Morning, everyone. We're gonna go ahead and get started. My name's Brian Peterson. I'm one of the application software analysts here at Raymond James. Very happy to have Manhattan Associates with us today. We actually have a broader team here, CEO Eric Clark, I just wanna make sure I get this right, CTO Sanjeev Siotia, Michael Bauer from Investor Relations, Dennis Story, and Linda Pinne. Like, thank you for bringing the rockstar team here. Eric, we'll start with you. Maybe kind of a 60-second overview for people in the audience that aren't familiar with Manhattan.
Great. Well, thanks for having us, first of all. Manhattan's been in business for about 36 years in the supply chain space. If you break that down, where we really focus is Warehouse Management, Transportation Management, Order Management, Point of Sale, and Supply Chain Planning. Very well known in the Warehouse space. You know, what I always say is there's not a deal that happens in the Warehouse space that we're not invited to. We've had a presence there, we've been recognized as a leader for many, many years. Across those other products that I mentioned, we've entered those markets at various times. We are well known in some of those spaces but not all of those spaces.
Big focus this year from a sales and marketing perspective is to make sure that we do get invited to every deal that we wanna be in across all of those products.
You know, you've been here for, been in the seat for about a year. You know, I'd love to understand maybe lessons learned and what are some of the key things that you've implemented in your first year in the seat.
Yeah, when I joined, I was, first of all, really impressed with the quality of the products. I mentioned 36 years, but really, we're a 10, 12-year-old cloud company. You know, this company has successfully reinvented itself a couple of times, and most recently was this reinvention around cloud technology. The reason it's so impressive is because Sanjeev and the team really committed to this cloud-first, all APIs, all microservice-driven. Through the years, they haven't done things like so many other software players have, where they've bought things and bolted them on and integrated and so forth. Because they really stuck to that foundation, now that AI has come into play, it's made it very quick and easy for us to deploy AI natively in our platform.
I wanted to hit on both of that, but maybe just quickly, the fourth quarter that you guys just put up was very impressive. You know, any kinda key highlights or anything that you call out in the demand environment for what you saw at least through December?
You think about last year, Liberation Day back in April and all the things that were changing with tariffs and everything else, I think a lot of people were concerned in the supply chain space, is that gonna be, you know, a tough go? We saw the demand, you know, continue to be strong. You mentioned Q4 was a record bookings quarter for us. 75% of that came from new logo. Full year, we had 55% of our bookings from new logo. We're seeing a lot of strength in, you know, companies in the market that are truly going out and re-competing their solution. When they are doing that, they're looking at Manhattan as really the only player that offers this unified platform across everything they're looking for.
All right. AI, we're gonna spend a lot of time on this. Just, you know, broadly speaking, I think there's a lot of concerns that AI will eat into the value propositions of app software. I know you both have written on this separately, so maybe I'll just open it up to you guys. What is your stance on that, and how should investors be thinking about the AI implications for Manhattan?
Yeah. I'll kick off, and then I'll let our CTO, Sanjeev, talk more about that. Yeah, this is one of those narratives that I think got overplayed very quickly in lots of different ways. The reality is, there will be software and SaaS companies that, you know, AI can really eat at them, right? You know, I talked about it in the blog that I wrote as winners and losers. The SaaS companies that will benefit from AI, where AI makes them stronger, will have the opportunity to put that AI growth on top of the cloud growth, and that's the opportunity that we see. Maybe I'll let Sanjeev kinda dig into why we see that and why we're so confident that that's where we're gonna sit in this.
Yeah. I think I wrote part of it in my blog too, right? If you have a farm store database, it's easy to kind of like really think about replacing, even though that's not even that easy. When you think about a complex applications like supply chain and everything else, there's a lot more which kind of goes in. I do not see a scenario where somebody on a weekend would kind of go write this application up, and somebody will just go buy that stuff, right? Now, AI, I see as a net additive to us in terms of what we've done with AI and how we have done it with AI 'cause AI is kind of natively built into the product. I mentioned in my blog, we generate a lot of our code.
If I go back to why we did all of those things, that'll go back to 14 years back when we started building this thing. First thing when we said, we had two choices: go lift and shift what we had and put it on the cloud or rethink on how the world will be five years, 10 years from now, and how do we prepare for the future. We made a decision that we will make a big investment to build for the future, right? Part of that, there were three or four core elements went into it, right? What we saw generally from a past history perspective, right, is user interfaces change every 10-15 years.
When we were building in 2014, we kind of knew that some sort of a user interface will come in next three, four, five years, and we have to be prepared for it. We took an approach saying we're gonna build everything as an API-first approach, right? To be ready for whatever that new user interface will be. We didn't know it'll be AI, but now it's kind of proving that our strategy kind of worked really well from that perspective. Second thing as we look through this, right, is when you think about workflows, we serve all tiers of customers, and our premise was we're gonna build everything as composable, right? We wanna make sure that our APIs, the workflows can be composed naturally, right? By configurations, by whatever else
That, again, I'll come back and tie back to the AI, how it plays. Build it as a composable thing. The third piece, when you build enterprise software, right, no matter what you do, it takes you N number of years. It doesn't get done in one month, two months. Typically, when you build software, what happens is what you build in first month looks quite different than what you build in the fourth year, right? You build a technical debt all along. We made a very strategic decision way back in 2015 that we are actually not gonna write a lot of software, gonna generate a lot of software, mainly from a consistency perspective, right? That we don't accrue any technical debt as we, as we progress. Those three aspects have really paid us well.
To even begin with, when people say microservices, when we started it off, I didn't even call it microservices. I used to call it components or componentized.
Okay. Components, yeah.
Right? The microservices kind of word came in later on. I feel like AI native, we are way ahead of that thing, is if I think about building an AI native platform right now, I would do exactly what we did in 2014. I would say we have been building this AI native platform now for last 10 years.
Well, maybe just 'cause I'll address it specifically. I think there's some belief that a lot of these customers may go out and build these things themselves. The WMS solution is very, very, very complex.
Mm-hmm.
Can you, like, address that specifically and why we wouldn't see customers trying to build these applications themselves?
Yeah. I'll give you an example, right? When we started in 2015, we already had a 20-year history with building WMS systems. We had all the domain experts in the house. We had a generator in six months we wrote, right? Which an AI could kinda write the generator and do something with it. Even with all that, it took a whole lot of us for three years to go build a system.
Sure.
If anybody thinks they can go build WMS in a weekend, they probably do not understand the complexity of what is required, right? We have roughly, let's say, 180 components. The magnitude of just understanding what to build-
Mm-hmm.
... is pretty large for somebody to kind of cross that bridge. That's kind of one of the reasons why I feel that there's a pretty large entry barrier for somebody to just go build a new WMS system on their own.
Well, and maybe I'll add to that a little bit. What about the complexity to implement some of these systems, right? I guess maybe taking the question a little bit differently, what is the opportunity for AI on the services side to potentially get more efficient? Is there anything that you can do there with customers?
Absolutely. Right. I think Eric talked about it a lot from a simplicity perspective, right? I think the time to value to accelerate it absolutely exists, right? We are looking at every aspect of implementation, whether it's interface mapping, design, how do you convert configurations, how do you test, all of those aspects, AI will absolutely be 100% effective, right? We're seeing, we are seeing time reduce, right? We are seeing acceleration from our implementation perspective with respect to, yeah.
Part of what that has allowed us to do is as we leverage more AI and automation in our services business, it's allowed us to start to do fixed price and fixed timeline deployments. We've started that with our conversions because we know, hey, you're running one of our on-prem products. We know exactly what you're running. We know exactly where you're going. It's very clear to us what that's gonna take. We started offering, you know, fixed price, fixed timeline on that. I expect that over time, as we get more and more confident in some of the automation that we're creating, that we'll be able to do that with new logo eventually also.
We also have the opportunity even more quickly to go and do that with customers that maybe have licensed software for, I don't know, call it 50 warehouses, but they've only deployed 20. We wanna go help them get the next 30 deployed more quickly.
Yeah.
These are all opportunities to leverage that AI and automation to move faster 'cause if you remember, the way our revenue ramps, it's based on a contracted revenue ramp.
Right.
If we can drive them faster than that, revenue ramps faster.
Maybe just to remind us, where are we on the conversion timeline? I know most of the WMS space is still on-premise today, but, you know, where are we in that conversion effort, and, like, how should we be thinking about that trajectory over time?
Yeah. What we shared on the last earnings call is that we've got about now 22% of our on-prem customers have either started or completed that journey to the cloud.
Mm-hmm.
We've still got a big opportunity for conversion. You know, we've had these cloud products now for, you know, call it, you know, roughly 10 years in most cases. On-only 22% went in the first 10 years. I think in the next 10 years, we'll see it go a lot faster than that. Part of it is it's just natural. You know, a lot of these companies forever have been on a cycle where they do an upgrade every 5-10 years.
Mm-hmm.
Some of them just weren't on their cycle yet. Now we've got this case where the gap between what they have and what they could have is just getting bigger faster. You know, we're never gonna build AI into the on-prem platform. To take advantage of all these new features, they've gotta get to the cloud.
Maybe just, like, thinking about WMS specifically in terms of the competitive landscape, you know, what are you seeing out there, and is AI increasingly more important in these conversations, or is it not yet, or is it on the roadmap? I would love to get a competitive update on WMS.
From a competitive update standpoint, you know, we mentioned we still have, you know, 70%+ win rates. I also mentioned, you know, in the last earnings call, a lot of people consider Blue Yonder to be our biggest competitor, and we've got 90%+ win rates against them in 2025. From a competitive standpoint, we're doing very, very well. We're very pleased with where we are. AI, of course, is a part of every conversation. Right? People wanna understand where are you going, how are you investing, how can we take advantage of AI with your platform?
With our customers. Sorry, with our competitors, you know, we've got some competitors that can tell a compelling AI story. When our customers really break that story down, and if the story starts with, "Well, first we've gotta move everything to a data lake, and then we've gotta do all this data indexing, and we're gonna perform functions over here and then move it back in, and we've gotta think about security of the data lake, and we've gotta think about latency," none of that conversation happens with us. You know, we turn it on, and you use it. Again, we're version-less software, so every one of our customers is running the same version of the software, which means right now every one of our customers has access to our AI agents. If they simply turn them on, they can use them today.
I think there's been some debate about, you know, cloud-based ERP migrations and if that's an opportunity for you guys. Any update on what you're seeing maybe from SAP or Oracle? Any kinda ERP replacement cycles?
Yeah. I think that ERP replacement cycle is always a tailwind for us, right? But I also think that. Because anytime somebody's going through this process of, "Hey, I've gotta relook at my whole SAP landscape because SAP's forcing me to do this upgrade," then it's an opportunity to think about, you know, best of breed, and do they wanna stop using SAP for WMS and come to us. And we've been very successful in that cycle. I will say, though, you know, a lot of customers, the dates continue to shift from SAP, for an example.
Sure.
That, you know, deadline doesn't feel as firm, and it maybe isn't producing the tailwind that we thought it would as quickly as it is, but it's a constant tailwind.
Constant in the market.
Yeah.
Sanjeev, maybe double-click a little bit on the AI products that you guys have announced and, you know, dive into some of the functionality and what can that do for your customers?
Yeah. When we kind of think about AI teams, I'll talk from a broad industry perspective on where AI can kind of impact software.
Sure. Yeah.
The four areas we see. One is just user experience, right? When you think about how this is even the human computer interface, how it's evolved, right? You started from a punch card, went to a green screen, went to internet, went to mobile.
That's right.
Now with the natural language interface, I think that overall you will see the software just generally change in terms of how you converse with software and how humans interact with it. That's kind of one piece we are focused on, and I think the overall industry should be focused on.
Sure.
The second piece we talked about time to value, right? How do we kind of accelerate our implementations? How do we reduce that time required to get somebody live and realize the value? That's kind of another big area of focus. For any packaged software, I guess, should be a pretty big part of focus. The third big piece, which kind of covers everything in some way, is productivity, right? We're looking at every operator who uses our system and say, "Okay, how do we make them more productive? What actions can we automate? What can we kind of make better judgments so that those processes can automate?" The fourth piece is around data insights, right? What can you get out of this data which you have?
What insights can you draw, and how can you kind of infer problems earlier, and take actions?
Mm-hmm.
Those are kind of four broad themes of all the agents we are building. They probably fit in all of these four categories. We have agents in each of those categories. I think these four broad topics I've mentioned to you, I feel just as a general broad software industry, those are the right topics to think through on how do you make progress on those.
As we're thinking about supply chain.
Mm-hmm.
What are some early, like one or two use cases that you would think would be the most interesting that would fit in one of those four buckets?
You know, sometimes I'll not kinda say there are some videos out there where there's kind of a little bit big, sexy, big bullet things. Where I find is even solving small problems.
Mm-hmm.
Can actually make a pretty big impact. I'll take an example. We publicly talked about Eaton, right? We built an agent. It took our forward deployment users about a week, two weeks to build that thing.
Mm-hmm.
All it was really about was they had an exception process when something happens. Somebody's constantly monitoring it, and then they will figure out how to chase the problem and fix the problem, right? The whole process we could automate in a week through an agent. That increased their shipping by 3%, right? That's a pretty big impact to the-
In the first week.
In the first week, right?
First week.
It wasn't really a big, large problem we had to solve. You can solve a lot of these exception problems, which is true across supply chain, right? Think about supply chain. There are a lot of small exceptions people deal with. In solving these small problems and add them up, they can make a pretty big impact, right? There will be big problems we'll solve too.
Sure.
Right?
The way we solve that is, you know, when you subscribe to our AI Pack, you get a standard set of agents that we've built and we continue to build. We'll continue to add standard agents. What's been really exciting is what you also get with our AI Pack is the Foundry, which allows you to either modify any of those agents and customize them for your operation, or you can build an agent from scratch. The one Sanjeev just mentioned was one that was built from scratch in about-
Yeah.
... a week or two with our team.
Yeah. We see that pattern across our customer base, right? I mean, I've talked to a lot of customers. They all have a spreadsheet on all of the exceptions they manage.
Mm-hmm.
How do they manage? They have a bunch of FTEs managing those exceptions. Even more than saving the FTEs, right? It's really the impact to the underlying metric, right?
Sure.
The shipping on time, the fulfillment rates, all of those can start changing, once you automate a lot of these things and speed them up.
What about the opportunity to use that with other agents, right, across other systems? I know people maybe don't talk about Active Omni enough and what kinda data that could provide in terms of the whole e-commerce solution. Maybe talk about that more on the front-end customer side and less so maybe on the supply chain side.
Yeah. I think just overall, AI will have a broader impact, and customer service side obviously has a pretty big impact. I think that's what people talk about the most, right, for various reasons.
Sure.
Call center agent kind of trying to get when a customer calls in, just getting a quick summary of what this customer could be calling about, giving them the right answers to the call center agent right there.
Mm-hmm.
in their face. Summarizing the calls, figuring out what happened with the call.
Right.
Those are all kind of really net additive to the customer satisfaction side of it, right? I've lost my train of thought. Just, so from an omni perspective, right. Store manager, let's say, take a store as an example. Today, a lot of store managers are trying to figure out how they can uplift their sales.
Mm-hmm.
They don't have data. They do not know what's going on, the foot traffic and everything else. We can analyze a lot of the data and start putting that out to the store manager upfront, saying, "This is what XYZ you can do because store X is doing better," right? I'll go back to the call center topic for a second. One thing which we find really useful there is sometimes when you have these call centers, there's a very high turnover rate there. You get a lot of junior guys.
Sure.
They got a lot of experienced call center guys. Where we see AI kind of help really is bridge that gap between them.
Right.
Where a lot of these junior guys who did not know the SOP, who did not know how to kind of operate. Now with the help of AI and with the learnings where they get from the senior guys, we can kind of codify that. You can kind of feed to all these guys to take the real actions, right, so they can service the customer a lot better, right. That's kind of one of the big impact where you can bridge the gap between the junior most salesperson to a very senior salesperson.
Got it. You mentioned the retail store owner. wanted to unpack Point of Sale a little bit. You've had some strong wins there. You know, where are we in the evolution of that business, and how do we think about that opportunity longer term?
Point of Sale is one of the products we're really excited about going into 2026. If you remember last year, we built a sales specialist team around Point of Sale as well as POS and others. We're starting to see the fruits of that labor now in terms of the pipeline and the opportunity that we've got. You know, we've never been disappointed with our win rate. You know, again, 70+ win rate across all the products. It's just about getting more at bats and competing for more. When we look at our pipeline across some of these products like POS and TMS and Supply Chain Planning, it's the biggest and best that we've had going into a year. Really happy about where we are.
Maybe talk about how you're attacking that opportunity. I know there's been some go-to-market changes, partnership efforts, like maybe unpack what you've done on the last year?
Yeah. We, we built a sales specialist team. We, we've changed our partner model, and a big focus on changing the partner model was to really get more specific and prescriptive with our partners about what we expect from them and how they can help us grow and what we can do to help them grow in return. Part of that is in the POS space, if you think about all the POS deals that happen out there, you know, our partners are, you know, Accenture and Deloitte and IBM, et cetera, et cetera. They are aware, as a company, they are aware of every one of those deals that's out there. We want the Manhattan team at those companies to be making sure that they are aware and bringing us into those deals.
You think about all the things that we've done across all the different elements, the regionalization of some of these things has just expanded that opportunity for us.
Maybe just similar question, but on Supply Chain Planning. I know that's a newer product. Where are we in the adoption of that?
Yeah. Supply Chain Planning, we just rolled out in the cloud platform about a year ago. It's our newest product on the cloud platform. I think we've said every quarter that it's moving faster than we had kind of anticipated. I think the most exciting thing about Supply Chain Planning is we've now seen multiple customers become new logo Manhattan customers with Supply Chain Planning. You know, in the beginning, we kind of expected, hey, that's gonna be a logical add-on if you're a warehouse or transportation or order management, you know, add the Supply Chain Planning. When we see new customers come in and start with Supply Chain Planning, that tells us two things.
Number one, we've built a product that can compete head to head against all these other, you know, pure play supply chain planning products. Number two, it tells us they're coming to us because they wanna bring more to us later. You know, they see the value of this platform.
I think we talked about this last year actually. The confidence that you've talked about to say 20%+ growth in cloud, that's well above industry averages that we see. Talk about the visibility that you have. I know we talked about the products, but the confidence that that gives you to say, "Hey, we can grow our cloud revenue 20%.
Yeah. No, I think again, you look at the things that we've done. We started these things in 2025 to make sure that we were set up for this in 2026. You know, put Bob Howell as our Chief Sales Officer so he could standardize some things globally, build out that sales specialist capability across each one of our products globally. We brought in Greg Betz from Microsoft to really get us focused on a conversion program that was... You know, historically, we've said people will convert to the cloud when they're ready. Now we're just making sure that we're having that conversation with every one of our on-prem customers, so they understand the difference between what they have and where they could be-
Mm-hmm.
... also so that they understand how easy it is to make that conversion. Greg and his team are also focused on this renewal program where we make sure that we're maximizing not only the price uplift, but the cross-sell opportunity at the time of renewal. recently, we added a new chief marketing officer who's come in and really helping the team think differently about how we create pipeline and create opportunities, partner with our partners to really get a different level of market awareness across all of our products.
Specifically on the conversion side, like how important do you think this fixed services dynamic can be for customers? Could that be a real catalyst in terms of moving people over to the cloud?
Absolutely. If you think about all of these customers that are on-prem, they have this pattern in their head, right? Every five to 10 years, they do a massive upgrade, and that upgrade is a big project, and it's like open heart surgery, right? It's the last one they did probably ran long, probably was over budget, and they probably still have, you know, feel pain from that process. Going to them and helping them understand that, "Hey, this one is much easier. We know what you're running, we know where you're going. We built automation, we built AI. It can happen fast. It's a low cost.
By the way, it's the last time you'll ever do it because after you do it, you're on version-less software." When we have that kind of conversation, some of these companies that were, you know, trying to make this, you know, forget about this pain and push it off as long as possible, now they're saying, "Okay, let's talk about this. That makes sense.
Well, I wanna expand on that a little bit. Sanjeev, feel free to weigh in. You talk about version-less and not needing to upgrade again, but 80% of the customer, well, 78, I'll keep me honest on the math, are still on premise, right? They need to go through a migration, but what is the value that you can provide them? Not if it's just WMS, but what about OMS and TMS? You're selling them multiple supply chain solutions, so what do you think that you can sell to them over time as they're, you know, again, early in the journey, but the value of the integrated platform?
Yeah, I'll jump in first, and then I'll let you go. Because I think that that's a really important question. When we get our on-prem warehouse customers to convert to the cloud, it immediately opens the opportunity to cross-sell transportation, cross-sell Supply Chain Planning, upsell the AI Packs. All of these cross-sell/upsell opportunities don't exist in the on-prem. Now, I wanna, you know, also say that 55% of what we sold last year was new logo. We've always been a believer that, hey, if we can expand our share, you know, every one of those new logo customers, we're creating those same cross-sell and upsell opportunities. Now we've got a sales force that's built to go do both, which we've never had before.
Yeah, I mean, I'll add, lot of times customer who are still on on-prem, there has been an inertia on moving, and you need some sort of a force multiplier to help them kind of find a reason to move. I think AI would be a pretty big incentive for them to say, "Okay, I wanna move from X to Y, and this is what I will get out of it when I move," right? That's kind of a big, large factor-
Right.
... on how we can overcome that inertia of movement. Once you kind of move, to Eric's point, right, it becomes a lot more easier to kind of use our rest of our products which are already there on the platform.
It maybe just a AI from a different perspective, but would love to understand how you guys are using it internally and what efficiencies you've been able to get from AI.
We've been using AI internally for last two years almost now, right? Almost every function of ours. I'll take our ops, DevOps side of it, right? We've grown our customer base in the last two, three years. Our number of warehouses which have gone live is probably about 2.5x. Our DevOps team is completely flat. We've not grown a headcount there at all, right? A lot of that has come from using AI to kind of manage those processes to make sure that we can continue to keep that, right? We use it for our development. I mean, I talked about code generation. Of course, we kind of wrote our own generator. The remaining portion of it now, we're starting to use a lot more AI in that.
Our customer service organization, same thing, when they get a trouble ticket, they're trying to figure out, "Okay, has this happened before?" AI is kind of helping with that aspect. Services, we talked about time to value. I mean, our services team is using it extensively to figure out how do they reduce that total time it takes to implement the software.
Mm-hmm.
That's a pretty big piece. I would say, I mean, it's pretty broadly used across the company, and we're using more and more.
Our sales team is using it. They're using it to get intel on opportunities, you know, you know, potential customers that we're going after. They're also using it to do better, more applicable demos faster in the cycle, so they can actually show the customers exactly how you're gonna use our software very early in the sales cycle.
We can respond to more RFPs, for example, in the sales team, right? I mean, they're filling 80% of the RFP using this. A human kind of reviews it, but it takes a lot of that mundane task away.
I wanna understand the sales side in terms of staffing and hiring. Do you feel like you're where you need to be to go attack the opportunity in front of you?
Our sales team is massively more efficient today than they were a year ago, and we're still gonna add more because the opportunity is there. The opportunity across all of those products, conversion, new logo, cross-sell, the opportunity is there. We're continuing to invest in sales and marketing.
Maybe just last one to wrap up here, but you guys generate a significant amount of cash. Obviously, there's investment in R&D, but, you know, would love to understand how you're thinking about priorities for deploying that cash.
No, no change there. You know, we've always said, if there were an M&A opportunity that made sense, we wouldn't hesitate to look at it. Again, I think a big part of the, you know, strategic advantage position that we're in right now is because Sanjeev and the team have really stuck to this platform approach. We haven't bought anything and bolted it on and integrated it. If we were to acquire something, we'd have to rewrite it.
Yeah.
We feel like we can write it ourselves faster than that. M&A isn't a big part of our strategy, which means buybacks. You know, big focus on buybacks.
All right, we'll wrap it up there. Everyone, thank you.
Thank you.