go through our Analyst Day briefing. We do this every two years, so the last one was 2023. And I will start it off. Adnan will pick it up, probably go over the parts of the slides that you really want to see anyway, and then we'll get back into Q&A and Kim and Adnan and I will. So basically, themes for today. Hopefully you saw it if you're attending here this morning. and I think it's relevant to both our investors and our customers. The semiconductor industry is evolving into the 3D era, I call it, and we are looking to be a $1.1 trillion industry by 2030 if you look at the semi numbers or handheld numbers of IDF. And we think when you look at that, that means the industry does need a unified analytics platform You probably saw with the discussions we had in the meetings today about what we're doing with SecureWise and generally the way that we're looking at the orchestration products. Our mental model many years ago, we started on this idea of putting Accenture in the cloud first around 2019. We first started bringing that out to customers. At that time, our thought was once you get the system in the cloud, you want to then make it usable by everybody else. If you notice, we hired our first partnership person, Bill Lee I think is in the audience, to start our partnership program in 2020. It's like okay, once you've gone through the trouble of getting your manufacturing data in the cloud, then you want to start using it with other systems. We then evolved that to then think about how do you then access the tools that you operate on. That was why we acquired Symmetrics, why we started thinking about the partnerships with folks like AdventTest and Teradyne and how you actually can work with the tools first in test but then more broadly across the entire test platform. And then with SecureWise, what we realized was you could have great stuff going on in the lab and at the floor, and you could have great stuff in the cloud, but if these two can't talk, then you can't get stuff done. And SecureWise really was another piece. And our mental model in all this is that eventually PDF becomes a platform for the industry. Every customer has their own instance and their own capability, but it's connected to every other. And you saw that in Aziz's presentation, if you attended this morning, where their vision about why they went with Accenture and PDF was because they know a lot of the customers they covet also use it. And they could provide a better level of connectivity between themselves and their customers if they could both communicate on Accenture. And that's really getting us to why we think You know, the reaffirmation that the industry does need a unified analytics platform. And today, you know, we're the largest independent analytics platform business out there, not attached to something else, and we think we're growing in industry relevance. So, these are the themes for today. We'll talk about what that means for our stakeholders a little bit later. These numbers are from IBS and Handel. He shows about a 10% cargo this morning. I showed a 12% if you go back to a little different time period. But in the end, whatever it is, it does mean about a $1.1 trillion business where 67% of all silicon really is related to AI, but not just AI in the cloud, greatly in the edge. And that's where most of the growth actually is. And when we see this with our customers, it is a tale of two worlds, It's our customers that are not as exposed to what's going on in AI are growing less fast than our customers that are. Tonight, the fireside chat speaker is going to be Tom Caulfield, who's a great speaker and a great friend. And Tom pointed out, like I've heard Tom point out a number of times, it took our industry about 60 years to achieve a $500 billion in scale. And in the next decade, we will achieve the next $500 billion in scale. And that's pretty staggering, and it gets there, as I said this morning, through three different, really big different things that we think have to come in. One is innovations in 3D, a much, much more complex supply chain, and leveraging AI to drive efficiency in manufacturing. You know, 3D, again, as I said this morning, it's important to remember this, it is not just in the packaging world, it is also very much in the front end factories. I know we talked a little bit about wafer-to-wafer stacking for backside power, but also if you look at 3D NAND, 3D DRAM, everything is looking at more applications for wafer stacking. In the back of the room here is S.W.'s son, who's also a good friend of ours, and S.W. really what he did at XMC was really the first wafer-to-wafer stacking on vertical NAND. And I think that innovation is happening across the industry. That really does mean the way you think about manufacturing is changing greatly. These two drivers are a big part of the drivers of our innovation on what we do on characterization. That includes the e-beam capability, what we do on data feed forward and the analytics capability because you have a lot more sharing across the production flow. You know, I think our industry always felt like we were not appreciative, kind of the Rodney Dangerfield of the world. The chip industry was never appreciated that much. And now we're strategic. And what does that mean? That meant governments started investing in facilities and factories. It also means that governments have a lot to say about the supply chain. One of the things that we see is increasingly important for our customers is the way we manage and handle data and data governance. Most of our customers sell around the world. Most of our customers have people around the world, and most of our customers have operations around the world. That means how we store and protect their data and what protections we have on individuals for the European engineers or employees is different than their Japanese ones or their American ones or their Asian ones in China, and also data governance. When you look at SecureWise and providing a network, data coming off tools in China often has to stay resident in China on that network, even though it's being shared between an OEM and a factory. This is increasingly for us, we think, something where PDF is building a capability and more and more important, a point of differentiation. Lastly, when you look at what's going on, because we're looking at building fabs around the world, it really is a huge step backwards from what the industry was doing. For the last 60 years, we concentrated production in a smaller number of sites, and that gave you the most economic leverage. And then, you know, for a variety of reasons, access to markets, as I said, access to human capital, access to energy, factors are being built around the world, and it's not cost effective. I think, you know, when this first started happening, you know, the founder of TSMC, Moistrong, was quite vocal about the fact that it won't work. The economics will be terrible. And that's in part because capital costs and labor costs are higher, but it's also just because it goes against what we've all known about manufacturing, which is the learning curve. The person with the biggest volume goes down the learning curve faster and first and with lower cost has the best ability to continue to compete. And our industry has lived well in that way, and now we're asking our industry to do something very different. There is AI, though, and there are ways now to get a lot more information out of the same amount of data than you had in the past. And we think this is super important for our customers because of the talent shortage, because of the requirement to have smaller facilities located around the world, and because of just the complexity, the systemic complexity of what they're trying to build. But when I look into my notes, some of you have been shareholders for quite a while. So really, for some of you, and for certainly us, we started out really building on that first pillar, what you do for characterization. That started with our test vehicles and the characterization vehicle infrastructure. We monetized that, if you remember, on the gainshare business model. We would deploy the system and then charge a royalty based on the yield the customer ended up achieving. We've repurposed that capability and expanded it to include the electron beam in-line ability to measure product directly and put that as part of a subscription much like the rest of the infrastructure. And we expanded it starting around the 2010s to include Accenture and the ability to start doing analytics for fabulous customers and the product groups inside the IBM. So if you look at our largest customer – part of the customer base, our two largest components of our customer base are the equipment vendors themselves and the fabless system companies and the product groups inside the IBMs. So I think lots of folks always think about PDFs for manufacturing, and we have a lot of fab customers, and most of the fabs use our systems. But there are not that many fab owners in the world. The majority of our customer base is actually the vendors that supply equipment to them and the consumers of material that's produced at their factories. Recently, starting around 2021, as we started getting the systems up and the partnerships started building, Tim and I worked very closely with SAP in the early two or so years just to find out how could you start bringing a real-time view of manufacturing into the hands of the finance teams. How do you have a more accurate understanding of cost when you have an RMA? How can you react more quickly and more thoughtfully? And this is really the Sapient's manufacturing hub, which we then blossomed into this portfolio of supply chain orchestration. I think earlier today they made reference to Sapient's supply chain hub, Sapient's manufacturing hub, and we will be demonstrating supply chain hub, which is the newest member of that category, I think over in the room to my left to your right. And there's some presentations about that tomorrow. But we recognize that orchestration goes on not just within the customer's organization but across the industry. And the SecureWise network is enabling us to make that possible.

Our customer base spans the ecosystem.

You know, I think what's very unusual about PDF, a lot of things are unusual about PDF, but one of them is just the breadth of customers. You know, I go back to when we were a yield ramp-focused customer and supplier in 2009. I remember meeting with the then Chief Procurement Officer and Chief Information Officer at TSMC, a guy named Steve. And he says to me, John, what's going to happen to your company? You have three customers left in the world. Samsung, us, and Intel. That's it. Three customers. Who else is going to buy from you guys? And I thought about that quite a bit. We thought about that a lot. And if you look actually, from 2009 to 2014, we made almost no acquisitions. We really just thought about what did that mean? What we realized is you concentrated manufacturing capacity. You've had an explosion of the number of equipment vendors that were out there supplying them and the number of product companies that are using it. And I think when the slides were shown this morning, you saw the talk around application-specific silicon and more and more application-specific silicon. And we thought everyone's ultimately going to be responsible for yield in manufacturing. And we could really look at this as a different way. If we changed our products around, we could really think about the market more broadly. And today, you see the outcome from that. We really span the entire ecosystem because everyone is responsible for manufacturing these days. The equipment is so complex, without the help of the equipment vendors, the factories couldn't use them. The designs are so complex, just to understand the test programs and what they mean, the fabless need to be intimately involved with what's going on in the front end fabs and the test floors, and up and down the supply chain. We really appreciate the feedback we've gotten from customers this morning. Mike Campbell talked about that a little bit, but over the years at our different user conferences, we've had different customers say different things about us and kind of put these quotes here. But what we try to be as a trusted partner for our customers, one of the slides I showed in 2023 was the last 25 years of changes in compute environment from Unix systems and Windows and Linux systems and CPUs to GPUs? And then what do we do to help customers move their workflows forward while the underlying IP layer changes? And when you think about these manufacturing assets that are being built around the world, these fabs will last 30 years. For a long time, what we did in our industry is we set up the fab, we installed the software, and then you change nothing. Change nothing on the software, run the same NES system, and run the same software for as long as you can. And that's like saying your brain is never going to get smarter. What AI has done for our customer base has got them to start thinking, well, wait a minute, I could get smarter over time. I could use analytics so I can get more out of this factory to run this factory differently. So this trust is really important to us because to us, earning their trust means that we can begin the dialogue of how we can help them use software in more innovative and sophisticated ways to get more value out of the assets that they own. That was kind of why at the end of my talk this morning, the call to action was around, let's look at all the waste that's still in this industry and how do we help drive a lot more opportunity out of that waste. As I said earlier, we began partnering around 2020. If you look before that, we didn't really see partnerships as being all that important. Again, because when the focus was just bringing up the yield ramp, there was really no time to work on a partnership. As we started moving customers to the cloud, we just thought more and more ways that partnerships were important. And this is a subset of partnering with. We continually look for new ways to expand the partnerships. Kim is a super big proponent of this inside the company, that even if you say, well, don't we compete with this company on this or that, the most important thing is to deliver more value to our customers through partnerships, which is also why we're very focused on standards. And today, when you look at the company and the scale that we've achieved, while we're, let's say, a $200 million business today, the scale and our reach in the industry is quite broad. We manage quite a lot of data. We transmit exabytes of data across a secure life network. And we provide enterprise capability on what we do on the cloud. and more and more what we're doing with standards bodies. I show here SOX2 and ISO 2701, but we also are supporting NIST2 and CRA and maybe European standards as well for our European customers. And this is a growing piece of what we're doing with this whole platform. I was meeting with one of the SecureWise customers, a large equipment vendor, and they brought their CISO to the meeting. I thought, oh, this is going to be interesting. I wonder what tough questions he's going to ask. And the person presented what we're doing on standards around the world for SecureWise and Accenture Cloud. And the guy stopped and said, wait a minute. So if we're using you guys for these things, I can just refer to you when I go get my CRA certification in the EU. I don't need to go and worry about that. And the answer was yes. And this is increasingly an important point of differentiation for our customers. We are making sure our customers can trust our systems out to the edge. When we talked about the fabulous work and the encryption out to the edge, they can understand that we're going to stay on top of the standards that are required so they're able to take advantage of the systems. And it greatly reduces their need to work on this stuff. So I want to provide a little bit of context when we go through TAM numbers for us and how we think about the business. So I talked about a $1.1 billion semiconductor industry. And if you would go back to 2019 or 2018, we really didn't serve the capital equipment industry. So our market opportunity was the manufacturing portion of the IC industry. And if you say the IC industry is roughly a 50% gross margin industry, then you'd say at a $500 billion size in 2020 or so, there was about a $250 million manufacturing business where software could add value. And then we add on top of that the capital equipment business because that's increasingly a customer base for us. Today, if you kind of project forward to 2030, you take that portion of that $1.1 billion industry that is manufacturing-oriented and add on to it the capital equipment piece. We think this is the customer base that we sell into. That is not our market opportunity. That's just the customer base we sell into. We think the addressable market for us, which has doubled over the last four years, will again more than double over the next seven years. As software for manufacturing becomes increasingly important, the manufacturing volumes go up. That's the right-hand side of this chart. And the need for more and more complexity in analytics continues to go up. When you look at how we've grown our business, that's why we put the left-hand side of this chart up, it doesn't mean that we bring the products to market the same way or the same capability. What's core and always been core in PDF was taking a system view to manufacturing to understand the design aspects, the process technology aspects, the manufacturing and the equipment aspects, and how those integrate together. That was, you know, as I said this morning, PDF stood for. It would be more portable document format. But what we show here is the way that we've layered on more and more capability reusing, and then, you know, from a combination of reuse, development, and acquisition to create new ways of helping customers capture the value in manufacturing. So today, still important, is our characterization of vehicle capability and the ability to characterize next-generation nodes. That continues to be important. We've enhanced that with what we've done on the DirectScan program. Later on top of that, starting in the 2010s, was really the way of having Accentio combine process control information, testing operations, offline manufacturing analytics to enable the customers to really look end-to-end at their data. That was really the next foray. Starting around 2019, customers started migrating that to the cloud, at least for the central and offline analysis capabilities. And that continues to be a very important piece of our business. Around 2020, we started adding the ability to give tools and capabilities to the equipment vendors. so the equipment vendors can be able to add more value to their customers, provide more AI-driven solutions, more analytics capabilities. And with that, we started recognizing the need on supply chain orchestration for a couple of reasons. As I said, most of our customers can't deliver value without crossing organizational boundaries. They need to get from their organization to their supplier or if they're an equipment supplier, to their customer. so orchestration increasingly became important we see that as a significant growth sector for us over the next five years and then you know um uh maybe was lost on on some folks when saeed presented but when you think about and we've you know we've been in the ai business for many years and and machine learning and analytics when you think about how you look at uh large language models, agentic flows, and how you bring that to manufacturing. Guardrails are really super important. You know, what Asahi pointed out this morning, what is hallucination is also imagination. I think, you know, my wife is a super linear thinker. I'm kind of a scatterbrain kind of guy. I think I get more creativity off being kind of like all over the place sometimes because you see connections between things. And when you let things hallucinate, you get that kind of creativity stuff, sometimes wrong, when you've kind of got a very linear flow, you kind of get repeatability, which is what manufacturing is all about. What we're doing with orchestrations and why orchestrations and workflows are so important in the next generation of our products is really around enabling customers to turn that dial between creativity and predictability. That's why we see the next phase for what we're bringing to the customer base, really an AI-driven manufacturing flow, and why we think it's so important for our customers, and as a result, hopefully for our business. So that kind of gives you the update of how we're thinking about the business strategy and what's going on. Now I'm going to turn it over to Adnan, who's going to talk about the part that you really all sat here for anyway. So I was kind of like, I was the preacher before the cookies at church.

Thanks, Adnan. So when I was thinking about the transition about how to come in at this point into the presentation, yesterday I had a different idea. But this morning, for those of you that heard Don's talk, talked about how parents always evaluate you on an integral function basis. So the point of this was to present a 10-year view to the investors. Yes, it's sort of a report card. I understand investors' past performance is not indicative of future results, but everybody, even after those statements, will ask, what have you done for me lately? So this is the perspective on what we have done over the last 10 years. And really, if you think about it, kind of year 6 through 10 going backwards was where the transition was happening for us to the analytics phase. If you recall back in 2019, 2020 timeframe, it's only started to break out with our 2019 analysts say the breakout of revenue into analytics and IYR. It made sense for them. Today, we'll present some other perspectives as well later in this discussion, so we'll What has happened over the last five years has been this growth. If you go back and think about the analysts that we did in 2023, there were three long-term target growth rates or target model metrics that we had set for us. One was on the revenue growth rate about 20%. This is 19.5. Kim and I had lots of discussion about it doesn't run to 20, but left it at 19.5. That's one metric here. But look, a lot of this is not just a function of, okay, industry happened. Yes, there are things happen along the way. For example, in 2020, we acquired the metrics. That was at the tail end of 2020. So initially, when we posted the 2021 numbers, of course, the curiosity was, well, you posted this 26% growth rate in 2021, but it was helped by the metrics. But the following year, 2022, again, against the backdrop of a strong industry, we were able to post 34% purely organic growth rates. And along the way, why this has happened is because we've done some things. I mean, John and Kim have a relationship with who of the people in this industry. You've seen the names mentioned. You've seen people talk. I think one of the things that we did was we came together as a team, especially as our number of customers expanded. And in 2020, we started to think, how do we take a relook at our bookings and how we approach customers? So I remember we formed this exec booking meeting that we started to do on Mondays looking at who are the key customers, where are we stock, who can unlock the ball and kind of move that deal forward. And between a few of us, legal finance, product, as well as John and Kim and relationships, we really made a difference in terms of the booking rates. If you go back, you'll see a big jump there. So that's our report card through 2024. 2025, as you know, we've guided and reaffirmed in the press release today the growth rates that we had talked about earlier in the earnings call as well of 21% to 23% growth rate would be acquisition, of course, of the SecureWise that we did in this part of the earlier part of this year as well. So within that, if you zoom in and say, okay, from 2020, and this one, last slide was through 2024, this one is trailing 12 months of the Q3 of this year, it's been a 20% CAGR during this time frame. But again, within that, what was happening was We were going away from IYR and moving towards the analytics. 2019 is the time where we started to offer some of the cloud solutions. So, you know, typical three-year deal, 2022 is when those came up for renewals. You've heard us talking, for example, a Q3 call last year about how some of the customers' usage rates were able to expand as those deals ended and renewed. So what's been driving within the total growth of the 20% has really been the analytics growth at a much faster kicker at 29%. You can see the numbers on the bottom right as far as how analytics has contributed, and frankly, why we're thinking of another different cut. Back to 2019 when we presented the analytics IYR, the business has transitioned to now 94-ish percent on the analytics. So that was some of our thinking why we presented you a couple of different cuts today as well. The other two metrics of the three, one was revenue growth that I talked about earlier, but the other two metrics that we talked to you about in 2023 analyst day were gross margin kind of the horizontal lines on these charts. 2030 targets of 75%, and then the operating margin target of 20%. And if you look at our progression over those years, it's pretty remarkable where we have come from. The non-gap gross margins on the left side from the low 60s to now in the middle of that, slightly exceeding that range at 76%, which is why we're here at the analyst day. So to John's point, we'll save some of the cookies for later. And then, of course, on the operating margin side, we're just kind of inching up to it. but getting there where it makes sense to start talking about some of the new things that we will today. I'm pretty pleased with this transition. And actually, if you think even more on the operating margin side, the fact that we've gone from a negative all the way to the plus 20% range. Okay, so this is one perspective we wanted to share with you on revenue. Historically, like I said, we used to report it as analytics versus IYR. To us, as you've heard the word platform ubiquitously today, to us it made sense to start looking at the revenue on a platform revenue breakout versus the volume. And I'll explain that in a second. The left top chart, we put it as reference. Really, to me, the interesting part is the annual and the kind of PTM patterns, if you will. Let me explain the characteristics of the right side in a second. But if you think about it, total growth rate is from $149 million to the $207 million. But within that, what's interesting is the platform growth rate that has gone from $120 million to $170 million or so. So what is platform? Platform is everything that you know of and classically expect within a PDF. It's a SaaS software that we sell. It's a term-based licenses, perpetual, as well as a DFI and CV systems. When we separate out the volume-based revenue, in that we do three things, the symmetric runtime licenses, the secure-wise, and the gainshare. To us, the reason why we call it volume-based is it's directly tied to the customer's shipment or production outputs. For example, symmetric runtime licenses. We go through a validation cycle, as John talked about earlier, of a software development kit, having the customer validate the software for the tool shipments. But really, the revenue on this symmetric runtime license is going to come when the customer is going to ship their equipment. Similarly, on the Securewise, the data component of it, if the customer is going to use more data, that's what's going to anode to our benefit. Lastly, similarly, on the gainshare side, we do the fixed fee part of the work, and then we benefit when the customer will do the gainshare. Now, the interesting part about all these three is these three are high-margin contributions to our business. Really, if you think about it, in all three cases, we've done the work in the platform side as well to get to enjoy that. If you think about the Symmetrics runtime, we did the software development kit work, which we think of as formation as part of our platform revenue. SecureWise has a software piece that provides the connectivity that's also in our platform revenue piece. Same thing for Gainship. We do the fixed-fee work with the customer, and that forms part of our platform revenue, which will then benefit us as the customer produces higher and higher volumes in the volume-based revenue side. This is another cut a lot of you have been asking us about, recurring versus upfront revenue, and I'll describe it in a second. Again, quarterly data on the left top side, annual data on the bottom left side, but really what's interesting to me is the first bar, which is a recurring portion of the revenue of $140 million, and then the last bar, which is $180 million. When I explain on the right side, I'll explain why. So let's just get there. On the recurring revenue side, again, like your investors would know and expect software companies to include, we obviously have the SaaS piece, the software piece, maintenance services that we have as well, as well as the DFI and TV systems, and we sell them on a subscription basis. We also, of course, have the Symmetrics software pieces, the Symmetrics business itself, as well as Securewise and Gainshare. Legal would be happy and wanted me to say this, so I will say this. within our recurring, those last three pieces, the Symmetrics, the SecureLize, and the Ganture, you call them reoccurring businesses. Similar to the thinking that we went through the last slide, runtime licenses and the customers will ship more, we'll get benefit more of that, and similarly for SecureLize as well as Ganture. But to us, these are businesses that will reoccur. And if you look at a little bit of a wider time horizon, they start to look like recurring businesses. We won't expect them to go to zero. Sure. In between some years, there might be some ups and downs, and that will cause the way we are measuring recurring revenue to have some different patterns. But over the long term, hence I point out to the starting and the ending points on the left side, they will have a pattern and a characteristic that we like. If you go back and do the math, you will see that it's about 80% of our total revenue is of a recurring nature. So today, 207 million LTM based on a revenue company doing about $180 plus million in recurring revenue. In the upfront revenue section, just to highlight, It's on the slide, but again, no surprise what you would expect. It's the three pieces of perpetual software, and when we do a CapEx sale of the DFI systems, which we have done, and then also certain of the IP licenses where we'll use some of the technology and license it to the customer. The other question that everybody has asked us, especially as we've taken our debt, especially as we've increased our CapEx rates, is what is the return on the DFI business? Obviously, we've got four machines out there with three customers, and we've talked about how a subscription model is useful. So we thought it would be interesting to share some perspectives as we look at our current deals and as we look to our future deals that we're engaging with customers on. What sort of a return on the machine cost can we expect over the lifetime of the machine? And looking at it a few different ways, actually we did even what our pricing would be versus what the customer might push us to. And we looked at those two different ways and we're coming back with a number of things. Looking at our machine cost investment, we believe there's a 5 plus X return on that investment over the lifetime, which to us is pretty compelling and is exactly the reason why we have invested and continue to invest in that business. Of course, recently we managed the CapEx, as you saw in the most recent quarter as well. And candidly, the machine subscriptions are a strategic shift. If you think about it, this is an industry, as you all know in this room, that is used to getting these machines on a CapEx basis. But to us, there was many benefits that made sense why subscription should happen. It provides the customers the ability to upgrade the machine a few years in. We've already had some occurrences of that, as we've talked about in the earnings calls. As well as for us, as a software company, it makes our revenue be more of a recurring nature, which is exactly what we like as well. And people said, okay, this transition is going to be hard. I remember John making a comment. It just kind of clicked to me at that time. It was AWS, of course, they're selling you hardware, but it is on a subscription basis. Behind that, they have hardware. So it's no different than that, yet it still requires a transition analogous to what the cloud industry went through, where people used to have on-prem hardware or used to buy their own hardware and then eventually got comfortable today that we're seeing massive amounts of investments in the CapEx space. So what does all that mean? Most recent quarter, if you go and look, we talked about a backlog number of $290 plus million. And coming from the 2020 number of $100 plus million, it's a pretty good growth rate. Remember during this time period I also talked about how revenue had grown at about 20%. So what we like to see is, sure, there might be patterns that maybe we don't like it from a quarter to a quarter, but over the long term, we generally like our backlog to be growing faster than our revenue. That to us is what creates a long-term sustainable business. It's also a testament to the relationship that you're building with the customers. They're willing to sign up larger long-term deals with you. I'm pretty pleased about where that stands today. Global geographic revenue distribution, this is all numbers everybody can read, but if you look kind of the last three years, I think one pattern that's interesting to note is if you looked at the bottom two colors, which is the U.S. and Japan, they were about 60%. And if you look at kind of what's happened over the last year, 2024, and even the trailing 12 months, we've managed to distribute that. So it's a little bit, not as much of a percentage as it used to be in the U.S., but it's more like 40-20 between U.S. and Japan. Obviously, people are, you know, people have seen our engagement for some of the key Japanese customers as well as our e-probe shipments that have been talked about, so it's been good to see that growth happening not just in the U.S., but also in other parts of the world. This is a statistics slide you all know, but I mean, kind of required, I felt it's important to put. Left one slide we talked about over the last, you know, five-ish years or so, we spent about $272 million. If you break that up and think about what categories, largely speaking, two-thirds of it will spend on acquisitions. Obviously, we did the Symmetrics acquisition, which was a smaller one at about a $35 million size. And then most recently, we did the SecureWise acquisition, which was $130 plus, so about two-thirds of that total on the M&A and investments. Of the remaining one-third, it's also about a two-third split in CapEx and the remaining portion of about the one-third of roughly we have spent on share repurchases. Balance sheet on the right side, John has made the comment in the last earnings call that as we progress through the next year, we expect our cash provision to improve, doubly on that as we pay down the debt because part of it has the amortization of debt, amortized debt payments, that should create some expansion on a net cash level for us as well. Last slide. This is probably the cookie slide. Let's walk through it a little bit. The first column is a prior target that we had set in the 2023 annual state. Today, we are revising those targets and putting in new long-term targets for our company. Obviously, much discussion, much debate, much planning that goes into it, but let's just walk through it. Look, I think John has talked about – let's go step by step. John has talked about the industry growing at 10%. If you go back and even look at our history, we've grown ahead of the industry. That's where we aspire to be. That's why the bottom comment is there that if the industry is projected to grow at about 10%, we would expect that we would be able to deliver a 20% revenue growth rate for our business as a long-term target model. That's where we felt comfortable. On the gross margin side, we're upping it to 77%. and the number there was chosen carefully in terms of greater than 77%. Some of you could go back and say, okay, you've come close to that number. A few slides ago, we've talked about 75, even 76%. We think there's opportunity there, but we wanted to be careful and commit to you a 77-plus percent number and hopefully kind of go from there against that metric. Where we're doing the bigger change is on the operating margin side, 20% going to greater than 27%. For us, as we're starting to see scale, we are starting to see some of that leverage benefit the bottom line. If you look at the last quarter at 23% operating margin, it's something that felt good to us going from the negatives that we had five years ago. And as we look forward to the future, we believe that whether it's G&A or whether it's F&M, we can have the scale advantages come through while still allowing us the dollars to invest in the R&D line to manage that spend and grow it to serve the opportunity. You heard Saeed talk about 100-plus people that he's had working on the new extensive platform, so excited about that. So I think in terms of targets, those are the new ones to take, and pretty excited about what that does. And, of course, with that, what that benefits the rest of the financial statements as well over the years to come. With that, and the last cookie, I think we will open it up to questions.

Is Mike here correct? Mike's in the back. Do we have a microphone for folks?

We have one here.

We've got two mics. Are there any questions that folks want to ask in the room? Sure. Go ahead.

So you talked about the subscription model and the lifetime revenue increases by 5x. Why can't I just purchase?

No, what we're looking at is if we look at what we spend to build a machine, what's the lifetime return machine? And when we did all this analysis, we did this analysis looking at both a customer buying a machine and depreciating over seven years, a customer subscribing machine. And we set up the economics where actually the economics over a seven-year time period is cheaper to the customer than the customer purchasing the machine. And you look at the seven-year cost of ownership, and of course, they've got to put the capital up front versus the machine cost over time. That greater than 5X is invariant whether the customers purchase the machine or subscribe the machine. We're invariant whether the customers do it. We make it a little bit more economically advantageous to them if they subscribe because we think we can deliver better value over the lifetime. But frankly, we have some customers who buy them. There's some customers that subscribe them. I think he was a little bit off on the number of machines in the field. I think the number is more like 6 or 7, actually, but over a few sites. But in the end, that 5x is just a return on the capital, and you factor this, not just the machine, but the software it drives, the services it drives, all the value that gets created off that machine spend.

Thanks, John. Thanks for doing this. I just wanted to ask you, this morning there was quite a few product, enhanced product releases announced for 2026, mostly coming GA in 26. What sort of has you most excited with these and what do you think has the most near-term impact on this?

Well, I love all my children, but the one that I'm really very, very excited about is what we're doing on scalable analytics. I don't think anyone in the data analytics business, not just in semiconductors, really rethought what you need to do to make it so you can start operating on super-wide data sets and super-huge data sets. And, you know, it was back in 2019, Saeed, Kim, and I talked about this as we were doing the next plan for the next decade of Accentio. We said, okay, we're going to keep going with, you know, a classic BI tool on top of Cassandra, you know, through the remainder of this decade, the coming decade. But we think we need to start thinking about what's beyond that. And so we challenged Saeed in around 2023. They kicked off this effort around, what could you really do if you just thought about, we had put Spark, which is a parallel compute layer, on top of Cassandra back in 2017. And it worked okay for batch jobs, but you couldn't make it interactive because there's no persistence of what you were doing interactively. And the way you store the data in the database to get the efficiency and speed that Ziz was talking about isn't the way you want to analyze it. So starting in 2023, they were like, wait a minute, what if we pulled the data out, put it into another data frame, a little bit different, Python-centric, and operate in parallel with the data and give the user interactive experience? Like why bring 20 million data points to a customer to put up on a screen that's 4 million pixels? You're not going to see it anyway, right? So that's kind of crazy. So they started rethinking all of that, and by the end of 23, early 24, we realized what would work. And they've been kicked off this effort, and it's been quite an effort, as he said, over I think he needs to understand the number because he doesn't want to get too upset on how much we put on that thing. I think that really has a way of just changing the way analytics is done. I think it is the first system out there in the world that really has this third layer. It's not just a BI tool attached to a database. It's a scalable compute layer. I think it will do much like what moving programs to parallel computes like GPs and other hardware environments. It gives that same ability to scale. I think it's super valuable.

Following up on that, can you maybe put it in the context of the share of wallet opportunity that it gives you relative to what you've had before with some of your larger customers if you combine what they can do with scalable analytics, sapience, cloud consumption. I mean, how has that changed your kind of per-customer level revenue opportunity?

I think it's early just to figure that all out. But what I will say is the following. I mean, you saw Aziz talk this morning. You know, one of the super frustrations for us, you know, providing Accenture to the marketplace was they always had internal storage anyway.

He talked about the systems they built around Teradata and Exadata.

And there was a tremendous cost in those systems, and in the end, they pulled the data into Accenture for the analytics and their capabilities. So we really wanted to be able to go back and say, we could build an enterprise-class system they could use broadly. And their commitment to Accenture that they signed earlier this year, as I said, it really is the largest, he said it in the meeting today, It's the largest single deployment at Accentio out there. When it gets to full scale, it will be substantially larger. And it is also, if you look at what their, you know, they also will talk today or tomorrow about using SecureWise as their standard for communicating between their edge and their fabs and their equipment supplies as well as their fabulous customers. They talked about the way that bridges between their data and customers that are using Accenture so they could communicate with them as well. They also talked about what they're doing about connecting Accenture manufacturing data to their enterprise through SAPIEN's capability. Overall, that is the single largest software deployment we have in the world by a substantial amount. And we think they are unique in the scale that they have, but there's a lot of other customers that we see spend really significant dollars trying to build these central data stores that we think Accenture and Scalable Analytics would be a lot more valuable to that. A big factor in Intel making that choice was Scalable Analytics. They've been working with us on this the last nine months, and I think very excited about what that could do. So we think it's quite substantial for really taking our analytics to the next stage for our business, but we don't have enough data points that I could go and say it's going to give you an MX.

But I think what you can say is we've expanded from being predominantly a company that supports engineering analysis to being more relevant to financial operations but also engineering operations with the new tools and making that data available not just within the organization but the ability to integrate across the organization. So we're seeing interest from IT groups, interest from manufacturing operations and product operations to work with SAP, getting more involved with the financial operations. So it's letting us grow vertically, if you will, within a company from a customer base over time, not just horizontally across the industry in our traditional engineering space. Sorry, I had to earn my speaker's badge.

That's okay, too.

You know, another follow-up on the same subject, but probably the most impressive thing I heard, you know, today was Mike Campbell saying, you know, this is our tool. This is the industry's tool. And, like, yeah, PDF sells it to us, but it's the industry's tool. So there's just a little bit of a disconnect. I feel like you guys are kind of underselling the opportunity here with the 20% number that it's 20% plus the creativity of the industry to leverage this layer that you guys are supplying to do more stuff and for you guys to come up with a way to monetize more on that network. So why am I wrong about that?

Thank you for the question, Jeff. We are honored that customers see us as a tool for our industry. We always, you know, Kim and I have always seen ourselves as stewards of this business, right? And, you know, we were the founders, two of the founders. But, you know, this business is a business that our shareholders own and that our customers depend on and that our employees depend on. And we're stewards to make it more valuable for, first and foremost, our customers because they are the ones that drive everything. You know, we fought really long and hard around the growth rates. I mean, to be candid with you, when Handel first started talking to me about a billion-dollar industry by 2030, I was like, Handel, man, you happen to be around by the industry saying that? You're just putting that number out there. It seemed farcical to me. And now as I've seen it actually evolve, it's like, oh, maybe this actually can really happen. So we didn't want to lean too far in on the growth rates because a lot has to happen, not just from our perspective, but for the industry overall. And we do want to be more important to our customers. We do want to make sure we're adding more value to our customers, but that's like getting the eye to the holder. They have to tell us that by their commitment and what they do with us. That was why Aziz has talked about what they were doing with standardizing and replacing internal systems. To us, it's a great responsibility that we need to take super seriously. We would like to win that across more and more of the customers and be more and more the tool for the industry. We're happy if we can outgrow the number. We're not looking to say that's the ceiling on where we're going.

I mean, long-term, the belief is there needs to be a standard in the industry for cross-collaboration in Spain. We're subscale today. Everyone is. You look at it, and it's sort of like the joke from the Depression. I can't remember if it was Groucho Marx or someone else's. How do you go broke, you know, slowly than all at once? I think the growth in this industry is the same. The growth is going to be slow, and then you're going to start seeing a flywheel effect as it goes. When does that point occur? Hard to determine. We think we're well-positioned, but it's an opportunity. It's not a guarantee for sure.

You've got to appreciate how Kim and Slipped in a joke that John asked at the beginning.

My joke was going to say, well, only 20%. I was going to say, well, it's because Mike is cheap. But Mike's in the room, so I can't use that joke. Hi, thanks. Clark, I would be at Davidson. You said in your prepared remarks, John, that the majority of growth in the Semi's industry is really going to come from that AI component. How does PDF look to increase exposure to some of these key players in the manufacturing of AI-related hardware?

Yeah, that's a good question, Clark. The subtlety is actually I think that the next phase of AI growth is the broadening out phase. So we're seeing this over the last few years, most of the hyperscalers have become customers of PDFs, not just relying on GPUs, but also building out special-purpose systems like the TPUs and other capabilities. Our customers, you know, I think I saw earlier today one of our users from Sentient, Peter Voynkamp, right? And they are building an edge processor for audio that's, you know, when you talk in the Google Alexa devices, it's the one that's processing your, AI is going to start showing up in many. Our NTU customers are all looking at it. And Edge devices are all looking at it. I think one of our customers was talking about their success in AR, VR. There's one of the Google guys, the Qualcomm guys on Snapdragon and AR, VR, and what's going on there. So we expect it to be a much more broader part of the business. Part of our strategy on all of this is we serve the entire industry. We're not here to pick who's going to be successful and how we sell to all of them. Some of them, they realize beyond what their expectations are in their business, and we grow with them, and some don't, and we will participate broadly. But we don't, you know, we do look at things like, okay, what are we doing on advanced memories? This is an area that, you know, Ingeniel talked about. What are we doing on co-backage optics? Each of these things we look and say, what do we need to make sure our capability is good? But then within that category, we just try to sell to everybody, and, you know, whoever wordens that they win, it's going to be on their brilliance. and we're just going to be a participant of it.

Got it. And if we think about unlocking additional budget, can you help kind of describe that process? Because if I think about it in my conversations I have with customers today, some of the in-house solutions that are already existing that companies use to solve some of the analytics problems, where do you see the ability for you to displace some of those and continue to gain share over time?

Yeah. Steve touched on that on his talk, and I think when Kim and I were to talk about our frustrations over the years, we would provide essential primary engineers. We've always sold to engineers in product and test engineering teams. And then we'd have customers, they would hire a chief AI officer, a chief data officer, and they'd start setting up a data lake system, and then they would spend a hundred million dollars between software suppliers and, you know, the system integrators and build a system and it doesn't deal with the edge and all the action in our business is what goes on the edge. So, you know, we felt like we weren't communicating with the CIOs and the IT organizations, the finance organizations, the point that Kimon was making and a big part of the reason like Kimmon was so passionate about the partnership with SAP was it got us to start talking to different parts of the organization. I think a lot of what happened at Intel was the finance organization decided to use SAPience on the connection between manufacturing and their business process. So if that's there, well then why not use it more broadly in manufacturing because they're going to be pulling the data out anyway. It takes out one of the, now I have to to worry about the MES system, right? And Aziz said, John, if I just use your stuff, that goes away, I don't have to support them anymore. It's the same data model. So the broadening out of the platform has helped us get to more touch points in the customer base, inside the customer, which is allowing us to maybe be looked at differently. We think we have a lot to prove to the customers to be trusted in that way. So we're not here to say this is a stamp and repeat. We think there's work to do. But, you know, that broadening out of the touch point from the customer is really important.

John, actually for Adnan, just on the margins, two questions here. So, where do you see the, you know, best opportunities over the next couple years to move that op margin line seven points? That's pretty significant. And how long, you know, is that going to take you? and also just in regards to the DFI, which you're still in some cases selling outright versus leasing, there's a different margin structure with that margin impact. Is there a bottom end on the margins that you are gonna try and protect, I guess, is what I'm thinking about, if you have that volatility in the top line?

Yeah, let's answer those in the sequence. So look, in terms of target margins, it's long-term. We chose to work carefully. Similar to the last time when we did this presentation in 2023. But if you go back and look at, okay, we have two years later and we're almost clicking in, I'm not saying that we're promising anything close to that, but usually when people think about long-term targets, it's three to five years on average. So somewhere in that window, near that window, is where we would like to be in terms of the timeline. In terms of where do you add scale, look, there's naturally some scale efficiency that you would expect in the G&A line. That's one. Second, on the sales and marketing spend, many of you have heard us talk about how there is an an opportunity that we are working to optimize and we see opportunities there. I mean, candidly, we've brought together the extensive sales team, the symmetric sales team, and the SecureWise. And with some of these initiatives that you, some of these discussions that you saw at the presentations from Aziz, you can start to see that there's a need to have one team for our client where you can present a portfolio of solutions rather than three different teams. So it's educating the sales team, educating the apps team, and trying to create efficiency there, that is another opportunity that we see. Thirdly, in the R&D side, I think there's opportunity there for us to provide the dollars that is needed for growth for the opportunities that we're seeing and then still be able to drop to the bottom line. So it's a combined effect of those three and again, over that time.

Yeah, I think what's baked in there, if I could just, I don't know about it, is we anticipate revenue growth. We know we need to scale R&D and we will continue to scale R&D, but we don't think we need to scale G&A and sales and marketing at the rate that we scale revenue or R&D. If you look at the last few years, we've been very much investing in those areas. We felt like when we switched from being a yield ramp company to a platform subscription company, we were very, very light on sales and marketing. So we needed to invest heavily because we really had two sales guys when I was in Iowa where we yielded our business. We were two people at 12 P.K. and K. The rest of it wasn't needed. Well, we needed to change that. That meant a lot of invest. We don't think we need to continue to sustain that investment at the rate that it was growing as faster, in some cases, some years faster than revenue, so we think we can meter down that growth rate substantially and let more of the growth and revenue go to the bottom On the gross margin side, we left the numbers there in part because we don't know a lot on how the probable impact gross margin. We do know when we look at Accenture Cloud Analytics, BI tools waste compute, massively waste compute because they're by and large in their programs, they by and large are in-memory database systems, and so so many cores get wasted. The reason why Saeed is able to show what he's able to show today is because you're using every core. You're using every core maximally. So we know for our compute customers, and part of the disease's excitement when he looked at this was like, wow, you can be a lot more efficient on compute spend. So we do think for our cloud customers, there's leverage on the compute side because you just start using all the cores that we're basically wasting. And also by decoupling the parallel compute from the Cassandra node, it gives you a way to get efficiencies on the storage side too. So there's some leverage there, too, in the way that we thought the product that we think would give us some upside there. But there's all those down headwinds that are out there in the business, too.

I just wanted to talk a little bit deeper on the R&D spend side. I mean, you guys have put in some rails, either by acquisition or by building, that were not easy things to do that took real investment for whoever made that investment. You guys are the company you acquired. Now you're going to have AI at some point helping with coding. Is that rational with what you do? I'm not sure that you guys are vibe coding. It implies that this scaling R&D budget is going to be more towards new products and new capabilities rather than building rails.

That's a great point. I think if you get a chance, go look at the product costing demo that the team is doing. I think it's probably in the room next door. Mike Norris, the guy that did that. Our team started working with a genre of AI techniques on coding. And what they started figuring out was very small teams, a mix of product folks, apps folks, and developers, and actually create virtual team members. So you have an agent that's writing requirements, an agent that's writing out test elements, you effectively build it. You scale out your team with virtual team members that are doing the same functions you do in a regular software development process, but they're virtual. And you've got a human that's working with them in each of those characteristics. And what he's been able to build, we put him in a small team on product costing because we knew we needed that for some of our sapience customers by the middle of 2026 and they built stuff out. They got much further along within a quarter and it was really around that innovation. And yeah, when we, you know, we think we still expect to grow our R&D spend, to grow more than we're growing our G&A and sales and marketing expense, but we think we'll get a significant We can boost in productivity and the way we develop product because of what we're able to do with AI. I wouldn't like arguably by coding, but it's really quite a bit different in the way that they're thinking about it. And the team, we did a lot of innovation, a lot of trial and error on that throughout later 2024 and 2025. And the rate of improvement in the tools and systems that we use is just staggering to the team. What they'll tell me is, John, what I was doing, what I did last week, I couldn't have done three weeks ago or three months ago, but the capability is really improving and it's really changing the way we're doing product development.

I can attest we're spending on those tools.

John, just one question.

So with the subscription model for Accentio, you do plan to give regular updates like Tesla, they will upgrade the FST every year or so. Netflix will give me new movies every week. So that's part of your model and that's included in your development. So customers can expect regular updates from you.

Yeah, and actually that's one of the big differences between what we do on the sale of the eProb and the subscription is the way the software gets smarter too on that as well, what FHIR can do and looking at layouts and what Accenture can do on the other side of it in terms of identifying things. And the big shift on Accenture Cloud was the ability to make it more efficient to push updates. When we moved customers to the cloud, the update got a lot more efficient and we could get them. It's super frustrating when you see customers running in the two-year-old version of the code. You're thinking, wow, I could have made the same money just firing everyone in R&D and running it up for the next two years. You're only going to change at that rate. And really, there is a need for that. That's part of my motivation around AI for manufacturing. If we're going to run lots of factories all around the world, we've got to get smarter, continually smarter. And that means continual updates. And that was a big piece of the reason why we acquired SecureWise, because our equipment vendors want to deliver more value to their customers. And the only way they're going to do that and get a subscription business is to be able to continually provide updates as well. The more value driven to the customer, the more IRC. And they expect, I mean, very early on, one of our first customers was Toshiba, a great friend of mine still to this day, this guy, Kakuma-san, I really love. And Kakuma-san always told me, John, you have to understand, every year I have to make the chip cheaper. You've got to give me more for the same money. If you want more money, it's got to do even more than that. And we understand that. That is part of the nature of the business. You've got to really be delivered. But as I showed earlier, it's an opportunity to reach an environment. You look at the amount of money we waste as an industry.

Do you have plans to expand into Silicon Lifecycle Management and basically you'll have more opportunity to engage with Automotive and healthcare and data centers?

Yeah, so the question about Silicon Lifecycle Management, for those of you that aren't aware, so the idea is, and I think it's really clever, putting agents on the chip, keep track of the data of the chip over the life, have the chip phone home, provide that data, and enable ability to work with that. One of our partners was Proteontex. If you looked on our slide, Proteontex is a leader in that space. We continue to work with them. We believe our capability and enablement is very important for that overall capability. The difficult part is getting the information from the chips in the field back to the chip supplier. We don't know how to solve that for our customers. If you can't solve that piece for the customers, then it's really kind of – the rest of it is hard for us to envision. So partnering with folks like Proteon Techs, we're happy to do this. Siemens also has some really neat capability from the UniSocca company they acquired out of the UK maybe 10 years ago. We've partnered with them as well. We've partnered with Analog Bits over the years. They have some capability as well. Around the analytics, once the data comes back, we are trying to enable that. But the real value piece is how do you get that data home from the chips in the field? and we haven't seen a way to solve that problem. The great thing about SecureWise is the ecosystem of semiconductor manufacturing, it's hundreds, hundreds of thousands of test facilities and OSATs. It's not millions and billions and trillions. So the phone home capability is contained. We could tackle that for our customers in this space. That Silicon Life Cycle Management dream means you've got to tackle that problem for the chip industry.

It's above our pay grade right now. I think the core for PDF and the customer base is being that central point of manufacturing data, that center of truth, and bringing in, if they get field data, as they talked about in the previous session, people running AI models. How do you pack the version of an AI model run on a specific chip back into the database and perhaps the output so two years later you can do analysis if you have a field repair? But the agents themselves on the chip, the phone home capability from the Tesla, et cetera, these aren't areas where I think we're going to be providing the expertise in the industry.

Honestly, it's interesting. I'll actually go.

Yeah, this may be a dumb question. In terms of analytics, are you just enabling your customers to provide their own analytics or are you able to offer some analytic solutions yourself?

And I ask this question because this is a thorny issue of data ownership.

Even though the data is hosted on your platform, you don't necessarily own the data. Only the customer owns the data. So by definition, the customer has to provide the analytics. Do I have that correct?

Both happen. You know, we've analyzed our test vehicle data over the last 30 years. And so we have a fair amount of expertise in analyzing data and building analytics that do different capabilities. and we do make that available to our customers. But you're 100% right, right?

The real details, you know, like there was a whole bunch of, you know, Adam and Testerodyne and us talking about data feed forward. The reality is, you know, in the audience were folks that know 10 times more than us and our equipment suppliers about data feed forward and what they need to do.

Mike kind of touched on that in his talk. And so, you know, a lot of the value gets delivered. Here's a platform. Here are some starter algorithms that you can work with. and you can then build them and you can take them and use them in many different ways. And 90% of the customers take what we provide that's generic and then take it the next quantum leap ahead of that. And that's why Saeed talked about flexibility in the platform being so super important in what we do. We don't look to be the single stop shop and we're going to tell you how to do your analysis, but we are going to provide you a pretty rich toolkit from which you can build stuff.

I mean, simply put, we provide AI models and other simple, more simple algorithms, analytics. Customers either import or build models within our system, and we also support third parties, right? Our belief is, especially in this AI world, no company is going to have, you know, the cornerstone on the best algorithms, the best understanding for every situation. We are the trusted platform we would like to be for that repository of data, but we need to enable the customers to use it and integrate it with other data sources that serve their needs. Can you guys talk about where you are from a supply chain perspective on the ePRO tools and just sort of the balance between supply and demand? And also maybe touch on the DRAM opportunity.

Sure. So we are ramping up our ability to produce. We expect to be able to double what we did last, in 2025 and 2026. Most of what we can produce in the first half, I think all of what we can produce in the first half of this year, we believe we know where they go between revenue generating machines as well as machines that are eval or demo machines. With respect to DRAM, we've been working with a couple of vendors on that. We do expect to be able to ship to at least one of them in the first quarter of this year. That's why one of the machines will be an eval capability machine. And, you know, I think we're pretty mindful of not getting over our skis too far on this. We do want to make sure we have everything that's out there in the field runs in very high utilization rates. We're very mindful about that because then we know that we can absorb more. And when we put one of the customers at one machine, we still got a second machine. The second machine gets a 90-plus percent utilization very quickly. So we know that there is untapped demand. We are then providing under that demand, somewhat constrained by manufacturing and somewhat constrained by making sure we start opening up the aperture of customers and market opportunities. We'll get the back first and then come back. Are we supposed to open up the questions for people on the call?

I'm going to ask another DFI one, kind of a multi-part one. that the way you've talked you talked about it today the direct scan the combination with fire and is that added capabilities new to me I didn't know how new that combination was and just more importantly as you talk about the added throughput that you've achieved what how do we think about what the what the Sam is at this point and and and have we learned much last part on how you're going to sell these machines relative to the one you sold in the fourth quarter. Recently, they've been more the traditional leased model. What do you know today about the mix of how that'll go?

Yeah. So I bought an electric car and then I regretted it instantly because you should just lease electric cars because the rate of improvement and change is so incredibly fast that why would you want to own these things? And I think that's actually going on in E-Beam. And we designed it with the ability to upgrade along the way. And a lot of that's because, you know, the gentleman in the front of the question around the software getting smarter. The integration of the layout software, actually even IP on the chip, the original idea had that. We still work with customers on that. There's a lot of dead space inside chips. You could put interesting structures there. And the analytics to know not just the measurement result but all the fields around the design attributes. That was kind of understood from the beginning.

I always said to the team, if what we're trying to do is be a better capital equipment company in the capital equipment industry, we should just stop it now.

Because we have to think about it from a system perspective and do it very differently for it to be a value. So that holistic view was always there. I don't think we ever – I think the difference is Kim and I presented it before to the investment community, and this time we had Interno presented. So probably that helped a fair amount because I think he could present it thoroughly and better than we did. Subscription versus purchase, as I said to them up front, we try to make it economically slightly advantageous for the customer to subscribe because we think that there's value to them being able to get upgrades and support it that way. And frankly, at our scale, one this quarter, one next quarter, two this quarter, one next quarter, but it's so lumpy, it'd drive our shareholders up the wall, right? So we'd like to make it as smooth as possible. It doesn't mean you get as much money up front, but I think over the long term, I think it's more aligned with how we operate and more aligned with the system view and more aligned to the comment he made about the extension of time-based licenses. The thing should get better over time, much like your Tesla gets better over time. The direct scan application gets better over time. mostly with software, but in some cases with hardware as well. So how will the market respond to it, and will it stay that way or not? I don't know. I think one of the things that we learned when we were super dogmatic about the IYR business model, I don't know that we did ourselves a service by being so orthodox. So we thought to ourselves, like, our customers are always a magnitude bigger than us. We show them multiple models. We let them decide. So far, I think there is definitely parts of the organization that I think finds that hard to digest. But when you sit and think about it rationally and you show the economics, it actually kind of makes a lot of sense, especially in a part of the market where there's a huge rate of change, which I think there just is right now. But I don't know what it'll do forever. But Sam, you know, if you look overall, I think, you know, ASML at the Analyst Day, ASML is one of the best analyst days out there. I really love working in the Analyst Day stuff. They talked about additional wafer starts per year. When we back that out, you know, we think there's somewhere around, you know, $800 million to $1 billion spent on e-beam inspection, you know, per year, roughly around now. That's assuming a certain attach rate per 10,000 wafer starts or wafers and an e-beam inspector. I think that's actually going up and there are more inspectors per wafer start. So if you've seen the flat rate, it's in that range and we think about half of that is voltage contrast based and the other half is fine feature inspection. So that would be, you know, 400 to 500 million is your kind of voltage contrast based inspection. I don't know if that's accurate or not. And then what fraction of that, you know, is a direct scan useful for? I think we're still learning that, you know, inside that $500 million, you know, voltage contrast based inspection ad that you say. And if you flip it to a subscription, how would that look? Because that's looking at the, if you sold it on a capital basis, what would it look Which is what the market does today. You know, I think Oliver Patterson from Intel gave a nice chat, right? I mean, I don't think it's a – a chef wants multiple knives and not a Swiss Army knife, right? If you really want to be a Michelin-starred chef, you have multiple knives. You don't have a Swiss Army knife. I think early on the E-beam tools were Swiss Army knives. I think they're evolving to be, you know, more like a chef's knife. and he talked about multi-beam machines, there's a value and a place for those. What we are doing with DirectScan, we think there's a value and a place for them. I can tell you that when we look, I always tell our teams, when we used to do yield ramps and we still do working with customers, any engineer that tells me the yield loss mechanisms are random, I know that's a bad engineer. There's nothing that's random that goes on in the factory. It's always systematic. You just haven't figured out what to do. There will be a part that fluctuates like the butterfly flapping its wings in Mexico causing a storm in San Francisco. There's always some kind of a stochastic behavior to it, but there's a deterministic element. You need to figure that out. And so the whole idea behind direct scan was there's always a deterministic element to it, and you need to be able to go figure that out. And the power that it unleashes when you understand the connection to layout is very, very valuable. But when we talk to the engineers that use it, what they love – and Oliver hit on it a little bit – is after it finds all the spots of the defects, it goes back and takes an image and it goes back and tells you what the layout is. So you know with one scan on the wafer, this is what failed, this is what its failure rates were versus the other more generic layout patterns and this is what drove those layout patterns. No, by the way, here's a picture in case you don't believe me because it doesn't take a picture to figure out where the failures are. It is just a one pixel measurement. So that packaging up we think is valuable. It's a more system view. But the fraction of that 500 million it would represent much more than what we're calling to now. So that's enough. Any other comments or questions? I think we're getting between people and drinks. So I do, you know, first of all, I want to thank everyone for attending. Also, many of you are shareholders for a number of years, and we do really appreciate your support and your confidence in the business. And some customers are in the audience as well, and we appreciate them as well. You know, as I said earlier, Kim and I see ourselves as stewards of this business. We are stewards of your shares, of our customers' products and tools that they use, and our employees' paychecks, and so we're really honored to have the opportunity to be in these roles as long as we have. We've both graded and lost a lot of our hair, but we continue to try to make it a better business, and we always appreciate the feedback, as And Mike said, I want to take you back as a guest. So thank you.