All right, while we work out the PowerPoint logistics over here, it's really my pleasure this morning to introduce Nicholas Cumins, the CEO of Bentley Systems, for our fireside chat. You know, I think Nicholas is going to explain a little bit more about what Bentley does, but they are a frequent visitor of the Nasdaq London Conference. We're so proud to have them as a partner at Nasdaq and to have them with us here today. So, good morning. Good morning. Good morning, everyone. Good morning. How has your trip been so far? So far, so good. Good, good. Hopefully, only better from here. Y ou've been in the CEO role for about a year and a half now. Yeah. Can you talk about any changes to the strategy or organization that you made and also the role the Bentley family plays today? I can. Maybe a few words about Bentley first. Great. Yeah. So we like to say we are the infrastructure engineering software company. And by that, what we mean is we are a software company and we're dedicated to infrastructure. W hat do we mean by infrastructure? Everything that makes other things possible. So think roads, bridges, tunnels, the electric grid, the water network, and so on and so forth. From a software perspective, we have software for pretty much all the engineering disciplines that are involved in an infrastructure project. W e have software for civil engineers, structural engineers, geotechnical engineers, you name it. We have software for every phase of the infrastructure lifecycle, from design to construction to operations and maintenance. And we cover pretty much all the sectors of infrastructure. T hat's who we are in a nutshell. We were founded more than 40 years ago in 1984, and we went public just five years ago. Ye s, I am the new CEO. I became CEO a year and a half ago, almost. I'm the first non-Bentley CEO. T he company was created by the Bentley family, Bentley brothers. I succeeded Greg Bentley, who is now our Executive Chairman a nd he's sitting on the board together with three of his brothers. I'm on the board as well. So that's roughly Bentley. F rom a strategy standpoint, of course, I had been at Bentley before. I was COO, and before that, I was CPO. So I joined at the time of the IPO. T he strategy we're executing on is a strategy I was already working on together with Greg, the previous CEO. So no change from that standpoint. Of course, however, a much stronger emphasis on AI. And I know we'll discuss it in a moment. I t's more of an evolution, if you want, than a radical change. W hat we've been investing in in the past few years has actually put us in a very strong position for AI going forward. T hat's that. And then from an org standpoint, maybe just a couple of changes as I became CEO. We consolidated all the product teams with our technology organization. I t's all reporting into the CTO a nd that's because we are in a time of great technological change, and we needed to have a very fast feedback loop between product and technology. That's one change. A nother change is we brought all the user-facing teams together. A ccount management, success management, services all together under a Chief Revenue Officer. Same thing to make sure we have a very fast feedback loop across all of these functions at a time of great change. Wow, wow. There's so many great changes. C an you talk a bit about, you just mentioned the Chief Revenue Officer. Can you talk about demand backdrop, global funding, and how you believe it will trend over the coming years? Yeah. So it's never been a better time to be in infrastructure and never been a better time to be in infrastructure engineering and never been a better time to be in infrastructure engineering software. I'll go there step by step. T he biggest demand backdrop here is a lot of investments going into infrastructure around the world to support economic growth, to address climate change, to ensure energy security. Just think about some of the bills in the U.S. in the past few years, but also in Europe. For example, in Europe, to ensure as part of the defense plan that we have strong dual-use infrastructure, infrastructure for both civil and military purposes. So the investments going into energy transition as well. A ll of that is a lot of investments going into infrastructure. There's never been so much investment going into infrastructure. Yet at the same time, there's just not enough engineers. That's why it's a great time to be in infrastructure engineering because you have a lot of work. We're not going to run out of work anytime soon. There's just not enough engineers. Y ou have this widening gap between demand for better, more resilient infrastructure and the engineering resources capacity that is available to do the work. How it translates is backlogs of engineering firms that expand further out, one year or more. You have engineering firms who are turning down jobs because they simply don't have the capacity. T hey're busy, a nd if you talk to CEOs of engineering firms, which obviously I do on a regular basis, they'll tell you that's the biggest challenge. They don't have enough people. I think in Europe, there's this interesting stat which says for the water infrastructure, about 50% of the workforce will retire in the next decade. We're not going to have 50% of the demand dropping for water. Quite the contrary, actually, because we need to be smarter about how we go after the aquifers in Europe. We need to also tap into the water for electric generation, et cetera. T his is not the time to have 50% of the workforce retiring. No w this is the backdrop for us because what do you do when you don't have enough people? You make them more productive and the best way to make them productive is actually software, obviously. W e've always been in the business of making engineers more productive since we started in 1984 by telling them there's a better way to do design than pen and paper. You can use computers to do that, computer design, going from 2D to 3D, 3D to digital twins, and now with AI, those are all interesting inflection points for the productivity of engineers. Yeah, wow. Really interesting stats. I appreciate that. Let's talk a little bit less about specifics of the business and let's talk about results. Y ou've delivered very consistent results over the last number of years and can you talk about the investment thesis and your long-term financial framework? So yes, the business is very resilient. I'll explain first the fundamentals of the business, and then we can talk about our plan going forward. T he fundamentals of the business are indeed very resilient, consistent results that compound basically each year. The makeups of our business, more than 40,000 accounts now with very low revenue concentration. About half of our ARR is coming from engineering firms, and another half is coming from infrastructure owner-operators. That's also something to bear in mind. I t's diversified from that standpoint. I did mention we're serving pretty much all the infrastructure sectors, but about 60% of our ARR, about 60% is in public works utilities and this is a sector which is countercyclical as opposed to others. This is the one which is benefiting the most from these very secular investments going into infrastructure. About 92% of our revenue is recurring. About 94% of our revenue is direct. We have a very high operating leverage. We have a low financial leverage, and we have free cash flow. So going forward, and this is our long-term financial framework we've had since the IPO, and we see no reason to stray from it right now. It's a low double-digit ARR growth. And this is composed of, let's say, mid-single digit from pricing, mid-single digit from upsell and cross-sell, and about 300 basis points from new logos, which we've had actually in the past few years. So that's on ARR growth. We see a margin expansion of, on average, let's say, approximately 100 basis points every year. That's what we've been delivering for the past five years as well a nd we expect going forward. It 's still a robust free cash flow generation. Yeah. Y ou just mentioned new logos. So let's drill into that a little bit more, especially with SMB. SMB has been a great growth driver for you for a number of years a nd so how are you bringing on so many new logos a quarter? And And how much opportunity is still left out there in the market? Yeah. So fair point. Most of the new logos are from SMB. We have some as we continue to grow into asset operations and maintenance, and we go after new owners and operators. T he vast majority is SMB. SMB is interesting for us. About five years ago, at the time of the IPO, we decided to be much more intentional about SMB. We used to be in the space, but more as a byproduct of serving very large engineering firms or very large owner-operators who happened to have smaller firms in their ecosystem to which they were outsourcing work. That's where we were. And they were basically telling them, you must use Bentley software, and they will follow suit. That was our SMB business before the IPO. Around the time of the IPO, we said, let's get much more intentional because we have the technology to do it. Oh, I didn't mention it. One of the reasons why we're not doing so much in SMB is because we do prefer a direct engagement model. Again, 94% of our revenue is direct, right? But clearly now, there are ways of being both direct and scalable. We've invested into our own online commercial platform, our own sales team to do low-touch engagements with inside sales. We're able to really scale our SMB business. For the past five years, it has contributed a lot into our ARR growth. For many years now, about 300 basis points of ARR is coming from new logos, primarily SMB. For 15 consecutive quarters, we've brought more than 600 new logos to the company. Every quarter, more than 600 new logos, all in SMB. And we see no slowdown in the foreseeable future. There's still a lot to capture there in terms of new logos, which is great. The reaction we're getting from SMBs is, it's great that you're coming to us. We'd like to have an alternative for whatever software that we're using before. And the software, by the way, that we offer in SMB is exactly the software that we offer for bigger accounts. There is no change as well. So it's purely a go-to-market investment. Got it. Got it. 600 a quarter. That's very, very impressive. L et's pivot and talk a little bit about data and technology. Asset Analytics is a newer area that you're investing in. Can you help us understand where that business is today in your longer-term strategy? Maybe I back up a little bit from this. So we do have software for design, construction, operations, and maintenance. Operations and maintenance, our ARR in that space is less than 10% of our total ARR. Yet if you really take a step back and you look at whole lifetime cost of infrastructure assets, the vast majority of that is in operations and maintenance. T hat's because, simply put, I mean, the infrastructure assets' longevity is very long. It's decades, basically. So there's a lot of investments going there. W e've identified a number of inefficiencies where software can help as well. W e've been in that space for many years, if not decades, actually, but focus on asset information management, which is how do we help owners and operators maintain information about their assets. T his is a services-heavy business. By the way, we did invest also our system integration arm here called Cohesive in order to help do this. It's a lot of integration with the ERPs of this world, the EAMs of this world. Think IBM Maximo or SAP ERP EAM or Infor EAM, et cetera. There's a lot system integration, which is good, and it's important that we do that. We've identified another opportunity which was much more akin to a true software business. That is what we call Asset Analytics and you were referring to. What is this? This is actually helping owner and operators and the people who serve them understand the exact physical conditions of an infrastructure asset in its full context. It's leveraging AI, computer vision to detect features. What's going on with that asset? Is there a crack? Is there spalling? Is there vegetation growing on a transmission tower, God forbid, or else, and then it's leveraging our pretty vast portfolio of engineering applications to understand what all of these features mean from an engineering standpoint, so we detect that there has been more equipment installed on a tower. We can run simulation analysis to understand if the structural integrity of that tower is potentially endangered, and we can trigger remediation work. W e're quite excited about this. It's a big investment area for us from a product standpoint, and it's a big focus area for us from an acquisition standpoint. That's where we want to look for assets. We are pretty much creating a new market here together with many, many startups. There are not really big established players doing this that we can go and acquire, so this is a market to be created and for us to lead. You mentioned briefly, you touched on the topic that we will have to talk about all day because it's so important, but AI. T here's quite a debate regarding AI and the impact on software companies. And how is Bentley positioned, and how can it be a winner in the AI space? AI is playing a role at many levels when it comes to infrastructure and infrastructure value chain. Where we have been historically with AI is in operations and maintenance, leveraging, as I said, computer vision to understand what's going on with the assets. I will say this is relatively straightforward and relatively established, even though it's a market that we're creating, but the efficacy has been proven, et cetera. There is a big opportunity for AI in design now. The infrastructure community overall is looking into AI as clearly a great way of solving for that widening engineering resources capacity gap on how we can make engineers more effective, more efficient, and more effective. Here we play at different levels as well. One is we are delivering our own AI capabilities to the benefit of the engineering services firms, the owners, and operators when it comes to design. Some of that is next-generation applications that are developed from scratch to be truly AI native. We launched one for site engineering. We announced another one coming for the design of substation. I t's quite exciting. But the majority of our users are not using these next-generation applications, of course, because we're launching them. They're using traditional applications. And so we're bringing AI capabilities now to users of these traditional applications. W e're going after the biggest time sinks we can see in the design phase. A t this point, it's not about generating design per se. It's from the design in which infrastructures spend their time or should spend their time, actually, or the majority of their time, generating drawings. We're in this interesting space where when it comes to design infrastructure, it's quite sophisticated, leveraging software to do 2D or 3D designs, leveraging digital twins to combine designs together, et cetera. T hen everything gets dumbed down as we get ready for construction because we have to produce 2D sheets. We have to print them to give to the construction firms so that they can carry on the construction work. It's an interesting space. So everything gets dumbed down. This, just the fact that you move from 2D, 3D design to drawings is a huge time sink for engineers. It's easily 40%, 50% of their time just creating these drawings, manually annotating them. That is really the worst use of their time, right? T hink about the potential efficiency gains if all of this could be automated. This is the kind of capabilities that we're bringing to traditional applications to do that. No w here's another interesting fact for all of you because you may have seen from many, many years ago a stack rank of all the sectors and how digitally advanced they are. And you will see engineering and construction pretty much at the bottom, right above agriculture, which is the absolute bottom, right? Now, we've been amazed in the past few months of how much engineering firms are actually leaning on their own AI investments. Not all of them, typically the larger firms, the ones who can actually afford that, not the broader engineering community out there. But we've been very impressed. So they're truly leaning in. Why? Because they want to solve for that productivity issue. T he way we help them here is, one, help them tap into all of their past project data. So they could leverage this to educate their own AI agents so they don't have to start a new design completely from scratch. They can reuse past design from past projects. W e can do that simply because the number one solution that is being used out there for public works utilities when it comes to infrastructure data is our solution, our Bentley Infrastructure Cloud. W henever you put a file into Bentley Infrastructure Cloud, we actually map that data into schema so it can be used by AI. It's made AI ready. So that's how we help in the first place. Then second is, as they create their own AI agents, what they're looking into, and it's very, very early right now, but what they're looking into is AI starting to generate some design recommendations, and they're tapping into our engineering applications to give feedback to their AI the same way that their engineers have been using our engineering applications for decades now to be able to run simulation analysis and make sure that those recommendations that are coming from their AI agents are engineering sound, and maybe I'll leave it there, which is, this is still very early. It's very early, and it's going to take a while because obviously, the space in which we operate, critical infrastructure, decisions that are being made there from a design standpoint have real consequences in the real world. Therefore, great care has to be taken when it comes to those decisions and the recommendations that are leading to those decisions. We need to make sure AI is really trustworthy. That is actually what's going to dictate the pace of AI adoption for infrastructure. I want to open it up in a few seconds for questions. But before we do that, let's look at the other side of AI and the opportunities for your business on the large-scale data, the data center buildout. Can you talk to us quickly about that? And then we'll open it up for some questions. Huge data center buildout. As you all know, interesting to think of a data center as like a mini city. You see data centers that have truly the size of maybe Central Park in New York or a big chunk of it. I think the Hyperion data center that Facebook or Meta is working on is going to be even larger than Central Park of New York. What it means is there's a lot of infrastructure in those data centers. You need roads to circulate around it. You have the buildings themselves. You need to be able to produce sometimes your own electricity so you don't tap into other sources. At the very least, there needs to be an electric grid in order to transmit and distribute the electricity all the way to the data centers. You need to be able to tap into water to cool down you, and so on and so forth. W e have tons of opportunities because there's so much infrastructure, tons of opportunities for our software to be used. I t is used in the design and the buildout of data centers. I think our own construction modeling software is like the de facto standard now when it comes to modeling the construction of data centers. So usually exciting. And there's so much demand that is put on the electric grid because of data centers that it further accelerates the need for the expansion of the electric grid. So this goes way beyond the data centers now. We see that as a major driver to improve the electric grid, to expand the electric grid, to also push for permitting reform in the U.S., in Europe, and elsewhere so that we expand that electric grid as fast as possible. So all of that is turning into great tailwind for us. Yeah. Larger than Central Park. That's incredible. Are there any questions from the audience? One in the back. Go ahead. Hi. Thanks for that. On the Asset Analytics piece, I understand you're going to look at where there's a crack in the bridge or a hole in the road and help people solve that. What are the firms doing now? W hat I'm getting at, is this a TCO saving for them, or is it just nice for them to know that their bridge has got a crack in it or whatever? It's a great question. So when it comes to public infrastructure, it's actually a requirement that you inspect the infrastructure asset on a regular basis a nd you need to generate reports with very specific format in the U.S. at the federal level, then at the state level. You need to inspect a number of times per year sometimes an asset a nd you need to generate these reports. The way it's done right now is all manual. You send crews. So for a bridge, you'll have literally people hanging over ropes with pen and paper and trying to understand what's going on. There's a better way of doing this, which is, what about flying a drone? And for a road, you can also send crews. But there's a better way of doing this, which is capturing LiDAR data and then processing that data and then being able to detect what's going on with those assets. T hat's what we're talking about. Now, this data acquisition piece is still a service in a sense, but already more efficient potentially than, again, sending people and less dangerous than having people hanging over ropes. Where we come in is once the data is being acquired, from then on, everything is automated. W e have the data. We process the data. We understand what the data means. We detect what it is. Then we understand the so what from an engineering standpoint. We generate the reports a nd then we trigger potential remediation work. Any other questions? Go ahead. Can you talk about your M&A strategy? Has it shifted recently more towards AI and less towards the programmatic acquisitions you used to do? Great question because we used to do a lot of acquisitions. We've done more than 120 acquisitions. More than a couple. W e did call it programmatic because we were doing them on such a regular basis. Now, we decided to focus our acquisition. It's not exclusive, but I said the main focus of our acquisition investigation is around Asset Analytics, looking into companies that are like startups that are already breaking ground there. Because it does take time to train the AI model on specific asset classes and then specific features that need to be detected, et cetera. So we're quite active there a nd that's why you should expect us to do acquisitions. But it's not exclusive. So we'll continue to see if there are some white spaces we need to fill in with our core engineering applications. We'll do so, for example. T he main focus is on Asset Analytics. Now, because it's a new market and we're talking about startups, we're quite rigorous about the kind of assets we will be looking into acquiring. T hat's why you don't see them coming up so often. Do you mind if they're unprofitable or profitable? No. The most important for us is the technology indeed, and they're small, so they will not be profitable, but will absorb the dilution impact in our margin expansion. Great. Well, Nicholas, this has been a fantastic chat. We have two more minutes. So before we let you leave the stage, we'd just love to hear your outlook for 2026 and what investors should be thinking about in terms of the environment that you're planning for and your ability in 2026 to achieve your long-term goals. So if you could leave us with that. I'll go back to my very first comments. There's never been a better time to be in infrastructure, infrastructure engineering, infrastructure engineering software. As we commented in our last earnings call, the demand environment remains very strong. We don't see any change to that demand environment going into 2026. W e see no reason to deviate from our long-term financial framework of low double-digit ARR growth, margin expansion of approximately 100 basis points, robust free cash flow generation. Perfect. Well, thank you, everyone, very much. Thank you so much, Nicholas. Thank you.