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All right. We're going to start with the next session. Next up, pleased to have Savneet Singh, President and CEO of PAR Technologies. Savneeth, thanks for joining us again. It's a pleasure to have you yet again at the conference. Thanks for having me. So before we get into the details, let's level set for the room. Anyone who may be newer to the name, PAR has been on a 40-year-old journey to kind of reinvent themselves from a hardware company to a software company. you know can you give us a snapshot of you know who par is today and what the platform does uh across you know restaurant front of house and back of house um sure par is a platform to run enterprise restaurants and convenience stores we are um uh everything from loyalty and online ordering all the way to point of sale and back office um our platform really sort of starts with plant the flag with point of sail and then we looked up sell you back ofhouse online ordering and loyalty. We've been sort of deep in software for six, seven years now, expanded rapidly. Today, we cover over 100,000 restaurants and 25,000 convenience stores. Got it. Okay. And then on second quarter numbers, you reported last month, you raised full year on both the top and bottom line. And this is, you know, it's not, you haven't been giving guidance for a while, so I think that's notable. What stood out to you in the quarter? Anything you'd like the script to focus on? You know, I think, so it's our second, we started guidance this year, so this is our second time giving guidance. I think probably the biggest takeaway is, you know, we continue to sort of significantly outperform our EBITDA targets, and I think I hope that continues for some time. So I think there's a really strong operating leverage story here alongside really durable growth. So I think probably the biggest takeaway was that we are over-earning, and I don't think it's over-earning. I think we're earning into a continual growth. So I thank every dollar of future revenue will come out at a substantially higher margin than when we started. And so I think that is really a direct result of a platform strategy, whereas when we're now selling two, three, four products per customer, the increment in the margin per customer is much, much higher than it was in the past. And soI think there's a little bit of underappreciation of how much that is flowing through the bottom line. And the second thing that's interesting to take away is, you know, we've crossed over 20,000 restaurants that now have our, I'm sorry, 20, 000 sites that have our intelligence platform on it now. And I think that's really exciting for us because, you know, we're selling to enterprises. It's not like a tool we can just flip on and say, surprise, you have it. We have to get approval. We got to get it signed up. And I thinks it gets us really excited about the potential future monetization of what we're doing there. Yeah, I want to come back to that in a second. but maybe talk for a second about the decision to give guidance. What was the thought process? You know, what changed in terms of visibility? And then secondly, how are you thinking about the philosophy around guidance go forward about how you set the bar and, you know, evaluate over the course of the year? Yeah, you Know, I think guidance for us was probably twofold. One, you Now, when we took over the company, we were like less than 10 million of error. And we used to get asked to give guidelines. And I'm like, you Know, how many, You Know, Series A companies give guidance? You know, we just happened to be public. And so I think it was always hard. And, you know, I think when we were building up our platform, part through acquisition, part organically, you know, it was very hard to kind of give guidance that I think was instructive. I think we got to a point now where the business is mature enough where we felt comfortable giving guidance. And I think the second part was we, you now, had a lot of visibility coming this year. And so, you knew, we didn't want to come out with guidance and be wrong. And so we felt like we had a lot of visibility this year and thought it was a good time to kick things off. Got it. Okay, that makes sense. And just philosophy going forward on how you set that bar? Yeah, I mean, I think we try to sort of put a bar we can hit and hopefully exceed. The first two quarters we beat pretty substantially. I think will eventually narrow it in to be, I don't think we want to beat by that much all the time, but I think our goal is to kind of put numbers we can achieve and, you know, give, like, reasonable expectations. Yeah, got it. Okay. All right, so let's talk a little about AI and how that's impacting the business. Can you talk through how AI is actually changing how PAR operates internally and how you're kind of separating, like structural costs out, cost takeouts from what I think you called, like AI washing cost savings programs? Yeah, you Know, I think we went about AI, really like department-by-department, job-by job. And I think it took a little bit longer, but I think we're going to be able to do that. I think that really worked in our favor. So as we exclude the one sort of set of assets that we acquired in Q1 of this year, our organic op-ex is down something like $15 or $20 million. And a substantial portion of that came from cost takeouts leveraging AI. I think an example is probably helpful. Our finance department today is down 25%, maybe 30% from where it started this year. And our goal is to take it down to 40% by Q1 next year. And so we've been able to take out a huge portion of our finance costs because we've been ableto leverage AI in areas that we were manually doing stuff. So a couple of good examples are things like internal audit, where an agent can pull sort things that look fishy or needs to reconcile stuff, you know, areas of billing where we were doing a ton of stuff manually, collections, you know, really aggressively put AI to work, and it's dramatically helped us cut costs. Same thing within HR. You know, all the queries that you send to HR, we've now made those agentic. Within our operations, you know, our hardware team now has, you know, something called HeyPAR, where, like, literally any question they have about a product, whether it's from 1985 or 1995 or now, they're able to query it. And so that allows us to cut the team down but also get rid of all this old software we had. We got rid of Smartsheets with some of our demand planning because we were able to use a tool we built on Cloud. And so I think we've been constantly going to function by function to see what we can potentially automate away. Got it. Makes sense. And then just on the product side, you mentioned the 20,000 live sites on Par Intelligence. Maybe talk about that product, you know, what it actually is, what are customers doing with it today, and how you think about kind of roadmap for that product. Yeah, so it's really exciting for us. You know, Power Intelligence is the single dashboard for all of your Power products and hopefully your third-party products as well. But what I think is unique about it is, you Know, today what we're doing is what I expect every company in the world will do in software, which is it's like chat GPT for your restaurant. You can say, what are today's sales like? How did they compare last week, last year? You know, does that promotion work? What store is working? How's my inventory looking? Your ability to just sort of run reports, you know, and that is actually really valuable today, and we're not charging for that. The idea is, hey, let's just, you know, we call it assist. We have a really good example where one of our customers shows a screenshot where his CEO had asked, you know, can you tell me the percentage of transactions between 0 and 10, 10 and 20, 20 and 30? And normally, he's like, listen, I would have to download some stuff, run some stuff. You know? Because he wanted to see how that trended over the last period of time. It's actually kind of complicated, right, because you're like, okay, how did that bucket of zero to ten compare to last year or whatever? And he literally just copied it, put it into our assist, and sent it to the CEO within like 10 minutes or whatever. And so that we call assist. The next step in our evolution is advise, which is instead of you prompting it, it starts prompting you. And so it says, hey, Will, did you know that, you know, drive-thru sales are down, you know, are, you're sorry, the drive-through is backed up 30 seconds, you know, FYI. You know, it's sort of giving you, hey there's too much inventory, hey this labor schedule isn't going to be working for you. And so, it is actually predicting stuff for you, just for you to go take actions. So, more valuable new prompting there. And then our third, our next third iteration of the product, which is coming out, you know, early next year, is the ability to take action. And so, you Know, in that example about the drive-thru, you know, hey, the drive through is backed up 30 seconds. Do you want to shut off DoorDash so that the store can funnel the drive through faster? And, you know, you press the button and it takes the action. And the idea is that over time, we just automate that. So, hey. Anytime the drive through is backed up by 30 seconds, you shut off DoorDASH. so we can add staff there or whatever it may be. And so when we get to that last point where we're going to take actions to help you optimize your store where you literally don't have to do anything but press a button, that's when we tend to start monetizing it. So our goal is to get 50,000 stores on assist by the end of this year or they have this beautiful experience to kind of pull the data, pull the information, get a bunch of customers on sort of advice, and then we'll just start monetize it. Yeah, okay, and talk about where you are currently and just when you get to that advised state, how long does that take and what should we be thinking about for a timeline to monetization? So our goal is by the end of this year to have 50,000 stores on assist. This is our first version where they're using it pretty extensively. And then through 27, our goal's then to get to this last point of action. So hopefully we'll have real revenues in 2027 that we can tie back to this product. And we think over time, this product becomes how you interact with us for everything. There's no more point-of-sale log in here, back up. It's all just in this one place. And that's really the major vision that we're pushing towards. And how does this, you know, we've seen similar products across our coverage, most of them in the SMB space. What's different about rolling out AI-enabled products into the enterprise ecosystem? You know, you've got corporate approvals, cyber reviews, longer cycles. I would imagine, though, that they focus on finding efficiencies and running businesses more efficiently, that there's more of a focus on that in some of the bigger enterprise organizations? It's wildly different. Like, I think, you know, when I look at the SMB, a lot of the SMBAI stuff is like, hey, I'm going to grow your sales, you know, 10% to 40%. You know, imagine going to, like, McDonald's and say, I want to use AI to increase your sales 10% to 40%. You just sound silly. It's just a, you know, it's not, you know, no one's going to go get a, you know. You know. You know how many people can get a multi-thousand store restaurant and grow their sales by 40%. And so, you know, they are, and that just gives you perspective, like how different the SMB is from the enterprise. Because, you know, SMB will say, I can grow myself 25% by using AI. Whereas, you know, that's just not reasonable to assume in any large business. The other part of it is kind of what you talked about, which is, okay, so what can you figure out? And in the enterprise, where there's massive focuses on the back of house, how do I optimize my inventory, my labor, my schedule, food costs, all that. And then it's on the loyalty side, which ist, how do I segment it? So, how I would actually say Will is a father of two that, you know, every week this week, you know, comes home super exhausted and needs like a, you know, Big Mac or whatever. How do I segment down to you as an individual? And so those are the two areas you see in the enterprise, whereas the SMB is all about at the moment like customer acquisition and, you know, choosing your business pretty quickly. Structurally, it's also very different where, you When we go sell something to the enterprise, we've got to actually, you know, convince the CIO to use the product. We've got it tested with a bunch of the brands and the stores, all the cyber stuff. You know, it's a pretty robust process. But once you go through that, you Know, it is a huge moat between you and the next person because, you Now, how many times do you want to go through it again and again and again? And so, you You know what I mean? I think us being first is really important. And then how does the AI strategy extend to the C-store side? So the C-Store side, we're actually a little bit further ahead. We're in 15,000 C-stores already leveraging Parassist, and so we're seeing tremendous use cases. As an example, one of our customers, our first customer actually, the beta customer, was actually able to use Parassit to realize they had, I think, a million-dollar ad buy being funded by one of their suppliers that they didn't use. And so you think about, okay, a million-dollar ad buy, what's your cost of production? You know, that's a huge amount of, you know, we just paid for the product for years that way. And so they're using it to predominantly engage on the marketing side. They're trying to figure out how do I segment, how do i target? And so we've got a lot of traction there. We're going to test out a ton of other stuff. So as an example, you Know, we're testing with a customer, how do they use voice to interact with parses? So instead of you typing it, can it be in the headset, and you can say, hey, how are we looking in the kitchen, or whatever, of a C-Store? And so the C-STORE, we've had a lot more engagement and a lot faster. Yeah. Why is that? Why are they so much more willing to engage? I think it's our standing in the category. We are the very dominant loyalty provider, but we've created a ton of value back to our customers. And so when we bring them something, they don't really have a strong competitive alternative, and then we've kind of got this relationship. Whereas in restaurant, we've done a great job, but there's competitive alternatives. They're being called on all the time. You know, in C-Store, you don't really have a lot of nearly the innovation or VC dollars that have flown into it like restaurant has. Got it. Okay. All right. Let's pivot over to Bridge. You closed earlier on this acquisition. Maybe you could provide an overview of the deal and the acquisition and how it fits into the Better Together thesis. Yeah, we closed on Bridge in Q1 of this year. bridge is is an ID our solution you know essentially it's a tool that allows you identify who a guest is whether they're in your loyalty program or not and so it sort of you know takes takes matching data and figures out okay that's well he lives in the zip code he's got this demographic data and and then obviously over time the goal is to sort of target those customers it is an incredibly powerful tool that historically you know was sold to the you know largest you you know, Walmart down, like it is the biggest, the biggest. And, and it was, Bridge was originally acquired for, you know $350 million in 2021 by a company called Cardlytics. You know, first post earn out, Cardlyics paid almost half a billion dollars for the business. And then, you know, we bought it for like $20 million in Q1. And so we thought we got a steal. And the real The idea was can we take this bridge product and combine it with our loyalty solutions so we go to our customers and say, hey, not only do we have all your loyalty customers and every transaction that are done and how they think about you, we have your non-loyal guests alongside that so we can then find ways to bring those guests to be loyal or vice versa, but also figure out how much of our spend is happening outside. So if Will is a loyal customer of XYZ Restaurant, how much is he spending on ABC Restaurant and everywhere else? And so it is a really, really fascinating tool for our customers to demo because they're like, oh, crap, I don't have any of this information. And so we have a ton of interest. We signed our largest restaurant loyalty customer onto it just a couple months after we bought it. We have a pretty strong pipeline of new deals coming through. So Bridges is pretty exciting. and I think will be the crux of our AI monetization going forward in that we can create really unique outcomes with stuff they couldn't do before. And what's the sales process or upsell motion look like on that? So it's very much pushed in conjunction with those that have our loyalty products. So when you're selling loyalty, it's so much about data, data, data, and an incredibly powerful data product I didn't have before. It's also very unique and hard to get to. And so we sort of sell it within that core buyer persona. Have you talked about pricing relative to the base of what used to be Punch? We haven't yet. And pricing does vary pretty significantly, and we're going to narrow in on this. But, you know, you should expect, you Know, a doubling of ARR and a loyalty customer when we turn this on. But it does vary depending on what we find. All right. Let's talk Papa John's. This was a major win for this year. Can you talk just a little bit about how that came together? how competitive was the process, and what role did the Burger King win as a reference customer play in achieving that outcome? Papa John's is a big deal for us for a couple reasons. One, it's our first pizza chain, so we've never done pizza before. And pizza is a little different than our traditional QSR business in that you've got modifiers, you've got this pizza going through the oven stuff that Domino's pioneered, and it's heavily delivery, heavily third party, heavy promotional base. So there are core product differentiators versus quick service and fast casual. So it was a big deal for us to move into a new vertical, kind of like an adjacent vertical, and then do it in super fast time. And I think the core reason we won the deal is that Papa John's is, from a tech perspective, is run by a really innovative team that came out of Domino's. It was the team that sort of did a lot of the really cool stuff that Domino'S is known for. And so they want to be viewed as tech forward. They want to being viewed as cutting edge. And so, they wanted a partner and a vendor that, like, matched their values and their goals. And so I think they took a huge leap of faith on us because we've never done what they're looking for them to do. So they're literally betting on us to do something we've ever done before. But I think that they felt it from our culture. They felt it for our roadmap. They saw the results. And then I do think a huge part of it was the success we had at Burger King gave them massive confidence we could scale and handle the volumes and quantity of stores that they have today. So I think that was a huge, huge part of it. So then I guess talk about pizza as a new vertical. You talked about how, you know, it's first major win in that category. Any changes to the product that, you Know, will come from being in that vertical? Yeah, absolutely. I mean, we've had to build a lot of that pizza functionality for Papa John's. But, you KNOW, what we've been lucky about is then we were able to go monetize that to other customers. So in Q2, we announced we want a business called Pizza Factory. And then we want A3 chain, a small chain after that. And so we've been making great progress. And pizza is kind of interesting in that there isn't an enterprise vendor that has serviced it before. So most of these pizza chains have actually custom-built software from a decade or sometimes decades ago that they've been trying to figure out how to work. And so there's an incredible amount of excitement in the category because no one's ever gone after that category before. And so we think it could be a nice place for us to expand. You know, we've got three customers on a standing start. And a lot of that functionality we can now use over and over again. And, you know, I think that a lot if it, too, is just stuff where I suspect – pizza's always been an innovator in far as, you know, first to delivery, first do DoorDash, first delivery. There will probably be stuff that comes out of that that are relevant to the rest of our base over time. During the Burger King process, there was a period of upsell where you ended up winning additional products. Do you see similar opportunities here, and what can make sense over time? Yes, and we already did. So we sold them on two products at the time we won the deal. So, again, I think that was because they saw what happened over there and said, okay, why don't we do that now? So that was kind of exciting because we were able to launch with two products, not one, and not have to, you know, pause and restart. And so, you Know, I think that they saw the value add there. Then it also started becoming the norm. In Q2, every single deal we did was multi-product, literally every deal. And then, you Now, the prior four quarters or three or four quarters, it's sort of been 70%, 80% of our deals were multi-product. And so I think we've been able to convince more and more customers to go that way. and I absolutely think it's tied to the success of us that working from these bigger, more complex brands. And just remind us where you are in the implementation of that. I think you sized it in the past as kind of like mid-teens, millions of ARR once it's fully rolled out. Papa John's, yeah. And we hopefully kick off the very end of this year, but it's really majorly a 27 event for us. Got it. Do you think you can get it done in 27? That's the hope. That's hope, got it. Okay. Similar question on Burger King. I know that one's farther along. Where are you in the Burger King rollout? You've been running north of 400 stores a month. How should we think about the remaining contribution into next year? I think we'd be pretty much done by the end of this year. I don't think there'll be a small contribution for next year, maybe some laggards. But, you know, for the most part, it'll be done. And so 27 will be a lot more about upselling the back office product and getting that going in the rest of the chain. So it's been super focused, you know, super successful, ahead of schedule. You know, we suspect that no one's ever launched this many sites in a single year. So, you now, it's gone really, really well. Yeah, that's great. I know there's been a lot of conversation around just the market opportunity of other brands, you know, like the pizza industry that ran a lot in-house software and are looking to modernize. We've been talking a lot about potential tier one RFPs out there. what's the level of confidence and PAR's positioning in some of those processes and any updates you can share? We continue to make progress. We're careful not to give updates on stuff that hasn't announced or signed yet given our customers it's kind of their private info. But the volume of RFPs has increased pretty significantly in the last 12 months in our business. I think we are clearly in a replacement cycle of point of sale at least. And so I think we should, given our win rates, we should continue to see, hopefully, above-average growth, given that just the quantity of RFPs has increased. I believe the only department at our company that has grown headcount has been sales engineers, which are folks that do demos and architect around that. We're just seeing a lot of RFP volume there, too. So I think we continue to make inroads into these big, big deals. And as I said, you know, our guidance, our business is, you know, a guidance isn't too many that if it happens, it's just great upside for us to have. What is the process of pitching and winning such a large customer like that look like relative to your standard sales process? Man, the big ones are just, they're very, it is just impossible to sort of like say the one is like this or not. You know, some firms run a super strict RFP process where they bring in Accenture, Deloitte, or something like that and say, you know, blind RFP response. We don't, you don't talk to us. Just, just walk through the consultant. Other folks will, you Know, sort of date you for a year or two and then sort of say, okay, let's do a quick abbreviated thing. Other times, you Now, honestly, with, with Burger King and Papa John's, you Knew, we were the last of the party, but, you Know, we won those very quickly because I think they'd kind of gone deep on other vendors and just were like, this is not going to work and then we came in and solved all their problems very quickly. So, unfortunately, it's not there. But that's, you know, there's a very, again, it's a small group of people that are in that, like, very, very super, super large brands, whereas our traditional process is, you're obviously have account coverage across every restaurant chain in America, but by the time you get that RFP, it starts to finish relatively smooth. So, just zooming out, I mean, there is a lot of, I think there has been a lot focus on, particularly early in the year, that AI may make companies manage more of their own software in-house. And so it's interesting you're saying that you're seeing a lot more RFPs coming to market, people looking to move to out-of-house vendors. So what is the market like right now for some of these big opportunities? Are you seeing an acceleration in people looking to do kind of refreshes of their tech stack? And then how do you think AI plays into those decisions? Well, I'll say that 99% of restaurant chains do not have their own tech stack now. So it's not so much a move to external. It's always been external. There are a couple, you know, McDonald's, Subway, Yum. There's a handful that have done stuff themselves. But everyone else has bought. And so I just think it's a continuation of that bought. And I think even more so, what we're seeing is some of these firms that have built their own now look at AI as a way for them to get off their own. Where I think a lot of them are like, man, we're going to be stuck on our own clunky homegrown thing with AI. It's like, okay, now we can actually get off the thing we built that's flexible as resources. And so I'm not seeing any customer come to us and say, I want to go build a point-of-sale system. I don't think that's going to happen. And if you think about it, if I'm, you know, almost all large restaurant brands are franchised. If I'm that franchisor, I'm Not sure I want To build, like, the payment engine, the transaction engine, the point-off-sales system to my franchisee. It's just going to be a massive point of friction for saving, you Know, how much? Point-of sale, you're paying $200 a month. It's like, is the ROI really worth the headache of giving your franchisees another thing to complain to you about? And so I'm not sure there's an ROI there, given that. And I've always said this, but, you know, to me it's like the equivalent of us saying, I want to go build my own CRM system because I don't want to use whatever gong or Salesforce.com or whatever we've developed. Like, why would I ever want to distract our team to build the best CRM systems? Right. You'd only do that if you felt there was a massive, you now, competitive advantage. And, you know, I don't think that exists in, you know, or if you can build the best product for your store today, I doubt that lasts because technology changes, integrations change, all of a sudden AI comes and you're like, I've got to rebuild it. I just don't want to be in that business. So the main driver of the movement of this aggressive sort of growth in our fees, I think, is really just down to the same exact stuff, which is, holy crap, our customers are more digital. We've got to meet them where they are. We've Got to manage our operations more dynamically because all of a sudden I got to deliver, I got to have Uber Eats, got to have pickup, I've got to be available on all these channels all these times, I'm going to manage labor, and I'm doing it from the exact same four walls that I did 20 years ago. And the only way to solve that is with technology. Yeah. Okay. Let's maybe pivot and talk about the competitive landscape. I mean, you sit behind, or I guess between, a lot of legacy enterprise vendors, Oracle, Micros, NCR, Global Payments. there's also a lot of SMB players who are trying to move up market you know what's kind of stayed the same what's changed over time on the competitive landscape the biggest players in enterprise are ncr oracle and global um that hasn't changed i think they still have the most market share you know we you know most of the customers we get are from those three or some of their legacy provider um and i think that will continue for for a long long time i don't think this is a priority business for any of them and for the one that is a prior business i think they just have too heavy of a product to to fix to really be competitive so i just i just think it's just it's hard even if they wanted to change you're talking about products that are 15 20 years old you know millions of lines of code like that's really hard to to do it and even if you want to do it it's like you know the innovator's dilemma like how do you tell your customers that tell your employees that like i think it's tough um you know from the you know uh competitors from outside the enterprise. There's always been SMB people that wanted to come up market. It's never really worked successfully. I think it's really hard to take an SMB product and make it enterprise. I don't know if there's a good example. I don' t know if I've ever seen that. There is Intuit and there is SAP. There is an SMV product and usually an enterprise product. I think it's really hard to make that the same product. You've got to almost completely change your stripes to go to that market. Specifically, we have incredible respect for Toast. you know I love those guys I love those products but I think the enterprise is still you know not I just don't think there's enough time and opportunity to make it worth their their time and so at some point it's just like you know economic rationalization comes in and it's like what are we doing here I think you know there's a few startups here and there but honestly not not a ton has changed you know since we probably lost the last year yeah does having more people at least looking at the space does that change any of the dynamics and competitive situations not really you know it's funny we you know it's been four plus almost exactly four years since gpt to 2.8 came out we have not seen one new company in an rfp since that time so whether it's loyalty online ordering point of sale really not one and so i just we have not seen like tremendous change on pricing or you know sales cycles it's it's only thing that changes is the quantity of rfps is increased kind of um one thing i want to talk about you know payments was something the company has been investing in i think more so for the table service uh part of the business but probably applicable applicable across the business any updates on where that product stands and how you're thinking about roadmap yeah payments is still less than 10 percent of our our net revenues but you know it's growing uh you know when we tell the enterprise it's tough to uh always have payments because they've got their own deals with you know Fiserv or whoever. But where I'm super excited about payments actually is leveraging payments in a CDP system like we've talked about. So how do I take that, get you on our payment rails, then I can take that data, put it into our CDP and give you incredibly high fidelity information about Will and Lance so that I can target the hell out of you and make you a loyal customer. And so a lot of times I think about how do we not sell it as payments, but sell it as, you know, a robust CDP system. And that's where I think we'll do more and more with these larger brands. And they look at it as, I'm not getting a payments product, I'm getting something else out of it. The place where I Think We See Pure Payments growth is actually in online ordering. So one of the, you Know, exciting parts of our business is, you know, we've kind of built an online ordering product that's going after our base customers. You know, this year, 2026, it's got a 50% win rate. and that's nuts for us. Every quarter we're winning five to six logos. About half of those come from the big legacy provider and every single one of those deals has payments associated to it. And so that will be a nice driver because card-not-present transactions are very lucrative and I think because all those deals go hand-in-hand, the ARPU is very, very high. So I think we'll continue to have good, stable growth in payments but I think the online side is actually where we're going to have the opportunity to do more. And then in the in-store, can we build out the CDP idea? You know, we'll see where that is in the year from now. Got it. Makes sense. Maybe a couple more financial-oriented questions. You've roughly doubled EBITDA year over year. As we talked about, you raised the guide. How are you thinking about margin expansion and, you know, the trajectory towards a kind of rule of 40 model? Yeah, I mean, I think we've said, you know, our goal was to go to kind of double EBITD and double it again. And so, you Last year we did 24, 25. This year we guided, I guess now we're guiding above that. So we'll hopefully do that again this year, and then we think there's a potential path to do it again next year. A lot of that is coming from the stuff we talked about, continued growth and then holding OpEx and taking out OpEx. We're obviously ahead of our expectations on EBITDA, and I think a lot of some of this AI work just became more lucrative to us than we expected, faster than we suspected. And so, you know, to me, I don't think it takes a gigantic leap of faith to see how we can get to a really robust, give you that number there. And then I think it's just about growth and, you Know, getting us closer and closer to that rule of 40. And then the other one I had was on just on capital allocation. You've got a buyback authorization. You've done a lot of M&A historically. You've been working on the capital structure to turn that out. you know how are you thinking about you know capital return m&a uh versus re-investing in the business i think we do not need uh to use cash on the balance sheet to reinvest in the business is self-sustaining and and you know as an operating leverage is growing so you know we're going to sending out more cash than we need and you like today i mean i think capital allocation is a dynamic question it's not static you know and so i think today i would suspect the best use of our best return on our capital is our own shares. But, you know, that can change. If a great, unique acquisition comes up, like Bridge, I would do Bridge instead of buy and make our shares because we think Bridge will unlock a lot more over time. So I think it's just where you are at the time and what generates the highest return. But we still don't want to be sitting on it because I think, you now, our shares would provide a really substantial return, so we'd probably look to do something there. Got it, okay. All right, just in the last minute or two here, Or how are you thinking about, you know, big picture, what is next for the company, specifically for PAR of the next 12 to 18 months? For us, it's pretty simple. We want to drive the profitability we talked about and deliver that return to our shareholders and, you Know, become a cash flow story. And then we want to prove the PAR intelligence story. We've got to prove that AI is a growth accelerator for us. You know, I think that if we can do that, I Think we'll have a multiple re-rating that, You know? Hopefully reward the patients of what's going on now. But it's Pretty simple. We've got to drive super high ROI on our AI spend, and then we've got it delivered on the cash flow numbers. All right. Well, Sabneet, thanks for joining us today. Thanks, Will. Really enjoyed the conversation.