Altus Group Limited (AIF.TO) Earnings Call Transcript & Summary

Ladies and gentlemen, please welcome Altus Group Chief Communications Officer, Camilla Bartosiewicz.

Thank you. And that was a really great pronunciation of my last name. Good morning, everyone. Thank you so much for joining us, both in person and online. It's so great to see a packed room. And I think we have doubled numbers online as well. It's also great to see a lot of familiar faces. We're so appreciative of your continued interest in the company and your ongoing support. For those of you who have followed us over the years, you know we've been a company in transformation. We've been building, changing and we're not done. We're going to continue to do that. But today is really about turning the page onto a new chapter. And our team built for performance sort of speaks to that. It speaks to the operating foundation we've forged to improve our operating and financial results. It also speaks to our client mission, which is to power their performance. So today's sessions have really been structured under 2 core sections. So first, we'll start off with Mike, who will take us through -- today's announcements as well as the strategic focus. We'll do a client customer fireside chat, and we'll have the team come and actually do a show and tell on the product roadmap. And we'll be then breaking for about 20 minutes at 9:50, and we'll come back with the financial overview section where we'll be discussing our new financial metrics and our capital allocation disclosures. And then to be followed by a 40-minute Q&A session. So if you could just please wait to ask your questions then. We'll take them both from the room as well as online. And then we'll have Mike back on for some closing remarks. I'm joined today by my fellow presenters with really great representation across the business. You guys always remind me, it's about the people, and I couldn't be more proud to share the stage with many of my colleagues. And I think, yes, before I officially kick it off, I do need to remind you that today's presentation will include some forward-looking statements and that -- those forward-looking statements are based on certain assumptions that are subject to risks and uncertainties that could cause actual results to differ materially from those projected. I would also like to remind you that we use certain non-GAAP, non-IFRS measures, and we have a lot of those detailed in our appendix as well as on this disclaimer slide, which I would just ask you to read at your leisure, instead of reading it out. And then I would also just like to point out that today's growth rates and whatnot will be presented on a constant currency basis, and we'll be talking in Canadian dollar currency. So with that, I'll now turn it over to our incoming CEO and Executive Chair, Mike Gordon, to officially kick off our 2025 Investor Day.

Thank you. Doing great. Well, first off, I guess I should say it's good to be back and good to see a lot of friendly faces who have lots of questions. And the good news about Camilla and the communications other than that last slide we showed, which shows you that we are a technology company because you can't read it, is the fact that she got everything out at 7:00 a.m. this morning has made my job a lot easier. So we put a number of announcements out this morning. And just excited to be here. It's a lot to be doing this work over the last 2 weeks. I got to talk to a lot of you guys -- you had a lot of questions, obviously. And I said, just give us a couple of weeks, and everybody said, "Well, what can you get done in a couple of weeks? Well, this team can move mountains in a couple of weeks. And when we get ourselves focused on what we'll be showing you today, we feel really good about where we're going. You're not going to hear anything about the market. I may regret saying this, I care about the market, but we don't -- we're not defined by the market. As a software data and analytics company that has some of the best advisers in the business, we make our own way. And while there have been headwinds in the market, and that has happened over the last couple of years, we don't define ourselves by that. And you shouldn't define us by that either. I've talked about pace. Hopefully, you're going to see pace. We're accelerating that pace and making sure that we get that through. One of the things you're going to start to see from us today is that we're going to simplify things. The business -- I love our business, and I love all parts of our business. But there is a point where we have to start simplifying who we are, what we are and what we do. And so we're going to be going through that. You're going to see new transparency from us. With transparency, I had a talk earlier, the truth set you free., The point being, as you should see what all parts of our business are. We love all of the parts of the business that are going to be focused on how this works together with our software and our expertise. There's going to be new focus. We need to focus on what we're doing. It's not that we can't operate, but we have had distractions and impediments that have led us to not focus as much as what we need to do. And if we focus on the value that we drive to our customers, this team can do anything. And then we're going to measure that and then we're going to operate that way. And there are going to be sometimes, there are going to be good moments, and there are going to be bad moments. Hopefully, more good than bad, but the fact of the matter is when we do operate and we talk about these things and it becomes part of our culture and it becomes ingrained then it is just continuing all the way down the road. And this is what some of the greatest software companies do. If you just sit back and you keep measuring and you keep measuring and then you talk to the customer about the value you're driving them. And if we do that, this team will be extremely strong. So let me just get to what we talked about earlier today. I was told that it would take a moment to put this up there. So it's up there, so we're good. First off, you're going to see our roadmaps today. And you're going to see actually some customers talking about what we're doing for them. So what we are explaining today is real. This is not any kind of MVP stuff. This is not any of this stuff. This is stuff that we have out in the market that we're talking to customers about and why we feel so confident about the organic assets we have. Do we need anything else? We're good right now. I'll come back to that in a second. So you're going to get a good sense on this. We're also going to get focused on who we are. So we put out a note today that we're divesting appraisals and development advisory. These are good people who deserve a home where they're going to get focused on. And so they can get focused on their places, we can get focused on ours. I would say one thing right already, just to give you -- to continue on the pace. We already have a signed LOI for our Appraisal Unit. There's -- Terrie would kill me if I didn't say there's no guarantee that it will close. It will close. That's what I think. Difference between a CLO and a CEO is that I always think I have to look at that and she looks for all the reasons why something doesn't happen. I've been practicing that all evening. But it will close, and we will -- we have an exclusive over the next 45 days to get this done. We need to act on this. They were a great part of our business for a long period of time. It's time to move and it's time to like really focus on where our future is. We will be doing work with the development advisory teams, and we'll find them new homes. It's a little bit longer, but hopefully within the first half of next year because we've already started some discussions. Operating expenses. If anybody likes the corporate line, you can talk to me offline and why we shouldn't keep it, but we're going to get rid of that. Now how fast we get rid of that is a question because we've got everything, and Pawan has been working on this over the last year or so. So there's a lot of work that he's done, but we need to get rid of that. When I talk about ourselves, becoming a Rule of 40 company, a couple of lines down. It is as a company, it is not as an operating unit. There is no point to what we've talked about in the past. In the past, we were probably the smallest holding company that there was for all these collection of assets. We're not that anymore. So from that standpoint, we're going to be focusing on our operating expenses, and we're going to get there quickly. So by 2027, when I say we're a Rule of 40 company, we are a Rule of 40 company, all right? Now how you're going to ask me how fast is our growth? We're going to get our growth up. I -- those of you who know me, know I like double-digit growth. There are parts of us that are growing double digits and there are parts that are not. We will figure out every unit that we have either is going to get us very good profitability, over 35% EBITDA. And I want that growth to be as close to 10%. So maybe I just said Rule of 45 company, but I'm going to hold it down at Rule of 40 right now. Pavan is going to go through a lot of the metrics we're using. I know it's an alphabet soup, but you know them all. ARR, gross retention, net retention -- there's going to be more -- I don't want to take that away from him, but these are things that we have to measure. And we feel pretty good about those things. And they're all in your handout as it is, so you guys can go ahead and look forward on that. Finally -- or the final 2 points, we are going to do a stock buyback of about $0.5 billion. For the last year, since we exited tax, we've been sitting on a bunch of cash. There's no point for us to be a bank for you guys as investors. All right? So we are -- we've looked through this next week. We're going to kick off our SIB and we've looked at the price, you should expect something in the $50 to $57 range that we'll be doing some of this stuff out. So that's coming out there. The Board's voted on it. They're very excited about that. It doesn't mean -- so people have asked me, are you getting rid of acquisitions. It's just not -- it's not like what we're looking at right now. And the reason why going back to what I said when I opened on this, we have what we need. We feel good about what we have. Our products, our solutions, we think, are second to none. And then finally, last point is that we will pursue a U.S. stock listing in 2027. Some of you will say, why aren't you doing it in 2026? Well, we want the organization to be in the right state when we go do that. And what I mean by that is we're simplifying it, okay? There are things that are core, there are things that are non-core. The non-core things we're going to get out in 2026. There's no point in trying to move that over to try to explain ourselves in another market when we don't have our stuff where we need it to be, but 2027, it's going to happen. We've been talking about this for too dam long. So this is where -- these are the announcements that we have today. This is what we're excited about is -- we're excited about as a Board. So from that point of view, that's where we'll stick. Now -- I now have to get you set up for what we're talking about next, which is really our product set. And -- when we talk about things, you've heard us talk about intelligence and what we're trying to do with that. We have the greatest software that does all the valuations that everybody uses that we want everybody putting their assets on. Our asset-based pricing is starting to get there. I had a discussion with one of our customers who use seat-based pricing up to a couple of days ago. And basically, they couldn't understand, wait a second, I can put my -- all my assets on this and you're not going to charge me for this in a weird way. And the answer is get your assets on. That's where your number is based off the price point. If you go above that, we grow with you. And they're like, well, that seems kind of refreshing. That's what we do with software companies. Now do I want to make more money? Do I want to raise prices? Sure. Sorry for those guys out there listening it. But I want to win with my customers. Our team wants to win with our customers. And so when you look at this, you're bringing ARGUS together, and then we have the greatest set of advisers in this space. Rick Kalvoda has built a team that is the trusted adviser to everybody. Anybody using our folks, they tell me all the time that these guys walk on water. Rick is not going to do that for you today. But the point being is they're using our software. They're seeing the value from it. They're using the AI and the analytics that we're building, all right? We want to make sure that we get that all out there, but their advice is going to be huge. I sat back and talked to our teams about who are you talking to and some of them are like, they're advising the C-levels at some of these places and the funds are doing really well. We need to like get that with our software working together. And so this is where we get very simply to ARGUS Intelligence. It is basically what we look at is the platform for performance. All right. Everybody should be using this. It should be ubiquitous, and that's what we want to make it in the market. People would think back that is an ARGUS Enterprise, ubiquitous. It is and it's been on the cloud and now we need to leverage what we're doing on the cloud. We need to leverage all the information we can give to people. We need to give them the insights that they need about their assets. As far as I'm concerned, when I say that I don't really care about the market, it's weird for a CEO or Chair to say that, we should be doing well when the market's up, when the market is embroiled when the markets all over the place. The reason being is we're trying to give our customers the best set of information so that they can make the best decisions on the assets that they have. And they have to make decisions no matter what the market is. Yes, if the market's down, will they actually do things a little less often? Probably. But if we give them the information that they need, we can help them through those times in a faster manner. And that's what we're trying to do with that and that's what you'll hear with some of the discussions that are going to be coming up from some of them and how they're using our tools today. So I'm very excited about that. So strategically, it's very simple from a manner of what we look at. We've automated the workflows, makes life a lot easier when you automate the workflows. We'll talk again about -- everybody talks about analytics and AI, it's real. It's in there. I always think about AI and everybody talks about a genetic AI. Genetic AI is great. Don't get me wrong. It is great. You can save a lot of efficiencies with that and make that happen. But it's the -- also the decisioning part of AI and analytics that's so important. That gives you the effectiveness. Those two things working in coordination is what we think is our secret sauce that will actually connect data on our platform and be able to have people use that data more holistically and being able to make a better set of decisions. By doing this, we continue to make our model smarter. We continue to make our customers smarter, they get more value from things. We keep adding properties on. We feel pretty good about where we stand and what we can deliver as part of our vision around this. So finally, as I get -- as these guys try to get me out of here because I know there's somebody here that I like really a lot that they will give me this when I've gone too long. If you remember anything from where I open up today, I look at -- I always talk about the legs of the stool. You have one, it's really not a really good stool. You have a couple, yes, can lean against the wall. You have 3 even better, but I watch my kids knock that over, and in 4, you're doing really well. Software, data analytics. I'll have to use a term AI, even though, I'm an old analytics guy, unsurpassed expertise. Those 4 things together is what we bring to our customers. When we bring that to our customers, I feel like we can drive a ton of value. My team, and you guys heard me on the call, say, we're talking about quantitative value proposition. We are going to start doing that in '26 to like say how much we're saving our customers and why we're so good at what we do. This team is excellent what we do. My job is very simple as a Chair and a CEO. I just have to get all the crap out of their way, and this team can do a great job. So as far as I told the team when I got my town hall in New York City, it was very simple. My job is to take the impediments out of the way. So if you see anything that I'm going to do, that's how I think you should value me is at the end of the day, I have to make it easy for them to do their job. So with that, with not being an impediment, I'm going to invite Rich Sarkis and his friends up here to talk about how our customers are using the software and how they're using things. Thanks for having me back.

Thank you, Mike, and thank you all of the folks for being here. Let me also start by thanking Joe and Chris. Chris has come from all the way in Australia. So over a day to get here -- so it really means a lot. Joe came from Boston, not as far, but we also want to thank him. Before we get going with our discussion, I thought it might be good for you guys to introduce yourselves to get a little bit of context about what they're about to hear.

Absolutely. Thanks, Rich. My name is Joe Crescio. I've been in the commercial real estate valuation industry, my entire career. I came from the principal side, then was at E&Y on the real estate advisory side for a bit. I'm licensed in a bunch of states, MAI Valuation background, keep things interesting for sure. And then recently, I've joined Manulife. Manulife is going through a bit of a transition going from within the real estate area, traditionally insurance company to more of an investment management focus, super focused on taking on more risk across the different parts of the capital stack, driving data analytics and really differentiating ourselves as we look to grow more of our third-party investment management business. I've really ship with Altus -- when I was hired from EY, my task was building out a best-in-class valuation function Historically, we didn't -- we had a mediocre one, I would say, it worked. And there were 2 legs of that. There is not just getting credible valuations for the NAV for consistency, et cetera, but also to do more with the data, in terms of forward-looking insights, which historically, as an industry, we haven't really done the best.

Thanks, Rich, and thanks for having me. I actually started my career for the first 10 years just doing a lot of financial modeling. I taught post graduate students in financial modeling and spent a lot of time doing derivatives, property-backed listed securities, and I worked for an entrepreneurial company for those 10 years where there was really -- anything goes. So I was that guy that built all the models and prepared all the public offer documents. Just prior to the GFC, I then moved into sort of direct property where I was a responsible for asset management, third-party capitals and capital transactions. And for the last 10 years, I've been the Managing Director for CBRE Investment Management in Australia and New Zealand. In that role, we provide full funds management service to our clients, our global clients investing into Australia. We do everything from acquisition through to disposal of all asset management, debt arrangement, trust management. So that's quite a good role.

So Chris, staying with you, you're at CBRE, as you mentioned, firstly, CBRE has a global enterprise by agreement with us. They use all of our software, the VMS users as well. But your journey into the ARGUS Intelligence family. So to speak, is a bit of a different one that came by the acquisition of a company we made a few years ago, Forbury, provide the Excel and basement to ARGUS -- can you speak a little bit about how that came to be?

Yes, absolutely. So with my background of financial modeling, the issue that we have when investing in property securities is it's generally got to generate 10 years of monthly cash flows. And to do that within the Excel environment, it's very difficult. It makes really large models. So what we do in the past is used, say, ARGUS Enterprise or another similar program run the cash flows in there, bring them into Excel, then wrap around the debt fees, trust expenses and so on for us to get the equity returns providing the numbers for our clients. When I saw the Forbury product, it was a game changer, a quantum leap for us. So being able to then just use the Excel environment to do all of those cash flows and forecasting and build around that within the native environment, it was a quantum leap for us. So I've managed to cut our underwriting and reporting from -- it used to take us weeks quite honestly, down to about an hour. So we can very quickly get to the source and get those numbers quickly to our clients.

And we like to say, we meet our customers where they are [indiscernible] familiar in uses with Excel. And I think one of those things that this brings that sort of eliminates the barrier adoption.

Absolutely, yes. There's -- and with the -- with all due respect to ARGUS Enterprise, it's not a very well-used product in the Australian market and APAC in particular, but Excel is everywhere. Everyone is familiar with it, very low barrier to entry. A great example is, I had an analyst from Singapore come down to seconded to my office. I had a really important market rent review for a major tenant. I asked him to do some analysis on what my bookends were. So it was a 10-year deal with a market rent review in year 5. In year 5, my 2 options were hit them with the market rent review and assume that they're going to vacate and lease or I cut a deal with them, lower market rent and we get a 10-year lease. So I asked him to do what those bookings were. You have no idea. And after 30 minutes of showing him in the XL interface, he was able to turn that around in a day and come back with the correct results. So I think that's really shows the power of that Excel interface, the familiarity of someone that can do the modeling. But yes, to be able to use it that quickly and that accurately was really powerful.

Yes. Just to build up that a little bit more. That's always been the criticism of the ARGUS Software. It's like it's not. If you can download things out of ARGUS Excel, but the ability to build customers from actually push that and run the calculations, have that be seamlessly and connected. That's a pain point. I think there's unlocking that is going to create a lot of immediate steps to drive more efficient reporting, aggregation of data, et cetera. We didn't now, but it's just a little bit inefficient.

Great. And I think that's a great segue for like talk about the convergence onto ARGUS Intelligence that includes ARGUS Enterprise that includes Forbury Excel Interface. Team about the demo, ARGUS Intelligence for all the viewer online. And I know you've been very familiar with it and over the last sort of 12 to 18 months. Can you explain the value of measuring performance, both for portfolio manager and benchmark manager to the folks on in the room.

Yes, absolutely. So there's the Asset Management portfolio manager and the benchmark manager. I kind of look at those -- there's value across each of those, but most importantly is the benchmark manager. We have a lot of the asset management, portfolio management data now, but really how do you compare that to benchmark and not just the headline number, but it's drilling down into the various different attributions, yields, the cash flow impact and then the cash flow impact going deeper within submarkets et cetera. So we're able to take the performance headline number, which we've had for a while, income versus capital and then actually drive into what the attribution is and then get as granular as we can on the asset individual. And there's a lot of value there. I think the deeper we go, the more value is there. And I know you got to kind of start at the MSA level broader levels, and there's a push to bring that even drill down. That's where I think where you can really get a true comparable set of data where it becomes pretty powerful.

Yes. We were chatting backstage. You also made the point of how you use the tool or can use the tool to assess your asset managers' performance sort of almost at the compensation level.

Yes. Look, I think across -- everyone needs to know their scorecard they're measured to. And I think the more objective data you can build into a process that's fair. No data point is the end all be all, but it starts to drive a conversation. And even like in a down market, if you have an asset, maybe you're an Asset Manager, you dealt a bad hands, but it's more of a stop-loss type thing you're doing. And it's like, okay, yes, market rent and the market has gone down, but you've managed to keep that up. I think that drives the conversation. It's not just the yield -- oftentimes, it gets blurry with the yield and the cash flow. And if you start to then within the cash flow, be able to benchmark those things to a relevant data point at that granular level. That's something pretty powerful and something that Altus has the unique ability to do so given the amount of data that you have insights into?

I think, Joe, that's a really good point as well. Really, for us as an investment manager, it's important we can benchmark obviously against -- but in downturn of downtime or good times, how do we demonstrate the offer that we're delivering for our clients and being able to clearly point that out and whether it's sector strategy, a property strategy, whatever it is, that then helps us to raise capital in the future as well, being -- having that clear strategy.

That's a great point, leveraging for our LP presentation [indiscernible]?

Exactly. The LPs have a lot of resources that keep us very busy. So any tools that are going to help us get to the key points very quickly and be able to explain those to our LPs. It's -- as I said, I think before, I mentioned it was a game changer. Just that efficiency for us is fantastic, really powerful.

I just add on that a little bit. One source of truth. I always say that one source of truth right now across various different funds of an idea. This, the data is out there, but people are kind of running things in different areas. So if you have -- there's the Altus ID for each property and then that becomes connected across the different systems. I think that is pretty powerful just for efficiency. So I think there's kind of short term, once these -- all these systems are connected and you kind of drive reporting from it, the reporting and efficiency that's kind of the short-term thing, but I think once you have all these forward-looking data points with historical data points, with benchmark data points, you blend all that together seamlessly, all these ideas have been out there forever, but the technology is only so many hours of a day. So we're not able to always do all the analysis that we want to do. And I think we're starting to see that come to fruition or at least that the foundations are building blocks...

And I think that's a foundationally important point because I think folks outside of commercial real estate, perhaps don't realize just how hard it is to connect the data. I'd like to [indiscernible] when I found my previous company Reonomy that was one of the seminal points of technology and IP that we developed through the Reonomy ID, which is now the office ID, but I lost my hair doing it. That's right? And just to pull on that thread a little more. I think part of it is also the data interoperability so that you don't have to jump from one application to the next, from Excel into ARGUS and back and forth. Can you talk a little bit about the benefits about the unified solution as well?

Yes. So having an interface -- I mean, this kind of relates back to the Excel point, but everyone is familiar with Excel. I mean, people have to take ARGUS trainings to learn. It's not the most intuitive thing and it's kind of badge of honor when you're the ARGUS Expert. But is that -- if you can have that ability in Excel, which so much of the other reporting analysis is being done and customized analysis. Having that all is something that in a format that's readily available and can calculate based off that interface, that everyone's used is critically important.

Yes. I'd like to add to that as well. I think, for me, it allows me to collaborate with my global colleagues. The journey of distance and time in Australia is that generally, I can work on -- I need to work on a 24-hour turnaround, which is so inefficient. So being able to work on the one model, see if you're sitting in Germany, in Japan or in the U.S. at the one time. It just, again, cuts all that friction down. And as Joe was saying in the Excel interface, it's really easily adopted by all of our teams around the globe. So it's -- and I can even open it up to my Asset Managers. So then I'm getting real live time data and insights into the market at all times because an Asset Manager is typically not the -- I wouldn't know the first thing about using an ARGUS Enterprise model. But for an Excel interface, they can easily pick it up and be trained quite easily...

As Mike mentioned, we're moving to that base pricing now. So you guys like mention -- you guys are on asset-based pricing usually and that's one of the things that also facilitates that ubiquitous and eliminates the barriers to adoption...

So historically reported the asset-based pricing, always be this kind of game would go back and forth with how many users are they all critical. We've reduced the amount of licenses, then that will reduce our fees and then there's backlog. At the end of the day, everyone on the platform should have access to these systems. And so I think opening that up is a really net positive direction. We don't have to -- everyone has access to the data within our organization. No one is prohibited from seeing all that. From my perspective, I think it's a definitely step in the right direction.

And just staying with you for a moment longer, you've been on the journey of ARGUS Intelligence from the early days when we first released a beta and your team were planning around giving us feedback that you tell the [indiscernible] online, how has been over the last 6, 12, 18 months to sort of see the evolution of ARGUS Intelligence?

Yes. Absolutely. I've been using ARGUS in my entire career, backbone is DCF 15, et cetera. And there's always been this like untapped potential of doing more with the data. And so over the last -- there's been a time where we wanted to see this happening as an industry, and it's taken a little bit longer than I think we would have liked to, but the fact that -- so when I saw the initial demo like this is powerful. This has a lot of great potential here. But being in beta form, it's like, okay, we have this data. We're doing this now. It would be interesting to see where it turns out it now fast forward a year or 1.5 years, there is incremental changes. They've moved at a pace that's pretty profound, and it's now -- it's going from something that's kind of like theoretical to maybe a nice to have to we should get on board here because when -- if we're not the rest of the industry is going to, we don't want to be a lagger in that regard. And there's -- it's profoundly moved in the right direction over the last year.

That's great to hear. Thanks, Joe. I know we're coming up on time, but we cannot have a fireside chat in 2025 without talking about AI. So I'll maybe end it by asking you, Chris, what are your thoughts on AI and how it should or could be applied in commercial real estate?

Thank you, Rich. Look, I'm just a simple property guy. So AI. I'm not quite sure of its capabilities. One thing I do know is that you need to have solid data. And once that's there, it's verified, it's accurate, then I'd say, let the AI out. So I think in the commercial real estate, we've been pretty slow adopters of change. But I'm really excited to see what that AI can bring to commercial real estate.

Awesome. Well, we're at about time. I am all that standing in between you and demos of those products that these guys were talking about. So I will thank you both again. And then I'll turn it over to my esteemed colleague, David Ross, to run you through the next part of the session. Thank you again.

Thank you very much. Particularly, thank you to Chris and to Joe. Obviously, my job is that every day is to make sure that I'm listening to our customers. Understanding what is most important to them and to deliver on that. What I'm going to do is I'm going to stand, do a little bit of framing from my -- the smarter people in the room for me, who are going to come up and show you more about what we've been doing over the last few years. But to just frame that strategy, I wanted to take you back where we've been, what we have been doing and then give you some direction about where we're going. Over the last number of years, we have completed the migration of our customers, their software, their usage on to cloud. A big driver, a big important element of that is allowed us to aggregate the data. So there's a whole host of data that is behind what our customers do with ARGUS Enterprise. The asset information, the models that they generate, the outputs and the performance ultimately that they understand from that. And we put that into a safe, secure environment and it also allowed us to scale the investment. We then met that with the development of a modern native cloud platform, and that was intended deliberately to then return back to our users and to our customers, access to the insight that we have been developing. You've heard from Chris and from Joe, you'll continue to hear what drives AI is the access to high-quality usable data, and that's a lot of what we've been putting in place. Underneath the covers within ARGUS Intelligence is a lot of learning, some of which we brought in from outside. So with the acquisition of Reonomy, we've got access to new techniques and tools that allows us to aggregate and move data at pace. So the knowledge graph, the development of Altus ID and a lot of the tools that sit around that have allowed us to produce a much more capable way of interacting with the data. And then where we're going from here is very much converging all of the user experiences we have into a unified experience itself. So we will focus a lot on valuers today, but those are Asset Managers, they're portfolio monitors, there's fund managers, there's appraisers, there's brokers, I could go on. . And I think you heard directly from Joe and from Chris, they want to have that ability to share across all of those different parts of the life cycle. All right, we are driving towards being able to do that with a compelling user experience, but also making sure the data is being shared backward and forward. And then ultimately, you're going to hear a lot about it because that's probably we are -- we want to be able to leverage the AI. So for me, I have been working in AI for nearly 30 years. It is my bread and butter. I know what we're doing with it. It is a vault dramatically. It isn't just about generative AI and LLM, there are a lot of different ways that we can bring this to automate what we do to guide users to help them take the next step. So when we talked about Forbury, the Excel interface, making sure you can do that in that space as much as any other experience that we deliver. To give them insight to give them information or give them a derived outcome from what is in the data itself that they may have taken much longer and more challenging to actually find it and then ultimately to generate output that can be shared broadly across organizations, so whether that's a valuation model, it's an appraisal report or whether there's some other aspects. So with that, I'm going to invite my colleagues up and they're going to show you a bit of what we've got. What's key behind this is that we want to show how we're combining data and AI, collecting the right information, using our information, assembling it in the right way that we can actually produce some appropriate output. We're going to show how we augment the human with the AI. This is not about replacing or removing individuals from this. This is about supplementing our human experts with tools and capabilities that help them do their job faster and more capably. And then ultimately, how that unlocks value for them, ensuring that we're empowering those users to do higher order tasks. I think what was key from what was Chris was saying that allows them to spend more time developing their strategies. The things that actually really drive value for our customers, cranking the handle on actually producing valuation models isn't that much fun. And certainly, if it's time consuming, it takes you away from things that really help the business. So that's where we're at today. So with that, I'm going to invite Matt LaHood, who is our Head of Platform Data and Analytics, alongside Lauren and Peter to come up and give the demo and show you how we're actually bringing this to life.

Thank you, David. So I just need a second to plug in here. Okay. So thanks, everybody, for taking some time to be with us. And for everybody who's joining remotely. We appreciate your time and attention. And really, what we want to do today is bring the strategy that you've been hearing about to life. So it's not just about, let's bring the data and put a web interface on it. Let's really work with the experts. Let's work with the Chris and the Joe's. Let's work with Lauren and the broader valuation advisory team to really understand the why behind the things that they do, so when we do build out the software, when we do build in the automation and the intelligence, it can have the most meaningful impact to the things that they do and the decisions that they make. So just one housekeeping note before we get in it for the people who are joining remotely. The demo will not be broadcasted, but you'll still see us as presenters up here on the stage. So as we get into it, we can see here, this is the homepage. This is a landing page. This is ARGUS Intelligence for the people who haven't seen it before. And you can see here, we have ARGUS Intelligence core, so this is the Asset Manager and ARGUS Enterprise. As the name implies, Asset Manager, we're really focusing at the asset level. Here, we're giving users the ability to create assets in a number of different ways. But then we're also bringing in new data sources as well. So it's not just the modeling data, we have access to all kinds of rich data sources like the Reonomy data. So bringing that in, surfacing that in new ways for people to use it to make better decisions. Moving on to the portfolio. Here, we'll be able to aggregate those assets in a number of different ways for people to do all kinds of different analytics and comparisons on. Here, one thing that you'll see is we're able to instantly and consistently create these portfolios and service the information. One of the things that we hear a lot from our clients is it could take hours, even days to do those aggregations. And when they're done, A lot of times, each of the portfolio managers do it a little bit differently. So there's not a lot of consistency there. Here, we'll see that we can solve both of those. And then finally, we have the Benchmark Manager. Here, the Benchmark, a super powerful tool. It's not just a list of numbers. It's not just here's your benchmark. Here's your average market rent or your contract rent for a particular sector. Here, we spent a tremendous time working with the valuation advisory team, working with clients. We've actually conducted over 100 interviews and demos to really fine-tune what we have here. And as you'll see, it's focused on attribution. It's really focused on how has the benchmark changed? How has my portfolio changed? And then as Joe was saying, what are those differences in terms of yield and in terms of cash flow and drilling all the way down to the asset level. So a lot of powerful tools here. You can see each of the different components that we have. They build on each other. They build on the rich data that we have and they build on the expertise that we're leveraging. So if we start off with Asset Manager, here, we could see I just -- I have a list of assets that I have permission to view -- and we can see here, one is just a simple asset. It's one address, it's one property, one building, but I also have the ability to create things that are a little bit more complex, that might be in line with my investment. So here, we have just a demo property. It's actually made up of 3 different buildings, with 3 different addresses. And when I click on that, what we'll see is -- so it is just demo, like demo addresses. So the map just puts us over the ocean. When you have real addresses in there, it will actually put you at your actual location. But here, one of the most powerful things behind the scenes is that Altus ID, right? So we're connecting these properties with the models from ARGUS Enterprise. And you can see here, I actually have over 45, 47 models for each of these properties that I can access with just a couple of clicks.

And let me jump in there, Matt, because I think, yes, it's good to be aware of our clients who have been using ARGUS Enterprise for many years, so in some cases, even decades. And you can imagine that over the course of time, they've been collecting dozens, hundreds of models for an individual asset. And it will take them a lot of time looking at and going through that data set to actually retrieve and find the information that is truly valuable. So imagine that you're getting a question from one of your investors, one of your LPs. And we heard Chris saying the 24-hour turnaround, being able to answer such a question to boost the confidence and the trust in your insights to your LPs is going to be critical. So being able to actually retrieve that information in a way that it's accessible is of great value to a lot of our clients. .

Yes, that's great. And we'll see through some of the demo, how we can access those different models and do some of those comparisons and analysis. So here, when I click on the overview, we can see that it's going behind the scenes. It's summarizing those 3 properties, the latest valuation models that we have for each of those 3 and giving us a number of key metrics. So here, I can see we're actually doing pretty well with this asset. It's got 100% occupancy. The base rent is actually higher than the market rent. So it's doing really well. And then I have a number of forecasts. I have my NOI forecast. I have my cash flow. I can see how the occupancy is going to play out over the years. I have some of my modeling assumptions here in the discount rate and the cap rate and then a summary of the cash flow. And then at the bottom, I can see I have each of those 3 properties with some of the key metrics. So if there was something up top, where I had questions on, I could come down here and then see how that's playing out or I can simply click on one of those, and then the page will refresh. And then instead of being all 3 of those properties, it will give me the same information just for that single one. And then here is the first place where we're actually starting to introduce some of the automation. So here, if I click on the files and I launched the tenancy importer, what this does is allow me to automatically ingest my rent roll. So up until now, the users have to actually hand type in their rent rolls into ARGUS Enterprise, takes a lot of time. It could be prone to errors. A lot of review has to be done because this is really valuable information as a key part of the model. So it has to be right. Here, what we're doing, we're leveraging AI. We're using the strength of the LLM to actually read the files that come in to understand what's in it. And then once we have that understanding, we can map it to the data that we actually want to bring in. The user will confirm that. Yes, that's the data that I want, that's the right spot and then that can be set up as a template. And then the next time you do it, it could be automated. So Lauren, do you want to talk a little bit about how your team would take advantage of this.

Yes. Thanks, Matt. So right now, our data ingestion, as Matt mentioned and as a couple of our clients mentioned is highly manual. It requires many layers of review and it's definitely prone to human error. By using this automation, we'll be able to eliminate that error, streamline our processes, honestly and be able to complete valuations faster and spend more time on high-value analysis, which is really end of the day, what we want to be spending our time doing.

Great. So then the next piece that we want to show. So once you have your rent roll ingested, the thing that you would do is work, spend a lot of time researching and coming up with the modeling assumptions that you're going to be using for that quarter. So here, I just have an individual model. And what I'm going to do is I'm going to use our valuation agent to actually come up with a set of recommendations. So here, what we have. We've spent a tremendous amount of time developing this. So we have a research lab with about a dozen data scientists. They've built a whole suite of machine learning models behind this to actually come up with all of these recommendations. They've also built algorithms to figure out what comps are most relevant for this individual property and the recommendations that we're making. And then that's not it. That's not the whole story. Like a lot of us who are well versed in analytics, you know you can have the best model, you can have the most predictive model. But if you're not surfacing it in the right context for the user, they're not going to take advantage of it. They're not going to use it. It's just going to on the shelf. So we actually ran an alpha program with the valuation advisory team that was 3 or 4 months. We did about 8 iterations on the software to really fine-tune and understand the context that they need to use these recommended values, so then we can really streamline and impact what they're doing. So we can see here highlighted in the blue, we have the recommended ranges for each of the modeling assumptions. And then one of the first things that they wanted to see was how does that compare to my last model. So that was the model that we selected when we first did these calculations. So we can see, here's the model, the last model and the delta between what's being recommended now and what they had last quarter. They also spend a tremendous amount of time in the benchmark, looking at the benchmark, doing comparisons, trying to figure out where the market is, where it's going. And so we've built that in side by side. So we can see here for the same property type for the CBSA, which is the same geographical region, what are those benchmark numbers. And then we also did the national averages as well. So then they can really have at their fingertips, a lot of information to start to home in on what they want to do and where they want those recommendations to be. The other thing that was really valuable for them was the comparables. So we have comparable sales, we have comparable leases and then also the exit cap and the discount rate. Here, the functionality is all the same between those. So I'll just click on one. We'll look at the comparable leases. And here, as I was mentioning, we have algorithms just crawling through the data, trying to find the most relevant ones to surface to the user. So here, we have our subject property, and we can see some basic information on it. The building size, the year it was built and then a lot of information on the leases. We're surfacing 10 comparables, but it's really up for the experts to go through there and pick out the ones that are going to be most relevant for the current situation and the ones that they want to use to reference in their models. So Lauren, I think you guys go through here and you take about 5 for the valuations that you do.

Yes, that's right. So what we find really exciting here is that all the comparable leases, sales, key data points and KPIs are really brought to one place. Right now, our teams can spend endless hours doing research, compiling all these data points from different sources. And manually and putting them into our own software, our own spreadsheets, right here. All the data is right in front of us, which will allow us to complete our valuations faster, spend time finding the right comps, the right data points, which is really great. .

Yes. Matt, maybe imagine we're looking at this from the perspective of doing a valuation, but imagine putting this into the hands of an acquisition or underwriting team who are working through dozens of deals each month, hundreds of deals and opportunities each year. If you would put this into the hands of that user group, they would be able to start joining those deals much faster and really spend time on more diligence to identify those deals that are making most sense and best aligned to their strategy to hit their targets. And this is going to be a huge way of saving time for those kind of teams and also help them in the end, prove out better returns. And based on those data-driven decisions that they're able to make with these kind of capabilities.

Yes. So that's great. So it's functionality that we build out once, but it applies to multiple personas and different points in the CRE life cycle. So that's great that it's going to be powerful for a number of different types of users. So once we've gone through that, once we've imported our data, we've gone through, we've landed on all of our modeling assumptions. We've got our models set. The next thing that we'd want to do is really aggregate those models or aggregate those assets into portfolios. So here in portfolio manager, we actually have a number of different ways that we can do that. So I can come in and I can select from a list of assets. So I can say these are the assets that I specifically want in that portfolio or I can write some simple rules to capture the assets that I'm interested in. So here, we could see there's a number of different ways to do that, just to call out one specifically. If I wanted to have all of the industrial properties in New York, I could code that and then that would dynamically update every time I clicked on that portfolio. So as things were acquired or disposed of, the system would automatically know that and take that into account when I clicked on the portfolio. So I'll just click on one here. So every time I click on it, it's going through, it's understanding what assets are in there. And then it's doing all of the calculations for the metrics and summarizing. So see -- I can see here I have 75 assets in this portfolio. Some of them have multiple properties in it. I'm actually up to 78 properties. . And then I can see that it's a very similar layout and set of information that I had when I was looking at the asset, and it's actually all of the same information, right? It's the same models -- it's the same summaries that I had at the asset level that I have here. And then I also, as before, I have the list of properties or yes, the list of properties and some of their key metrics. And then if I saw something here and I wanted to go back, I would just click on it, it would take me right back to Asset Manager, and I can do some further investigation. One of the most powerful things here -- and to what Peter was alluding to before, having all of that history. So I could come in here and I can select my valuation from the prior period, and I can instantly get a comparison to see what has changed from the prior quarter, right? So I can see here that I've increased actually 6 assets. Obviously, my total value is going to go up. But my value per square foot is down. That's probably something I'd want to look at and investigate. I'd be free to go through that here. But really, the power in having all of that history as I could come in and I could look at, okay, well, what's happened since the start of the year. What's happened in the same period last year. I can all go back all the way to when this portfolio was initially set up having all of those models in and see since inception what has happened, all just with a couple of clicks, having that history built into the platform.

Yes. And you make it look really simple, but I think it's good to understand how difficult this is for our customers as of today. But having this data organized and structured around that asset ID that Altus ID, is really going to drive the ability that you're showing here. So when we're speaking to clients and I think Joe was alluding to it earlier on as well, it's getting the insights out and having to pull the data in some cases into Excel. But if you want to look at this from different angle, so you want to look at this from -- for all your office assets or you want to look at all your West Coast assets in the U.S. you want to be able to build those insights really quick, and this is going to save hours. This is really where you're going to be able to pull the data together in minutes rather than having to spend a day or so, putting this back into Excel and compiling those insights.

Yes. And then from a valuation advisory standpoint, we spend countless hours pulling this data for our clients. Do they want a set of assets together or set of portfolios together. We don't always have the time to do this. But with this product, it really does allow the data to be at their fingertips and it can really help with us and give us an opportunity to provide additional insights for portfolio analysis. So this would be very helpful. .

So that's great. So we're already seeing some areas where you could have time savings and then there's actually a real need from our customers to have further insights and that all can be driven from here. So the next thing we'd like to highlight is the benchmark. So I click into Benchmark Manager. There is intelligence behind it. So I was looking at the Connect Portfolio and the Connect Portfolio is the one that comes up. So it remembers what I was doing. But I'm free here to select any of the portfolios that were created, and I don't have to do anything for this. As soon as the portfolio is created and it's available in portfolio manager, it's also available here. So there's no additional setup needed. Just to take a quick tour through the tool bar here. I could either look at all of the data, which is the data that we have from our software side of the business in AE plus the services side that we get from the valuation advisory. We're bringing all of that data together to have a really comprehensive set of data for our clients to analyze. Here, I could also select core open-end, so I could have a fun type. Here, this is something that our clients have been asking for, they want to see more fund types, something that we're considering for '26. And really, what we're hearing across the Board is they just want finer views of the data. So we'll hear a little bit about that in a minute, but the fund type is one that they're really interested in. We've also seeded this with 5 years of history, so I'm free to come in. And if I wanted to do a historical analysis to click on one of those dates. And then everything here is a delta. It's a difference between -- and so I could look at the quarterly difference and annual difference or 3 or 5 year. Here, I'm just going to stick current period quarter, and I can see that in my portfolio, I actually have 78 properties and I'm comparing that to well over 15,000 in the benchmark. So one of the other things that our clients have been asking for is to include property subtypes to really get into finer cuts, so we released this in Q1. We've already built this in for them. It was by far and above the #1 feature request. So we're glad to have that in there. And then I can scroll down and I can see the headline. So here, I'd be a little bit frustrated and slightly under the benchmark in terms of my appreciation. And I can see how that plays out in terms of the yield and the cash flow and the allocation and selection. And then as we heard from the fireside chat, right? We can see the detail behind that. So I can see, yes, my discount rate, my cap rate are creeping up a little bit, but the benchmark has actually been pretty stable on both. So I'm slightly disadvantaged to them. But I actually have a positive cash flow when they're negative. And if we start to look into some of the detail here, we can see a pretty interesting story building out. So I have a pretty big decrease in my occupancy. Usually, that's coupled with the OpEx ratio going up OpEx over revenue, my revenue is going down because I'm losing some occupancy. So those usually go hand in hand. What I'm also seeing is an increase in my contract rent. So this might not be a totally bad story because it seems like I'm losing leases that are under contract, under this current contract rent, but also under market. So I can see that I'm well under the market rent, and I'm under both the benchmark contract and market rent as well. So as with Asset Manager and portfolio manager, I can simply scroll down to the bottom here, I can expand and I can see either all of the yield -- the yield effects are the cash flow effects for each of the individual properties. And so here, I can just simply scroll through and see if this is really the case, if that's really the story that's playing out. I see some little increases and decreases, some puts and takes. And then I get to property 42 and there it is. There's a significant drop in occupancy, coupled with a big increase in the contract rent. So those are the -- indeed, the leases that I want to be losing out and recycling. And yes, my OpEx ratio did come up. And so if I wanted to investigate that further, I click on the hyperlink it opens up a new tab. It takes me back to the asset page and the overview, and then I'd be free to investigate any further here.

So you already mentioned, Matt, it's a bit frustrating, right? Because this portfolio is underperforming against the benchmark. But there's a little more frustrating and having to go and tell your LP that you're underperforming. And then not coming prepared with a plan on how you're going to remediate or what is causing that in the performance. So with this in my hands, I'm able to actually quickly identify what is the cause of this. I can work with my team. I can start collaborating with my asset management, property management teams to actually build out a plan, see how that plays out. I can use the Asset Manager and portfolio manager capabilities to work out a couple of scenarios and then go back to my LPs and say, I know I'm not maybe hitting the mark today, but this is my plan. This is how I'm going to improve my performance coming next round.

Right. So really taking advantage of all the capabilities here to come up with that plan and have as big of an impact on the negative performance as you can. So one other thing that I'd like to highlight is just a different way to use the Benchmark Manager. So this was very much a top down. Let's see how the portfolio is performing. But if I come in and I select a property type, I select a region. So it's Southern California, and I select just an individual property -- now I can compare just this individual property against what else is in the market that could be used to judge my performance. So here, it's just my single model against 470 that are in the benchmark. So before, when we were looking at comparables, we had a list of 10 to choose from, and we're trying to narrow it down to 5, but here, we can actually see we have a much broader dataset to start doing some of these comparisons. So here, the story is a little bit different. I'm actually very positive on the appreciation, which is great. Again, as before, I'm a little bit challenged on the yield side, but I'm positive on the cash flow. And then if I look down into the details, I can see that I'm actually very stable. I haven't had hardly any changes at all in any of my metrics. And this is really what we want to see. We want to see stability in our asset. We want to see positive appreciation. And if this is all I had I might just move on to the next one and be done with my analysis here. But with the 5 years of history that we've seeded into the benchmark, I can actually come down. I could see both the yield and the cash flow metrics and how they played out over the last 5 years. And there's a pretty interesting story here. So my occupancy is great. It's been 100% for the last 4 or 5 years. I can see that I started out with a pretty good separation in terms of the contract rent for what is charged -- what the benchmark has versus where I'm at. But over time, I've only increased pennies, while the benchmark has increased dollars. The good news is that I actually have further separation in the market rent. So I'm actually able to -- would be able to charge a much higher, almost 2.5x where I am currently, and it's much higher for where the benchmark is today. The other thing that highlights is this linear relationship with time and the lease term. So this tells me I have a single tenant, and I have about 2 years left on this lease. So this would be a high time for me to make a plan to see am I really going to be able to increase this lease by 2.5x. And if not, 2 years would probably be a good time to start who's going to come in, how much time is it going to take? Are there any renovations that I need to be doing in order to get my property ready to really be able to take advantage of the separation I have and the higher market rent.

Yes. And this analysis for both property and portfolio is currently offered as a service by our performance and analytics team, but it's only to a set amount of clients because it's manual and it's also delivered as a static report. Benchmark Manager will really allow our clients to dig into the data when it's available. And reduce that turnaround time that there currently is, which will bring a lot more collaboration to these client meetings and offer more insights on our side, which will be helpful coming into those meetings.

Yes, for sure. I could see a huge value in that. Like if I was a client and I had access to the tool and you guys were going to come in and actually use the tool to do the analysis, I could be prepared. I could have my questions ready. And then just interactively during the session, we could look and we can filter and investigate anything that we would need. So I could go on for hours, maybe even all day. There's a ton more in here that we just don't have time to show today. So we're going to close this part of the demo. But hopefully, you've been able to see the 4 legs that Mike was talking about in his strategy and really coming to life in the software. It's not just about, hey, let's surface the data in a new way, but let's leverage the expertise from internally, from our clients, and let's make sure that we're surfacing it in ways that it's going to be much more powerful. It's all built on our foundation. It's built on the AE calc engine. It's built on the Altus ID. And these are new foundational pieces that we're bringing to market. But I'm sure you can imagine if we had a team of agents working on your behalf, interacting with these foundational pieces, we could be much more efficient and effective. And that's actually what we've been working on and built and Aditya is going to show us.

Thanks, Matt. Good morning, everyone. Super excited to be here today. I'm going to show you all a piece of innovation that we've built. It's an agent that we've built that brings together, as Mike had mentioned, analytics, data expertise together in this application. We asked ourselves a question a few months ago, right? Can we build an agent that automates a ton of what our users like Lauren can do. So we started on the goal of building an agent that generates a restricted appraisal report for our users and gets that in about 90% of the time that it takes today. The AI that you're going to see is built on the same trusted foundations as an ARGUS calc engine. It's rooted in the same outcomes that Matt just described the same numbers. They all come from our calc engine under the hood. And our AI encapsulates that and brings the outcomes and augments the users. So to start with, this is our landing page for the agent. It's clean, it's simple. Our appraisers today deliver -- build about 20,000 assets worth of restricted appraisal reports day in, day out, quarter in, quarter out. What if we could take the agent, roll forward previous quarter's valuation model and make the report available for the next quarter with all the data from our platform, from the knowledge that pulling it together. And let's see that in action. Generate an appraisal report 4. These are the assets I've worked on in the previous quarter. Let's pick one. And the agent will go do its thing and should come back. Maybe let me refresh. All right. As you can see, the agent went back, created the appraisal report for the next quarter and here it is. This is our landing page. So this is our page of the appraisal report, we have laid it out in a pretty user-friendly fashion with help from our users guiding and shaping the vision all along. There are different sections available. The restricted appraisal report consists of a variety of tables organized in different sections on our traditional standard printable report, we have reflected those here that go on from value conclusion, the summary assumptions, income expense summaries, the cash flows, the input assumptions, and this is where all the supporting ARGUS model schedules are available all the way to standard stuff, boilerplate stuff like the cover page, the transmittal letter so on and so forth. So going back to the value conclusion. Let's start with the simple prompt. One of the pain points we've heard from our users is we make changes, adjustments to discount rate, exit cap rate all the time depending on the market. What if someone could just summarize very neatly for us what happened actually in the model. So that's a simple pain point that we started to focus on, and we'll look at that example now. So this is the prompt I gave it. I asked it to adjust the discount rate downward by about 150 bps. What the agent does under the hood is it goes in, opens up the ARGUS calculation engine that's been packaged up as an AI agent. It finds the relevant sources of data knows where to go in and make the change to the agent and then the agent will be intuitive and will tell the user, "Hey, I've understood your ask, I'm trying to figure it out, and let me go do that now, and it gives that transparency and the user is in control over here. And the agent is now going back and saying, you can see changes being reflected -- it's making the changes live on the report, and it's done. The value changed. It gives the previous value with the change, the new discount rate and gives a summary and a commentary of what it did, how it did in so on and so forth. It also pulls in our recommendation agent that Matt was just showing and highlights, hey, you're doing something. This may be out of range, may not be out of range, it gives that insight and pulls together for the user. Peter, would you like to add something here?

Well, so what I would like to point out here is if you speak to customers and you ask them, do you want to apply AI? And well, we've heard Chris saying -- he's a property guy. So he doesn't really know if he can trust this. But I think one thing that is really relevant here is that what is sitting behind this -- it's the same set of data, the same set of calculations, the same modeling capabilities that the industry has been trusted and have been relying on for the last decades. So when I hear clients saying the outcome of an AI model, 80% accuracy is not enough. We take -- we hear them saying that, and we're taking that into the way that we built this -- and we're making sure that this is comparable to the way that we're delivering our services as of today through all the manual processes that we have in place to actually deliver this.

That's exactly right. Moving on to a more complex prompt. As you can see here, you've got a vacant suite in this property at Suite 15066. One of the pain points you've heard from the users, and I was in the meeting in Chicago when this happened, the client calls Lauren, we've got an update to this property, someone just signed a lease, what happens to my value. So let's try to do that. I just signed a new lease for Suite 15066, new tenant is Altus Group. Lease is a 5-year term, starts Jan 1, 2026. All other parameters stay the same and we ask it to update. I'm being nice to the agent, please.

Yes. And throughout the quarter, we will get many calls from our clients as Aditya mentioned asking us to model a new lease and amendment and there is a downtime that -- we need to send it in a day or 2 days, but with using this tool, we'd be able to tell them on the phone, what happened to the value, how does it impact the value, which is really huge efficiency.

Yes. As you can see here, again, the agent has been transparent. It's telling the user what it's doing. It will go in and identify what part of the model, what part of the lease schedule it needs to make the update. We'll try to identify the empty suite, here in this case, Suite 15066. It will go ahead and update. And as you can see, it's identified the right spot, it will give the user that visual queue and then we'll go ahead and make the update there you go. And it adds commentary on what happened, how it changes the income, anything changed materially or not, so on and so forth. Now moving on to a different kind of user journey and a feature that we worked on, we've heard a lot of questions from a user pain points around what if something happens? I want to do X, I want to do Y. I have some capital in hand, I want to deploy that. I want to plan the renovation, what may happen, what may not happen and they ask these kind of what of questions to the agent. Now this agent here can do that. Let's slide the report out of the way, let the user focus on the agent at hand and the conversation. And let's collaborate with the agent. I'm planning a $2 million renovation in say, 2027. Please update. I'll be nice again. Peter, how does the market feel about this?

Well, so you can look at this from the perspective of a valuation, but I'm also wanting to think about other use cases -- preparing an investment committee memo. So looking at your acquisitions, if you're a bit more opportunistic investor, the question that you're just raising is going to be very relevant, right? So I'm going to build this all building, but I want to renovate it, I want to spend money. I want to be able to quickly answer this, and I want to make sure that this is a deal that is going to help me making my strategic objectives and my targets that I'm put out there with my LPs. Being able to do this like this in just a few seconds, yes, that's a game changer. This is going to create a lot of scalability for those teams that are working through all of those deals. So they can start processing 20 deals rather than the 10 deals that they might be doing each week.

That's awesome. And as you can see the agent came back and outline how it changes the cash flow across the years. The last piece of feature that I want to showcase today is the ARGUS model, the currency of the industry that moves around. And as you mentioned, like acquisition analysts and brokers get their hands on an ARGUS model, they want to see what is in there. They want to interrogate the data quickly. The agent can do that, too. Let's go back to the landing page. I have an ARGUS model here, I'm going to drag and drop it. I click go and the Wi-Fi still working. The agent goes back and then brings that out for this particular property in question. And that folks is breakthrough innovation in agentic AI that we brought to the platform. Really excited that I was able to demo this today, and I'm going to hand off to Rick Kalvoda, the President of Valuation Advisory to round this out.

Thanks, Aditya, and good morning, everyone. Wow, was that not impressive is. And I'm excited about this, and I'm speaking of someone who has been in this industry for 35 years, and this is transformational. This is something that will change the way we operate, just not only in the commercial real estate valuation side of the business, but everything we do in the commercial real estate industry. Why is that? As I think back to 35 years ago, when I started doing commercial real estate valuations and what did I do back then? I manually typed a rent roll, I manually typed an I&E statement. I manually inputted that into a DCF model and then spend hours going out and collecting data to bring that together to come up with a value conclusion. This changes that. This changes it to another level. Why does it do it? The first thing is, is 90% of what we do in the valuation process today, not just us, but everyone in the industry, 90% of that is menial, mundane and repetitive -- it's stuff that does not add anything -- any value to the end product. It's stuff that you just have to do to get to the 10% of what really adds value and coming up with the value of that asset. This changes it by automating it and bringing it right to the expert. The second thing that is transformational is -- we spend a lot of time going out and collecting that data relevant to that asset to come up with that value conclusion. This now centralizes that data, brings it to the expert and not going out to disparate data sources and trying to find different what is particular to that specific asset. It brings that to the expert, customized for that specific data. So then again, they can focus on the 10% that matters to come up with that value conclusion. Next is, and as Peter mentioned, is the obvious question that any expert, whether it's Lauren or anybody in our team or anybody in the industry, Jim -- or Joe and Chris, they're going to ask is, can I trust this? Can I trust the output from this? And two important things that we talked about that was critical, and this brings is, one is it's transparent. It's not a black box. Just as Peter said, is you can download the model at any point from this and audit and go down to the individual factual tenant information and understand where that value came from, that is critical for this. Second is it's run by the expert. The expert takes the output of that and comes up with a value conclusion. It's not relying on just what comes out of that. So two very important things as to what makes this transformational and then finally is if you take 90% of anything out of any process and especially if it's menial, mundane and repetitive and doesn't add any value to the end conclusion. Imagine how much more you can do with the 10% that does matter. That is critical not only to us and to the valuer and to the people in the industry, but it's to our clients and customers who now what they can do, and this will now help even more with the performance and the management of their portfolios. So very excited about the changes that we're seeing here and how we're going to use it, how the industry is going to use it. Before I pass it back to Camilla is I just want to reemphasize one of the things that you kind of heard throughout this morning is it's not just because AI is here. It's not just in what Aditya has done in a short amount of time. Technology is a very big part of it. But it's also Lauren and the 400 experts that we have in Valuation Advisory and then working very closely with the technology team to come up with what it's helping them. They live and breathe the valuation process every single day, of every single month, of every single quarter is it's them working with Aditya and Peter and Matt and helping them understand not only what we do, what's in that valuation process, but what part is menial, mundane, and repetitive that we need to solve for. That's what they did here. And then on top of that, so it's the technology, it's the experts that we have, but then also very critical. It's the data. It's not tens of thousands, hundreds of thousands, not even millions. It's tens of millions of models with hundreds of data points in each of those models that allows the experts and the technology to bring this together to come up with the solutions that you're seeing here. So I'm excited about what I've seen. I'm even more excited about what this will continue to evolve for and look forward to the future with that. So with that, I'll pass it back to Camilla.

Okay. Thank you, everyone. I think we'll take a 20-minute break, which I believe would put us at -- actually, I don't have a watch. So 20 minutes from now. There's coffee and snacks outside. [Break]

Thank you. I hope you guys enjoyed the break. Okay. I would like to thank our great demo team. That was such a terrific showcase of the innovations. Every time I see it, I walk away feeling just even more enthused about what's to come. Thank you, guys. That was really great. We're going to move on to the next session, the financial update, which is a great opportunity to walk you through, not only the new financial disclosures, we'll be rolling out with our Q4 results, but also the new capital allocation framework that we press released today. So with that, I would love to introduce Pawan Chhabra, our CFO; and Mike Gordon to take to the stage and to take us through the next session. Thank you.

[Technical Difficulty] in our shareholders [indiscernible] as the portfolio [indiscernible] obviously, we are start down [indiscernible] we are very comfortable in that. [indiscernible] If we can't be the right home to them, then they should be somewhere else. And I did get a couple of questions also from -- during the break, well, does this mean you're going to be looking at some non-core analytics products? And the answer is yes. At the end of the day, it's very simple for me when you take a look at the product set and what we have on the truck. If you can't make something be at least just one adjacency over and there's too much distance between what your core is and what that is and you're not going to build that bridge, it's probably not for us. And the reason being is, while it might be really good software, we won't do the right thing for that software ultimately because we'll continue to invest in the things that we would define as core. So that is going to be working, and we are going to be looking at that, again, same time frames. It's something that we want to do. We gave some midterm targets. Yes, guys, everybody knows the Rule of 40 companies kind of stuff. We -- our management team believes in it. We're going to push on that. And again, on the consolidated level. I have to keep saying consolidated level because you guys have been looking at us for years in a different way, and we've kind of conditioned you to look at us this way. And so we don't want to be that way anymore. I mean at the end of the day, this is who we are. And then finally, and again, we'll sit back about this as Pawan has told me this for the last 2 weeks, every day, he wakes up and he keeps telling me, Mike, we're the best PropTech investment that's out there. So why would we use the money any other way? That's how we're looking at it. So we are going to be increasing our go-forward capital allocation. We'll talk through that. We're going back -- we're not -- I feel like it's a back to the future moment. Before we got -- before we exited tax, we actually had a set target, and we just got away from that a little bit. We're going to get back to where we were. We think that this is a good place with us. We have really good strong cash flows. And with those strong cash flows, we should be able to return good value to our shareholders and at the same time, ensure that our customers are seeing the investment that we need to do into our product set. So with that, I'm going to turn it over to you because I get to play color commentary to this. Pawan is the designated driver for the next 30 minutes.

Yes. Look, I'm super excited to be here with you guys today. This has been multiple years in the making, and we're very excited to be sharing our new disclosures and how we're thinking about the capital allocation framework going forward. So let me start with the Analytics segment revenue reporting. So in addition to recurring revenue, we're now going to be breaking out the Analytics segment into 4 categories. The first one being software consist of ARGUS Intelligence plus a host of other software applications that we're resolving to the platform to become add-on step to ARGUS Intelligence. We heard you. We're carving VMS out separately, gives you a visibility of the tech-enabled expert services that our valuation management solutions team are delivering. And then we're carving out data and services separately. This represents the stand-alone elements of data and service. They have a different revenue and gross margin profile. And so it's really about making sure that we've got the right level of visibility and clarity on the core franchises of software and VMS, but then also understand the contributions of growth associated with data and services. Ultimately, the point here is to make sure that we're increasing our transparency and giving you the better blueprint to be able to start modeling growth. So when -- let's double-click into the software portfolio. As I mentioned, the software portfolio category consists of ARGUS Intelligence, which represents about 2/3 of our software category. But then we have a host of complementary software applications that we are resolving to the platform to be able to drive more models and more value into the core. And so you see those reflected here. Collectively, these are going to help provide an unified user experience for our clients as they utilize ARGUS Intelligence and the add-on capabilities.

Yes. And if you think about it and what David and the team talked about, I mean, again, when we talk about the platform, it's a platform, but it's made up of its services-oriented architecture -- they came -- we're just developing services and we're going to put more services out there. So the team is already working on the next set of services. So when I sit back and say, I feel comfortable with what we got. We've got a lot of things that we can expand into just within our own portfolio. So this is why we're just trying to simplify on this.

So keep going on software. So let's dig a little bit into the financial profile and some of the reporting and metrics that you guys are going to hear from us going forward. So first and foremost, we were going to talk about organic revenue growth. We're going to talk about annual recurring revenue growth. And as you can see from a year-to-date perspective, annual recurring revenue growing at a healthy 10% growth rate. We're going to be focused on talking about gross and net revenue retention for our software portfolio. Again, this ultimately helps speak to the stickiness that our software solutions provide, but also talk to the tremendous expansion opportunity that we have with our software developing at the platform and rolling out add-on modules. So as you think about the path forward for software, really 2 big growth levers for the business. One, you've heard Mike talk about the opportunity for us to continue to cross-sell as we deliver more value in the platform and when we provide our clients with a quantitative value proposition. And then secondly, asset-based pricing, which allows us to get ubiquitous collaboration across the client's enterprise. It drives adoption. It allows us to get deeply embedded into the client workflows. And then when it comes time for renewal, it gives us pricing opportunity as we continue to become more penetrated into the clients day-to-day.

Yes. And if I add it on, I mean I had a lot of -- you guys all asked a couple of questions like, okay, I look at the gross retention, what should I be thinking about ARGUS, ARGUS is higher. There's no doubt. ARGUS is in the mid-90s, and you guys understand where that is. So then you're going to do the math on me. Well, that means the rest of it has some problems. Some of them do. We have some older pieces of product out there and kit that we actually have to sit back and figure out how we're going to retire. And there's 2 ways to retire either you let it slip away over time or you just say, okay, we're going to do this and you have to move to this. I'm more of the partial of the second one. There are some good reasons why you let it slip over time, but that's just the normal thing when it comes to software. And so from our perspective, as we're looking at this, what I'm happy with and what I'd like to continue to see is that 15-point difference between gross and net retention. That means we're doing a good job of things on -- when you think about your recurring revenue table. So it's just -- we're not going to be doing anything that's remarkable. You guys are all doing this anyways, but you got your new business -- you got your cross-sell, you got your upsell, you got your churn and down-sell. The good news is we're not really down-selling on our core stuff. The good news is we're not really churning on our core stuff. But what we have is we have -- what we want to make sure is as we talk as a leadership team, and then we have our guys talk through everything else going down into our organization is that we really want to understand like, okay, once you landed here, how can we get them to use more? I want our VMS guys to be talking to our guys about software. They're not software salespeople. I don't expect Rick to do that, but Rick is pretty good as a software sales people. You heard them today. But I don't expect that. But what I do expect is that as the funds are using us, there's so much we can bring to them and so much data that we can bring to them and so much information that each piece that we're showing, I think, becomes a lot stronger. And so that's where these things coming together makes sense. So while we've broken the 2 pieces out, so you can see them -- at the same point, we do think that they're very synergistic.

Excellent. So let's look at our second category, VMS. Again, as you all are familiar, VMS delivers trusted valuation insight and compliance to some of our largest clients around the world. The valuation process creates a lot of exhaust data, and we provide independent oversight to manage that process, but then we also normalize that data and put it into ARGUS Intelligence. At the end of a VMS process, we have a very thorough conversation with the clients, as you saw in the demo in regard to what are the drivers of growth, what are the attributions of growth. And so that leads to a very fulsome conversation from a VMS perspective. As we think about the path forward on VMS, our VMS teams internally now are leveraging ARGUS Intelligence. So now they can go faster and they can process through information in a much more efficient manner. And then as you think about the convergence between software and VMS, we can now take the relationships that we have on VMS and look at their assets that may not have the same compliance requirements and deliver the same type of output that we're delivering from a VMS perspective. So it's a very synergistic relationship in regard to how we're growing VMS and software and how they are both complementary to growth.

I've said enough about it. They do -- I mean, Rick will be walking on water later. Maybe you too. If you want to see what they really know how to do in this space.

So keeping with the theme in regard to reporting and how we're going to talk about VMS going forward. Again, very similar to software. We will look at the organic revenue growth, and we'll also talk about the annual recurring revenue growth number, but the most important measure for me within the VMS business is really understanding that gross logo retention. And really, what it does is it showcases the durability that we have with our clients, whether it's an up market or whether it's a down market, our gross retention is remarkably high and a testament to the power that our teams deliver. And again, as we think about path forward and growth from a VMS perspective, we're going to continue to have secular tailwinds that's going to drive capital into the CRE space, which will translate into more assets being deployed. And as our teams become more efficient to deliver the VMS output, it allows us to be able to enter new customer fund types at potentially different price points, so it really expands the addressable market for what VMS can serve because weaken process information much more efficiently now.

Yes. With what you saw out there today, I mean, this is a piece that I think a piece of the business that we think will grow and will grow consistently and grow well. And the reason being is, at the end of the day, we have the best people, and we have the best mousetraps. And as a result of this, we're going to do a good job of like anybody else can go out there and do this. There's plenty of good people out there. But it's the combination of the 2 things. And what we're going to be able to do is like our guys know how to ask the right questions to the system. Now the AI will continue to evolve, but -- and people will start to get there, but that's when we'll have -- give them more and more tools. This is not just a step in time. This is going to be like what Matt was trying to show you with looking back over 5 years. We look at this going forward over 5 years, this business and the assets that we can deploy on this platform based off what our team is doing, we expect this to grow and be a really good pillar for us going forward.

So data and services, and again, as I mentioned, this represents a stand-alone opportunity for data and services. Obviously, given the different growth profile and margin profile, we are carving this separate to provide cleaner optics in regard to what's happening with our 2 core franchises, but it also gives you a baseline in regard to how these businesses are progressing. So from a data perspective, we've got data studio in Canada. We have the Reonomy in the U.S. When you take a look at the revenue trajectory here, we've talked to at our various earnings calls that we have a lot of scale episodic clients in the data business that have churned out. So we expect that to normalize over time. Services represents our premium support around our ARGUS products and services. We are consciously exiting non-core areas where it doesn't involve implementing ARGUS solutions. And so carving that out separately allows you to understand the dynamics of that driving in versus bleeding it in into a total recurring revenue number, which decreases your visibility. So this is really about giving you the tool set to be able to model our business appropriately and have the right transparency in regard to the contributions of growth that data and service brings to the total analytics segment.

On the data side, I know you guys will take a look at the gross margin and say, okay, can you guys do better? And the answer is going to be yes. There's been a lot of work that has been done over the last couple of years that we've been curating the data. This is not just keeping the data on every property and having like a file where you just open it up internally. This is actually pulling the data into some sort of usable foundation that we can use for analytics. That curation did take some time and effort. And once you -- and how you curate that data coming in and making it usable for our customers and our clientele and our AI was good, right? Then you can now get to the questions that you need to get to. So we expect our gross margin to improve on that. When you take a look at our services, one of the things that we're also doing is we're making it easier to deploy our products. I mean people want to be -- people do not want long implementations, like you saw in the product set that we can now ingest rent rolls, all right? Well, that was a large piece at one point of doing a lot of work around services to get that working. Now that we have that in the product, we expect that to go down. We're still going to have to do some of the value-added services. There's no doubt about it, but we're not necessarily looking at managing ourselves in that manner. We are not -- at the end of the day, software, data analytics and then that value-added services or that advisory role that we play, that's what we want to play. Just entering data, not where we want to be. We want -- would get that done in our platform as much as possible.

So simplifying the portfolio, obviously, a big theme. Mike started the meeting and you guys read our press release in regard to the immediate work that we're doing on that front, but let me take you back a little bit. When we divested the Property Tax business, we purposefully announced in that press release that we're accelerating our transformation to a pure-play software data and analytics platform. And so what that means is we're very comfortable shrinking to grow, shrinking to grow more profitably by disposing of non-core and low-margin businesses. It allows us to have clarity in regard to our capital allocation perspective. It allows us to deploy our capital in a smart way, and it allows us to take a lot of costs out of the business. So to that end, as you guys heard this morning, we're in advanced conversations on divesting the appraisal business, hopefully, with the Q1 output.

Very advanced. We have an LOI. I keep -- I have to put that out there for Terry. Signed LOI.

We're also in the process of advanced conversations on the Development Advisory business as well [indiscernible].

Not as advanced.

Not as advanced. Several conversations on the DA business that we're hopefully going to provide you more updates on going forward. And then obviously, as Mike just referenced, there are some non-core elements products and services. Within the Analytics segment that we've talked about at the earnings call that we're also going to look to divest. But again, this is really about simplify to grow and how do we just make sure that we've got strategic clarity in regard to where the value is, and it's really around ARGUS, VMS and the platform.

I think if I just added one more word in here that I didn't open up with, but we've talked about it as a leadership team and a Board is predictability. We -- as we've been trying to pull the businesses together, we want to be very predictable with how we're flowing, how that's happening, so that we can give you guys that over time that we're just going to continue to roll. I mean that's -- I mean, a boring business that's predictable that continues to hit what it needs to hit is like not a bad business. And so I'd rather be a little bit boring and predictable than being a little less predictable. So from -- with that, that's why as we go through all these metrics. That's why when we look at these, these foundational metrics will help us bring that out to you guys.

And that predictability will make my life a lot easier. Thanks for that, Mike.

I'm trying.

Look, in terms of the P&L, I'll keep it brief. But the point of this page really is to show you that we're changing the format or P&L from a presentation by nature to our presentation by function, which hopefully will give you a lot more clarity in regard to the moving parts within the business. It will highlight the strength of our analytics business and the gross profit and margins that we're driving and continue to drive in that space. But equally as important for me and hopefully for you as well, too, is we have a lot of corporate costs in the business, a big focus area for us. And again, the catalyst to be able to action corporate costs is to simplify the business. And so we're breaking down and breaking out in a more traditional fashion. You can see our path on how we're going to optimize R&D, sales and marketing and G&A. It will become a part of our talk track as we go forward. And I wanted to make sure that you all had very clean optics in regard to how that's impacting growth and measure our performance and see if we do what we say over time to be able to achieve that. But this new format will allow us to be able to get to that state pretty quickly.

Yes. And when we look at some of the metrics and the ratios we have here, we know we have some work to do. There's no doubt that we have some work to do. And you guys can all come back and tell me where certain numbers should be. And I would agree with you. I'd agree with you. But this is what we're going to be doing in '26. Actually, it starts after we're done with you today that this is the first 2 weeks. The next 2 weeks start with that. And that's where we're going to sit back and talk about as an organization, how we're going to run. We've had that discussion already, but like now it's really saying, okay, now how do we do that and apply that across the business so that when you look at us and as we move into that software type of business, that SaaS type of business, you'll see all these metrics start to get into like what you think the business should look like. I mean this is why Pawan has been working on this, and there's a lot of things that he and his team have been lifting. Now we know how to do it, and now we're going to start executing on it.

Great. So as it relates to midterm goals and as you guys heard from Mike this morning, look, our path on simplification and driving operating efficiencies within the business give us a lot of conviction on our ability to hit our midterm goals. So our midterm goal is anchored on being a rule of 40-plus company exiting 2027. So how do we do that? So looking at it from a revenue perspective, we expect revenue on a consolidated basis to grow at the high single-digit level across Altus all in. . Within that, that means that ARGUS Intelligence is going to grow in the double digit. Again, the transition to asset-based pricing and deeper adoption that we get within the client base and the fact that we're bringing all of this power into the platform is going to accelerate our abilities to be able to cross-sell. From a VMS perspective, we're expecting growth to be in the mid-single-digit growth, mid- to high single-digit growth for VMS. Again, that's a combination of a CRE volume recovery that we're expecting to see in the marketplace, but more importantly, we're also making our teams more efficient. So now they can address a wider array of customer types and fund types a potentially different price points. So again, to Mike's point earlier this morning is how do we disconnect ourselves from the market, and it's about making ourselves more efficient driving more quantifiable value to our clients, and therefore, making us a very useful tool in a down market or in an up market. From a margin perspective, we're applying the same discipline. You guys have seen our track record in regard to what we're doing from a cost savings perspective, a lot of low-hanging fruit for us to still hit that particularly as we continue to simplify the business. Obviously, the adoption of ARGUS Intelligence internally is huge because it drives significant value for us from a service delivery perspective, it lowers our cost to serve, but at the same time, the innovation that spins out of the work that we're consuming internally is what we're now taking to the market as well to, but that is a tremendous opportunity for us from a cost perspective of drinking our own champagne and leveraging our tools to be able -- to be operate more efficiently. You've heard our story about our love for our India location in the global service center. It was not really a model that was in our DNA in the years past. . We've proven that we've won the hearts and minds of our own internal associates that there is a tremendous advantage of leveraging India and the great talent that we have there to be able to take best practices and standardize that a broad significant cost leverage for us as well, too, and a great model for us to continue to scale. And then obviously, there's a lot of opportunity for us from a G&A perspective to rationalize our corporate costs, reduce our facilities footprint and really just rightsize the organization as we continue to simplify and grow.

Yes. I think as we go through this, when you look at this slide, I think there's a lot of work to do here. I would tell you right now, we feel really good about our path on the cost side because we know what we're going to do around that. And then we're going to start executing on that -- starting in an hour or two. What I would tell you and I had a lot of people from the Board and from the team saying, well, going from 2% to high single digits, Mike, are you sure you want to put yourself out there on that? Yes. If we don't put a goal out there and we don't go -- get to that goal, well, if I just go medium single digits, they did tell me not to put a number. So HSD is the new acronym of the day. But if we don't set our goals to something, how are we ever going to achieve it? And this company has grown and we have assets that are growing at that pace right now and actually are growing at low double digits. And in my mind, there's 4 mutually exclusive ways to grow, very simply. Number one, we get new customers. We think that we can go down market effectively with the platforms that we have. We actually have -- we've integrated Forbury and ARGUS intelligence. We feel pretty good about that, that we can add a lot of value down there, and that also allows Rick to go down market to. Secondly, you raised price. Now for all the used people on camera. That doesn't mean we're going to raise price, but what we will do is we will bundle differently, and we think that there's benefits for that, and there is more value that we can get with our customers around that. So we'll leverage that a little bit. Third area is that we're going to introduce new products. You've got to see those new products walking out the door today. And the fourth area is to reduce churn. And the team has done a pretty good job of that. We can do a little bit more with that. And so if we just focus on each one of those 4 things and you just get small improvements in each, you go from 2% up to 8% or 9% pretty quickly. So again, I'm not out here preaching to you that we're going to turn that around immediately. But what I will say, regardless of the market -- that's how we're going to be looking at this, and that's how we're going to be managing this so that we can get to those numbers as quickly as possible. So I see the path and we'll be looking at this quarterly and we'll get there. And again, they told me not to put out high single digits. I don't care. We're going to get there, and we're going to find a way to that. And if I have to come up here in a year or two and you guys can say I told you so, then then we'll deliver something differently, but we're going to find our way there because we've done it before, and we can do it again.

So let's talk about our capital allocation framework. Again, for us, driving the most value back to shareholders is our north star. So as we think about our priorities from a capital allocation perspective, first and foremost, we're going to continue to invest in the business in organic growth of the business, to fuel and fund our innovation going forward. We're going to maintain our dividend. It's a great, consistent way to return value back to shareholders. We're going to continue to -- and as we started off, we're going to continue to opportunistically look at M&A opportunities. But again, the best M&A opportunity for us right now is to buy our own stock, and we'll talk about that in the next page in a bigger way. And then lastly, we are comfortable with taking our debt leverage ratio up to 2.5x. We have a very strong cash flow generation within our business. We have a very healthy balance sheet. We have a lot of comfort that we can run at a slightly higher net debt leverage ratio and still operate efficiently.