Bentley Systems, Incorporated (BSY) Earnings Call Transcript & Summary

It's really my pleasure this morning to introduce Nicholas Cumins, the CEO of Bentley Systems for our fireside chat. I think Nicholas is going to explain a little bit more about what Bentley does, that they are a frequent visitor of the Nasdaq London Conference. We're so proud to have him as a partner at Nasdaq and to have them with us here today. So good morning.

Good morning. Good morning, everyone.

How has your trip been so far?

So far, so good.

Good. Good. Hopefully, only better from here. So you've been in the CEO role for about 1.5 years now. 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. 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 and what do we mean by infrastructure, everything that makes other things possible. So think roads, bridges, tunnels, 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 infrastructure projects. So we have software for civil engineers, structural engineers, geotechnical engineers, you name it. We have software for every phase of the infrastructure life cycle for design to construction, to operations and maintenance, and we cover pretty much all the sectors of infrastructure. So that's who we are in a nutshell. We were founded more than 40 years ago in 1984 and we went public just 5 years ago. So yes, I am the new CEO. I became CEO 1.5 years ago almost. And I'm the first non-Bentley CEO. So the company was created by the Bentley family, Bentley brothers. And I succeeded Greg Bentley, who is now our Executive Chairman, he's sitting on the Board together with 3 of his brothers, and I'm on the Board as well. So that's roughly Bentley. So from 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. So the strategy we're executing on 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. So this -- it's more of an evolution, if you want, than any radical change. And what we've been investing in, in the past few years has actually put us in a very strong position for AI going forward. So that'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. So it's all reporting into the CTO. And 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. And then another change is we brought all the user-facing teams together. So account management, success management, services all together under our 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, some of the great changes. So can 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?

Yes. 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. So I'll go there step by step. So from the 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. And 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 defense plan that we have strong dual-use infrastructure for both civil and military purposes. So the investments going into energy transition as well. So all of that is a lot of investments going into infrastructure. There's never been so much investments 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. So you have this widening gap between demand for better, more resilient infrastructure and the engineering resources capacity that is available to do the work. And how it translates is backlogs of engineering firms that extend further out 1 year or more. You have engineering firms who are turning down jobs because they simply don't have the capacity. So they're busy. And 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 an interesting stat, which says for the water infrastructure, about 50% of the workforce will retire in the next decade. We're now 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. So this is not the time to have 50% of the workforce retiring. So now this is the backlog 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. And we'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 a 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.

Yes. 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. So you 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. And maybe I'll explain first like the fundamentals of the business and then we can talk about our plan going forward. So the fundamentals of business are indeed very resilient, consistent results that compound basically each year. The makeup 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. So it'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 work 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 a robust 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 AR 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 5 years as well, and we expect going forward. And it's still a very robust free cash flow generation.

Yes. And you just mentioned new logos. So let's drill into that a little bit more, especially with SMB. So SMB has been a great growth driver for you for a number of years. And so how are you bringing on so many new logos a quarter and how much opportunity is still left out there in the market?

Yes. So fair point. Most of the new logos are from SMB. We have some, as we go -- continue to grow into asset operation and maintenance and we go after new owners and operators. But the vast majority is SMB. So SMB is interesting for us. About 5 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, a very large owner operators who happen to have smaller firms in their ecosystem to which they were outsourcing more. That's why 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. And around the time of the IPO, we said let's get much more intentional because we have the technology to do it. 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 is ways of being both direct and scalable. And we've invested into our own commercial -- online commercial platform, our own sales team to do low-touch engagements with inside sales, and we're able to really scale our SMB business. So for the past 5 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. And for 15 consecutive quarters, we brought more than 600 new logos to the company every quarter, more than 600 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 like to have an alternative for whatever software they were 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. So let'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 and your longer-term strategy?

So maybe I'll back up a little bit from this. So the -- we do have software for design, construction, operations and maintenance, operations and maintenance, or 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. And that'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. And we've identified a number of inefficiencies where software can help as well. So we'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. And this is a services heavy business. And by the way, we did invest also our own 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 will, think IBM Maximo or SAP, ERPAM or Inforem, et cetera. There's a lot of system integration, which is good and it's important that we do that. But we've identified another opportunity, which was much more akin to a true software business, and that is what we call asset analytics and you were referring to. And 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 spooling? Is there vegetation growing on a transmission tower, God forbids or [ OLCM ]. 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 the tower. We can run simulation analysis to understand if the structural integrity of that tower is potentially endangered then we can trigger remediation work. So we'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 start-ups. They're not really big established players doing this, that we can go and then settle. So this is a market to be created and for us to lead.

And you mentioned briefly, you touched on the topic that we both have to talk about all day because it's so important, but AI. So there'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?

So AI is playing a role at many levels when it comes to infrastructure and infrastructure value chain. So where we have been historically with AI is in operations and maintenance, levering, as I said, computer vision to understand what's going on with the assets. And 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. And 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. And so here, we play at different levels as well. So one is we are delivering our own AI capabilities to the benefits 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 and it's quite exciting. But the majority of our users are not using this 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. And we're going after the biggest time syncs we can see in the design phase. And at this point, it's not about generating design per se. It's from the design in which infrastructure 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, you're leveraging software 2D or 3D designs, leveraging digital twins to combine designs together, et cetera. And then 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 sync 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? So think 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. So now 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'll 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. And the way we help them here is, one, tap -- 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. And we can do that simply because the #1 solution that is being used out there for public works utilities when it comes to infrastructure data is our solution, our Bentley Infrastructure Cloud. And whenever you put a file into Bentley Infrastructure Cloud, we actually map that data into schemas, 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, 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 is coming from their AI agents is 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 and therefore, great care has to be taken when it comes to those decisions and the recommendations that is leading to those decisions. We need to make sure AI is really trustworthy. And that is actually what's going to dictate the pace of AI adoption for infrastructure.

So 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 build out. You can 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 and you see data centers that have truly the size of a mini Central Park in New York or big chunk of the [ Helsinki ] Hyperion data center that Facebook or Meta is working on, is going to be even larger than Central Park of New York. And 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 have -- you need to be able to produce sometimes you own electricity, so you don't tap into other sources. At the very least, there needs to be electric grid in order to transmit and then distribute the electricity all the way to the data centers. You need to be able to tap into water to cool down and so on and so forth. So we have tons of opportunities because there's so much infrastructure, tons of opportunities to -- for our software to be used and it is used in the design and the build-out of data centers. And 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 hugely 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 go -- we expand that electric grid as fast as possible. So all of that is turning into a great tailwind for us.

Yes. Larger than Central Park. That's incredible. Are there any questions from the audience?

On the asset analytics piece, I understand so you're going to look at where there's a crack in the bridge or hole in the road and help people solve that. What are the firms doing now? Because what I'm getting at, is this a TCO saving for them? Or is it just nice for them to know that bridge has got to crack in 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. And 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, and you need to generate these reports. The way it's done right now is all manual, yes, you send crews. So for a bridge, you have literally people hanging over ropes with pen and paper in trying to understand what's going on. There's a better way of doing this, which is what about flying a drone. And now for 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. So that's what we're talking about. Now this data acquisition piece is still a services 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, right? So we 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 and then we trigger potential remediation work.

Any other questions?

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 double.

And we did call it programmatic because we're doing them on a such regular basis. Now we decided to focus our acquisition. It's not exclusive, but I'd say the main focus of our acquisition investigation is around asset analytics, looking into companies that are like start-ups that are already breaking ground there because it does take time to train the AI model on specific asset classes and specific features that need to be detected, et cetera. So we're quite active there. And that's why you should expect us to do acquisitions. But it's not exclusive, right? 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. But the main focus is on asset analytics. Now because it's a new market, and we're talking about start-ups, we're quite rigorous about the kind of assets we will be looking to acquiring, and that's why you don't see them coming up so often.

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No. The most important for us is the technology indeed, yes. 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 2 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 '26 to achieve your long-term goals. So if you could leave us with that.

Great. Yes. I'll go back to my very first comments. It's -- 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. So we see no reason to deviate from our long-term financial framework of low double-digit ARR growth, margin expansion of approximately 100 basis points and robust free cash flow generation.

Perfect. Well, thank you, everyone, very much. Thank you so much, Nicholas.

Thank you.