Well, good morning, everybody. Thank you for being here. Thank you for those of you listening online. Good afternoon to those of you overseas. My name is Lorne Gorber. I'm just quickly gonna introduce our day. We have this great series, two great speakers this morning. We'll wrap up the morning after the two speakers with a Q&A. That'll include Greg, Shaun Maine, Avjit as well. So really happy to have you all here. Before I turn it over to Greg, just to kick things off, famous slide. The disclaimer, everything we say about the past is true. Everything we say about the future is up to you to decide and evaluate. So maybe without further ado, we're a couple of minutes behind here already, so I'll turn the podium over to Greg Berard, President, Global CEO. All right. Am I up? All right. Good morning, everyone. Welcome to our first Coffee and Converge series. We appreciate you taking the time to be here. I know everybody is busy. We're excited for today. I won't talk long. I know you guys are here to listen to Chris and Shaun really talk about what we do with our clients. There we go. What we do with our clients and the high-value solutions we're driving on a day-to-day basis. For those that don't know me, my name's Greg Berard, Global President and CEO here at Converge. Started with Converge back in 2018. Was the fifth acquisition, and now 35 later, I'm in this role and excited about what's to come for Converge in our future. I just wanna do quick introductions for the two presenters. So Shaun Bertrand, here on the right, runs our cybersecurity practice. He will be the second presenter, after Chris Foster, who's our CTO of our advanced analytics and artificial intelligence practice. So excited to have them here today, both from recent acquisitions. Shaun joined us in March of 2021 through the CBI acquisition, and Chris joined us in October of 2022 through the Newcomp acquisition, which was the fourth analytics company we acquired. A lot of people have already asked me, are we doing these monthly? Are we gonna do these quarterly? We don't know yet. We're gonna do some surveys and get some feedback from you guys after this, and then we'll make some adjustments to the agenda, and we'll focus on what you wanna hear about. So more to come on that. We'll get through today and then, let you guys decide how often you wanna see us and whether we do them in person or remote. I'm gonna spend a couple of minutes talking about the Converge strategy, and I think my first message to everybody in the room is our strategy has not changed that much, right? We've been acquisitive, we've made 35 acquisitions, but every time we acquired a company, our strategy was to leverage those clients and cross-sell into those accounts to gain more wallet share and drive more value with those customers. That hasn't changed. The only thing that's changed right now is we're not acquiring, and we're focused on organic growth in a couple of different ways: bringing in more sellers, driving more solutions, building new partnerships, building new solutions, and continuing to have those high-value conversations with our clients. In terms of the transformation, right, we've seen it happen over the last couple of years. We're continuing to see it happen. We're continuing to have different conversations with the clients we acquired, and you'll hear a lot about that today. You'll hear about what we're really doing around AI. You'll hear about what cybersecurity has brought to the Converge company and what conversations we're having with our clients around cyber, and how that aligns and ties to every other conversation we're having around application modernization, around cloud platforms. There's a lot you'll hear about today, and the overall strategy of us at the end of the day, being the end-to-end solution provider for our clients. That's what makes us unique in the marketplace. There's no one out there that can do what we do and go as deep as we can across all those practices. A couple of points I wanna make on this slide. You've seen this slide, I'm sure, many times, but I think it's important to reiterate the structure we've built, both from a sales perspective and practice perspective, is what makes us different. When we acquire companies, we have integrated, specifically in North America, every sales resource into the region where they belong. We do that to ensure they maintain that client relationship. They're still the face to the client, but they can tap into everything we do as an organization. They can leverage folks like Chris and Shaun to go have those high-value conversations, and that's important. It makes us different in the marketplace. The second piece is on the right-hand side of the slide here. The amount of technical resources and the amount of partnerships we have allows us to be that end-to-end solution provider for our clients, right? We can go in there and have conversations and bring in the thought leaders and the technical resources that can truly have a thought leadership conversation. The sellers can tap into all of that across North America, and that's been very, very key. The other comment I'll make is around the partner relationships. We have 10, what we call our strategic partners, but that's at a global Converge perspective. Within each practice, and Chris and Shaun will talk more about that today, we have other strategic partners that we're partnering with on a day in and day out basis. And that's where we get into the technical solutions and capabilities that we bring to the table. When you think about this structure, and we've talked a lot about it, and it's evolved, right? We launched the practice structure in February of 2020, right before COVID hit. But we've continued to make investments in these areas. We've continued to acquire companies to make sure that we can go deep and wide with our clients and have those conversations. We've continued to invest organically in technical resources to support the sellers. When we talk about regional presence and regional capabilities. Our ability to put solution architects on the front end of a sales cycle in region with our account execs, so they're in front of our customers, is a game changer for us. The other piece is, when we talk about integration, I think I've already had two questions already on ERP today. When we talk about integration from a sales and services perspective, every technical resource in North America now resides in one of these practice areas. They're no longer part of the companies we've acquired. So from a people integration perspective in North America, sales is in the regions they belong, technical resources are in the practices where they belong, and that helps us align with our clients, it helps us align with our vendors so that we can have that thought leadership conversation. The other comment I'll make on this slide is around partnerships. If I would've showed you this slide in 2020, and we have a different logo slide on what partners that we go to market with on a day in and day out basis, that's evolved over time, right? When you talk about analytics and AI, we wouldn't have shown Snowflake three years ago. We wouldn't have shown Tableau or Alteryx. That's evolved. Why? Because we wanna stay at the forefront of the, the IT landscape and make sure that we're talking to our customers about what's important to them and what's important moving forward. You know, Shaun will talk about Snowflake and Okta and other partnerships that we've developed based on the CBI acquisition in March of 2021. The key for us is to be vendor agnostic and client-centric. We wanna be able to make sure we understand what our clients want to do, and we can build the right solution that makes sense for them, and that's gonna be key, and you'll hear about some of that today. Two other points on this slide, and then I'll turn it over to the smart guys in the room. When we talk about AIM, you've heard us all talk about assess, implement, and manage. Each practice area will continue to evolve and make sure they have the right partners, the right solutions, and the right offerings that we can take to our customers to ensure we're on the front end of the sales cycle, helping them understand what they really want to accomplish, and then we have the skills internally to implement those technologies and manage it long term. That's a transformation. It's not gonna happen overnight. It's continuing to evolve, we're continuing to build new offerings, and we'll get there. The last piece, which is critically important for us, is as we've built up this foundation, our ability to bring thought leaders from across each of the practices is what our differentiator is. When you can put Shaun and Chris together in front of a customer and talk about how they wanna build AI applications and wrap security around it, having one partner to do that is what our clients want. That's changed over the last three-five years. You've seen a lot of consolidation happen in the IT marketplace. They want one partner that they can trust, that they can rely on, and that can build them a true solution end to end, and that's our goal as an organization. I know standing up here today, we have the platform and the resources to be that end-to-end solution provider for our clients. With that being said, I wanna introduce Chris, our CTO of our advanced analytics and AI practice, and have him talk about some real-world examples. Thanks again for the time today. Chris? Thank you. Thanks for having me up. Can everybody hear me? If it's not on, I'll yell. So, yes, I'm Chris. I'm based in Calgary, and like Greg said, I'm the CTO of our AI and analytics practice. That means I get to talk to our vendors and decide where we're going to invest our time as far as how we go to market with who we hire, how we partner with those vendors, how they like to work with us. And, it's fun. I get to see all of our deployments across North America and decide what do we focus on. Now, when they asked me to speak today, I wasn't actually really sure what to talk about. There's not a whole lot going on in the world of AI and analytics, right? Obviously, I'm kidding. It's wild, and, you know, to be in this role and have to stay on top of everything that's happening daily, hourly, the developments that are being made is just crazy. A lot of the discourse out there is that this stuff is scary or it's going to save the world. So somewhere in between there lies the truth, and that's what I hope to go through with you guys today, help you understand, where are we spending our time, where are we investing, where are we winning, where are we learning? But ultimately, when you look at the market, everybody is a little bit scared, and I think there's a lot of discourse out there that says, "Just shut down AI," and that is not the case, and I'll explain why that's not our perspective. If you follow this, you guys probably know about this letter. This was signed by, I guess, almost 35,000 AI researchers and scientists now, that basically says, "We need to pause development. This stuff is moving too fast. It's dangerous. We don't have enough governance around it. We can't control it." They're kind of treating it like a nuclear weapon. And so, is everybody familiar? Does anybody know this name on the bottom right-hand corner here? I'll know who's a nerd. Okay. If you think of a Venn diagram of a philosopher and a computer science kind of guy, he's kind of the forefront of all of the AI discourse. Basically, he said, "It's not likely that this stuff is going to kill us. It's the most likely outcome if we just continue on the path that we're on." He wouldn't sign this letter. He said it wasn't restrictive enough. So this is the world that we're operating in right now, and I'm gonna spend the next 20 minutes helping you understand where the real business opportunity is in this. Is it ChatGPT? Sure, that's part of it. Has AI been around since the 1950s? Definitely. And so this isn't new. Just the language around it is new, i t has exploded, though, and this is what we're dealing with every day. So in my job, it's too small, and I made a point, so you can't read this. But these are all the AI vendors out there, and this is what we have to stay on top of, and this changes every day, right? They bubble together, some of them grow, some of them disappear. And so where do we place our bets? And that's not just a Converge question. That all our clients are having to deal with this as well, right? And so, you know, we're spending a lot of our time just being myth busters and saying, "Okay, let's cut through all the LinkedIn posts about how this is the best and newest and greatest, and we do something nobody else does." And this is what I spend my day doing, is, is going through this so that they don't have to. When we talk to our clients, there's a couple of themes that emerge. I'm gonna try and go from here to something a little bit more focused here. There's a couple of trends that emerge. This is really where we're spending most of our time. In fact, it's really in these four categories. So designing for AI, this is relatively new. This design thinking concept of how does AI actually fit into the real world? When I put this into, you know, my dad's hands, what happens? How does their behavior change, right? How do we ensure that whatever decision we're telling him to make, if we're telling him to turn left, how do we know that that, you know, is going to lead him somewhere safe? And so we sit with our clients, and we do design thinking sessions. We sit with them and say, "Okay, if you infuse AI into your HR application, what does that actually mean culturally? How do we need to train people? How is this gonna integrate with what they're used to doing?" We talk about synthetic data. Okay, this is where large language models and generative AI live. We've actually been synthesizing data for a long time, right? So if we need to generate our own test data, we need to generate an image or a forecast or something, we're using historical things that we've trained a model on to generate something into the future, right? But now that we have so much computing power at our disposal, we can generate a lot faster. That's all ChatGPT is, right? That's all large language models are. All they're good at doing is forecasting the next word in a sentence. That's it, right? That's as powerful as these things get. Digital twins. Anybody familiar with this term? Yeah, especially if you. Oh, there we go. Especially if you live in the manufacturing space, right? So instead of doing, like, destructive or non-destructive testing on a turbine, for example, we create a digital twin of that physical entity, and we can perform tests on it, right? We've collected enough data off of the 150 sensors that sit on a piece of equipment, where we know what happens when conditions change, if vibrations increase or temperature goes up, and we can test things in the digital world, as opposed to doing it in the real world. All of you have a digital twin as well. You know this because anytime you go on Instagram or, you know, you see an ad, they follow you. They know your profile. Google Maps knows so much about you that they can actually draw a heat map of the path that you're going to take on any given day. We're predictable creatures, right? So each of us have our own digital twin. And optimization, this is something that we've been using AI and just analytics for in general, right? This is linear algebra, so saying we're gonna optimize for some specific outcome, whether that's safety or production or throughput. But again, now that we have so much computing power, we can optimize in real time. So this is where we're spending a lot of time speaking with our, our clients about, and that puts us in this role where we're not just AI evangelists or developers or coders. We actually sit with them, and we close the doors and put the blinds down, and they say, "Okay, what is this really? How are we actually going to use it?" And so we end up in this trusted advisor role, and we're thinking a lot about that because we end up spending our time with not just the technical team, in fact, it's rarely the technical team, right? Use cases for analytics originate in the business, where they say, "We have to tighten something up or reduce risk or stop accidents from happening or increase safety on our well sites." And so we've thought about each of those personas, and we're, we're, we're really organized. When we go into a meeting and we know who we're meeting with, we have a little playbook knowing what that person is, is actually caring about, right? So whether it's somebody in sales and marketing or an executive, what is their perspective, and how are they actually going to use AI and care about it? We actually can't be everywhere at once, although I wish we could. So we need to teach our clients to go evangelize and build an AI culture themselves, right? So they have to educate their staff on how to, you know, use AI in a healthy way and in a productive way. They need to be nurturing and teaching people and communicating the AI strategy among their executive team or to their board and their shareholders. You know, we just helped a company hire an HR director, and she was saying the first question she got asked is: How are they gonna use AI in HR? And she didn't- she doesn't come from an AI background, right? She comes from a human resources background. And so these people, you know, in these roles that aren't traditionally tied to AI or analytics, they need our help. And so that has nothing to do with our software development skills or our math skills. We, we need to be able to coach her on how to- what are people expecting now? What does a new grad expect from an HR department when it comes to technology? And so what do we do? Maybe we build a chat interface for an employee handbook, right? So something we're working on and are testing internally. So we're trying to come up with real practical ways of doing this in departments. This is how we build trust our clients, so that each of them don't have to fail and trip and fall themselves. They can learn from what everybody else has done. So we gather this whole treasure chest of things that you should do and shouldn't do, and so we're warning. You know, this is how we fulfill our role as an advisor. We say, "Watch out! You know, when you're building these things, there's some risk behind it." This doesn't mean that you shouldn't do it. It just means that, you know, what are you, what are you able to tolerate? So, you know, we give them a whole book of things to watch for, and in this case, this allows them just to move forward and know that we've thought about some of these traps on the sides. We obviously have to build a team to go do all of these things, and so, I tried to distill all of our capabilities down to a couple of categories for you. How did I do? Three is pretty good, I guess. So, you know, we've always had to go and get data from where it lives and put it somewhere. None of that, that has never been more important than it is now to get all the data in one place, because the wider the data set we have, the better we are at predicting what's going to happen, right? So we can use that very wide data set for more advanced analytics. People want to see and interact with data. So, you know, data doesn't just live in a database. That's not its final home. We need to put it in the hands of somebody who can actually make a decision with it, right? Or look at a trend, identify a pattern. Data means nothing until you can take an action on it, right? And so our job is to put that in front of people in a way that they understand it. And then, obviously, we want to use all that historical information to go look for patterns and predict the future, and this is where our AI and data science team comes in. I figured I might as well splash it all up there. What you don't see here are all the skills that wrap around this, right? So software development, for example, things that maybe weren't traditionally data and analytics skills. You needed database skills, but now we actually end up building applications a lot of the time. So, if anybody has any questions in the follow-up here about some of the tangential skills we've had to build to go support a traditional analytics organization, let me know, because that has changed over time. Now, we can't do everything for everybody, and so we really need to decide where to focus. And so Converge, we've decided we wanna focus on this part of computing, which we call cognitive computing. Essentially, things that humans do, right? Seeing, hearing, interpreting, translating, searching. And we're trying to use our data powers to go enhance or augment the human experience. And so, this is the subset of AI that we really focus on. And when I talk about our use cases and success stories in a little bit, they're gonna be focused around these things, okay? I was alluding to it a little bit earlier, but you know, applications are a great way to deploy AI capabilities. So not everybody sits there in a coding Python to do AI, right? In fact, you know, very rarely is that how AI is deployed. And so we need to wrap it into an application, whether we embed that into Salesforce or into the ERP, or we build a specific application. So like here, for a bank, we built this deep learning model where it kind of does this PDF search, and it builds a graph in the background, and it connects all these documents together for this real holistic view of deals, in this case. For manufacturing, if you think about what it would take to go and gather data at a manufacturer, it's actually complicated, right? Every piece of equipment has a sensor on it. Those sensors might belong to Siemens or some other building management system. It's on a completely different system. The HVAC and systems are all on separate automation controls. We need to bring that all into one place. So before we even start talking about how to optimize, you know, production and throughput and safety, there's a lot of plumbing that needs to be done. And so, I'll talk about this a little bit in a second, but AI, for us, is just the piece that you see. All of the rest of the plumbing and engineering that has to happen is a huge effort. And so what we're trying to do is abstract a lot of that work from our clients and say, "No problem. Let's talk about the business use of AI." And then we've got a blueprint for going and doing all the plumbing work and these repeatable patterns per cloud. So if it's on Azure or Google or AWS, we've got a pattern to follow, so we don't have to invent these things from scratch every time. We also have to think about how we actually deliver these things and implement them, right? And so we've got a couple of services patterns that have emerged. This speaks back to our AIM strategy. So whether we are advising up in the top right-hand corner, where we're sitting alongside our clients and doing roadmaps and that sort of thing. I don't mean like big, fluffy consulting roadmaps. Usually, our roadmaps are like three pages long. It's very specific about what we should do. Then we do our implementations. Obviously, most of the time, we're sitting beside our clients, so everybody's hiring up their own AI and engineering and software developers. There's not. You know, they can't move fast enough. So it's often this hybrid approach, where we sit beside their developers, and we're building and teaching them and learning together. Then our managed analytics practice, so where a group just says, "You know what? You guys, we don't have the analytics skills, or we can't staff up quick enough. You guys be our analytics department for the time being." So those are great ways for us to work with a plug-in to a client, regardless of where they are in their journey. Let's talk strategy for a little bit. I think it's important, I might as well start with this. Who do we compete with? You know, we run up against the systems integrators more often than not. They tend to have good executive relationships, so then maybe they have done some of those, you know, three-ring binder strategies, the ones that are 1,000 pages long. And they've kind of been embedded in these organizations forever, and so I think it's easy for clients to say, "Yeah, you guys are already here. You might as well try this, this data warehouse project or this AI project." But they end up having y ou guys know this. They hire junior resources, they bill them at really high rates, and so we often get the opportunity to swoop in after and say, "Okay, we're much more efficient. We've got real experience. Those guys, you know, they tried, but they can stick to what they do best." So we come up against them. Regionally, we compete. There's a lot of startups, a lot of, like, government-funded or provincially-funded regionals that we'll bump up against. These are 30-, 40-person boutiques. So I came from the Newcomp Analytics acquisition, so this used to be my life, right? 'Cause we were, you know, less than 100 people. Now, we've got much broader shoulders to stand on, and so, you know, they might be really good at getting an AI project started, but. If it's a cybersecurity question, or somebody says, "What's the best AWS pattern to follow here, and how do we manage our costs on the cloud? How do we embed this into an application?" They don't have those skills, and we didn't have those skills anymore. So for me, it's been really great because now it's not – we don't have to compete at all. We have the full story, which is great. And often our biggest competitor is doing nothing, much unlike cybersecurity, where you can't do nothing. In AI, you can. Sometimes it's still seen as a luxury, right? And so this ends up being the biggest competitor. Our statement of work is up against nothing, and so they have to decide: Is this a cost-centered thing that I wanna take on or we're willing to take on? I think often they will need a strategy and a roadmap, so we're doing a lot of those kind of engagements. But, yeah, you often, you have to convince people just to move. And, I don't know if that's surprising to hear or not. It is for me every time. I'm like: How is this an option? But, it's a good spot to be in because they think of us when they come back, and they're ready. So Greg had this up here. I'm sure everybody's kind of familiar with how we think about our practices in this kind of traditional way, right? So, advanced analytics, this used to be my whole world. We've got these seven practices, and we've always kind of, I have always kind of thought about them as independent pillars of Converge, right? But I think what we have the opportunity to do is, you know, especially let's think about AI, in terms of AI. There's a lot of overlap in terms of what our salespeople are going to be asked. Shaun, you know, your salespeople are gonna be asked: How is AI infused into cybersecurity? And these are, like, problems where we have a lot of overlap, and we can reuse resources. We can invite people to the same events and workshops. And so we're working top to bottom in our organization, so from our executive team to our developers that are on the streets, just making sure we have repeatable motions. When we talk to a vendor like Dell, somebody I would have never talked to before, right, who now is asking, you know: Will you guys partner with us for AI? I need to say the same things to that partner that my colleagues in the infrastructure business are, that Shaun would be talking to them about. So we really need to standardize a lot of this, and then across our practices, we need to make sure that our teams are collaborating, so our pre-sales folks who are doing demos and doing architecture and solution design, that we're saying the same things, that we are bundling things together. So right now, in the analytics practice, we always bundle together some DevOps work, which is traditionally a software development kind of thing. We bundle in cloud services, which comes from a different practice. And so we're appending all of these things that have immediate lift. So instead of thinking about them side by side like this, my view is that Converge is this vertically integrated group of practices where we have clients, these are real humans who work on, you know, laptops and with workplace tools like Teams and Office. Those applications are increasingly powered by AI and data. All of that sits on cloud infrastructure that we can deploy and support and engineer. Shaun and his team wrap security around it, and all of that could sit on public, private, or hybrid infrastructure that we deploy and support, right? So to me, this is awesome because my story used to stop at data and AI, and I would need to phone a friend to say, "I don't know. I need somebody to come do some Google BigQuery development," 'cause that's not our world. But now it is, which is awesome. This might be a little self-centered, but I think it, we're looking for opportunities for data and AI to be infused into the rest of our practices, right? And so I've been spending a lot of time with Shaun and his colleagues, these people who are running the practices day by day, looking for opportunities. So if I talk to our workplace team, yeah, of course, they're talking about Microsoft Copilot, right? It's AI sitting next to Teams and helping people organize documents and search. So we need d ata and AI needs to be a service to the rest of our organization, and we think sales-wise, this is an easy append into a lot of these accounts, right? Where we've got cloud business, or we've got digital workplace, productivity tools business or security. You know, we can automatically talk to them about AI, and so not only am I spending my time talking to clients about AI, but I'm spending time talking internally to our group about it as well, and all the opportunities there. And you guys can read. These are all real things that we can go talk to a client about today. We thought a lot about how do we do that cross-selling, so we've got a lot of these motions. We did a roadshow. We're doing a regional roadshow with all of our salespeople, helping them understand what how to have this conversation, so they might come from an infrastructure background. How do you talk to a client about analytics and AI? And so we're teaching them to do that. We're doing, you know, like, mock selling sessions and having them, you know, really practice this messaging because it's really important. There's hundreds of them and one of me, so that's how we scale. Now, don't squint too hard. This is real life, so I put this up here kind of as a joke, but this is Microsoft's architecture for easy AI. So you can imagine, I don't know how many services are on there, but there's a dozen plus, right? It is not easy, is the point. And so, you know, you can't just go into Azure and say, "Spin up my AI studio." You can, but it goes this deep, right? To deploy AI in an organization and get it into operations takes a lot of this. There's containers and security and IoT connectors, Power BI, which is where the users might consume it, right? So we are trying to come up with a lot of these patterns, so we can walk into a client and say, "Ah, you're talking about retail up customer 360. We've got a pattern to follow for that. Here you go, and here's how we plug it into your CRM, your retail system, all the sensors that are in your stores so that you can see the movement of a pair of pants as somebody tries it on." We know all of those things, and so that-- this is how w e don't wanna do things bespoke every single time. That's a really expensive way to do professional consulting, right? So we've bundled a lot of that up, and turned it into offerings. How am I doing on time? Anybody watching? Okay. All right. We're trying to bundle these up. So I'll talk about the Walled Garden, for example, right? So, we were just talking about it this morning. Does everybody just use public versions of ChatGPT? Well, that's not really acceptable for, you know, most organizations, right? So we're spending time, w e've, we've got a bundle that says, "Here's how you spin up your own internal large language model and train it." We understand the costing, what kind of hardware they need or, or virtual services they need to spin it up internally. Design thinking, this comes back to the, the design for AI. I don't know if you guys remember on one of my first slides there, but we will sit down, and these are advisory sessions, where we sit down and people just spill use cases to us, and we gather them up, we put them in a list, and we sit with the executive team or the steering committee, and we say, "Where should we invest?" And then we use those as pilots. And, you know, that first one or two, we really, those are icebreakers, we really learn a lot about their ability to deploy AI as we do those first pilot projects. So, we're trying to be very intentional about how we go to market, and we're trying to do it, we're being pretty agnostic as far as the platform we do it on. So we need a pattern for each of the major cloud platforms. Governance is. We anticipate is going to be huge. So AI, you know, it's always been huge, but I think now that we put these tools into everybody's hands, we have to think more about how do we document decisions that are made and watch for bias and risk, and understand how they're being used. And so I think we're gonna end up investing a lot more in governance. I know, Dave, you and I have talked about this a lot. These are some of the first questions we get from clients who are risk-averse. And you'll notice the word "document" in each of those three pillars. This is all about documentation, being able to show our work, being auditable, and understanding, you know, these models cannot be black boxes. That's not acceptable, right? So we're spending a lot of time on governance. I'll talk about partnerships just for a second. So in my role, I get to talk to Databricks or Snowflake or Microsoft and understand what they're doing and how they're going to market. So we spend a lot of time not just understanding the technology, but understanding the economic side of how we partner with them as well, right? So when we're talking to an opportunity, how are we going to get paid on this deal? And so there's your traditional resale margin that we can get paid, or some of these new vendors will pay us on the back end, referral and collab fees. Now, this can be really lucrative because sometimes we just need to participate in one or two meetings and do a demo, and they'll pay us a fee on the back end. Some of those are really big deals. We can participate in ELAs and adoptions, something we could only do historically with some of the real mega vendors. Now, being able to do this with some of our more strategic point vendors, so, that's really promising. And multi-vendor, so you probably see if you follow us, you'll probably see this in the way that we do our marketing. We try not to just do one vendor anymore. We try to have a couple in the room who work together, and they've got connectors to each other's platforms. That's a much stronger story. Then when we have opportunities with clients, we come in and we do that together. We build together, which is great. They're letting us behind the scenes. So, they're saying, "Here's our product roadmap. So here's, you know, what we're going to put into the platform. What do you guys think? What are you hearing from your clients?" We get input into that. Those are the advisory boards and councils. We're getting certified as training and services partner. That adds legitimacy to us because a lot of the time, these vendors is everybody familiar with Snowflake? If you hit Snowflake's website once, you'll get their ads for the next six months, right? So the gravity changes. People will call the Snowflake reps directly, and we need that Snowflake rep to think of us first, right? And so being certified, being authorized, having a lot of these blueprints, they feel comfortable coming to us. Yeah, you have a question? How many of these are, like, one-time fees versus recurring? Like, some of them say renewals, so, like- Almost all of these models now are recurring subscriptions. There's some perpetual licensing plus, like, a renewal model in there, but most of these are subscription models nowadays or pay as you compute, right? So like a Databricks or Azure, for example, you're paying for what you use. You'll get revenue- Based on whatever. Yeah, and so if we have a great story. I cut this slide out. I should. I'll show you later if you want, but one of our big pillars is to drive compute. That's how you make friends with the hyperscalers, right? A lot of times, Snowflake will go in, and they'll sell a $50,000 contract to some client in Vancouver, and then six months later, they look at the bill, and they've spent $600 out of it, right? So they say, "Okay, Converge, please go sit with them and find use cases. Get them using that computing power so that when it comes to their contract renewal, they re-up or buy more, right?" So that's where a real strength of ours is. They don't have. There's six Snowflake reps for Western Canada, you know, for example. They need us to go, to go do that. They can't be everywhere at once. So we're spending a lot of time just driving compute for these guys. Good question. Thank you. We'll talk. Let's talk about a few stories, and then I'll turn it over here to Shaun. So this one really interesting, and I had no idea. The whole part of the world. But about 80% of the RVs, do you guys know this? 80% of the RVs are made in northern Indiana, and these are, these are, like, Amish communities. Almost every adult male in those communities works in these factories, works in manufacturing, and so you can imagine getting them to adopt technology is a challenge. And so they were trying to give them scanners on the assembly lines. This client makes about 50,000 of these trailers a year. It's 12 production lines, and they just run side by side in a giant facility. But you know, the craftspeople were breaking the scanners, and they. You know, so this was very slow. Things were moving and stuck. So they called us in and they said, "Okay, we need some balance here between just winging it and letting them work at whatever pace they want, and some crazy technical solution." And so we ended up building, you know, the solution. We could look at every part and scan which part was at what station on the assembly line, and all the craftspeople had to do was hit a button that said, "Starting" and "Stopping." We were using cameras to tell how far along the job was, so we could forecast when that it would move to the next station. This is huge. I won't talk numbers, but you know, this was a, an eight-figure return for them. So, you know, that is massive. When they can make 20,000 extra trailers in a year, that is huge. You know, COVID was wild, and getting everybody back into venues like this was a challenge. We were asked by t his is a public one, right? Yeah. Yeah, yeah. It's Lucira. So basically, you know, they work with the Oscars, with the NBA, and they needed a way to certify people negative COVID tests without testing everybody at the door, without showing y ou know, it's slow to show your phone and get to scan the codes and whatever. So they asked us to build an application for at-home tests, and it ended up being the first FDA-approved at-home test. And basically, all you had to do was take a picture of the test, and it would detect if it was negative or not, and that was all shared with these organizations. So, you know, that, that's huge. Being able to get people back into venues like this, I think we accelerated that by a long shot. This is a really cool application. But you can think of all the intersections that needed there. We had cameras and everybody's phones that needed to be supported. We had to collect that data somewhere, share it, API, with all these partners like the NBA and the Oscars. So, this is a really complicated one. It shows our strength to go just beyond data and analytics. This one's public too, right? I don't remember. No, it's not. Nice try. So they make powder. It's metallurgy. So they make powder coatings. So if you got, you know, rims on your car or on an airplane, basically, they make powders for all the coatings. You know, very strategic client of ours, we helped them hire their first CIO, and they grew by acquisition. So they ended up with this really messy world of applications and devices, and so it didn't even start as an analytics client. We did device management for them, or endpoint management, right? Trying to manage all these devices from all these different clients. And for our strategic accounts, we have a, w hat's the STA? Strategic technical advisor? So we have somebody assigned to just think through hard problems with our clients, and so, we identified, you know, they really need to modernize their data infrastructure. So they brought us in. We did a data modernization workshop. So we sit down with, you know, everybody from every department, and we just say: What are your data needs? Where are you at right now? What's antiquated? What needs replacing and modernizing? And then we go build it. And then, you know, we I think the first project we took on was modernizing their data warehouse. So great, again, started as a hardware endpoint kind of client with phones and devices, ended up in the analytics world. And finally, this is a giant natural gas company. They brought us in to help with their budgeting and planning process, so our FP&A practice. We actually sat alongside IBM in a lot of those meetings. They needed to replace something called Hyperion, which was their, you know, budgeting and planning platform. But in those meetings, after they pulled this is my client, so they pulled me aside and said: "Actually, we've got this whole mess of data infrastructure. We're paying Informatica and Oracle combined about $250 million in the next three years for our renewals. We need to do something about this." So we brought Microsoft in. They wanted to modernize on Azure, so we brought Microsoft in. They paid for the first couple of pilots, so everybody familiar with ECIF? Anyway, Microsoft will fund a project for you. You have to show how much cloud spend you're going to drive, and then they will pay you a portion of that cloud, forecasted cloud spend, to go and do pilot projects and that sort of thing. So Microsoft and Databricks came in. We did a three-month POC for submersible pumps, replacement. I don't know if you guys know this, but they, submersible pumps in a well, they don't fix them. They just run them until they explode. It's too expensive to fix it, pull it out of the ground, and lose production for a day or two, right? So they were trying to decide what RPMs and how much pressure do we put on that pump, until it explodes, to maximize throughput. So we built those models with them. This ended up being a three-year project. Tons of data engineering behind the scenes to go get all that sensor data, and historian data from PI and put it all together. So CAD 1 million of services just out of that, which is phenomenal. I know I'm tight on time, so we'll look forward. You know, we don't see any of this slowing down. I think the hype around AI is real and will and will continue to be real. I think reality will set in, that a lot of organizations, we already know this, and we're already seeing this, they need a lot of the plumbing work done first. They need their data clean and put into one place. And so, we can sit there and say, "Okay, we have an AI roadmap for you, but also we can do all of that engineering and software development for you along the way." Governance is going to be huge. We talked about this. We are going to end up having to find talent for our clients, and so we, I, you know, we stay close to the schools and the programs there to try and direct traffic. We've got a talent organization at Converge, and I think that'll be more important than ever. Our clients will turn to us and say: "Who do we hire? What are even the skills we're looking for? How do we evaluate, who comes on board?" And so, you know, I will just leave you with this, in that, in my year here, it's been pretty awesome. I, you know, we used to have just part of the story, and now I've got so many friends that we can phone. That oil and gas client, by the way, we brought in our app development team, so our app mod team. They needed to rebuild their whole DevOps environment in Azure, and so I brought in, my colleagues from that practice, and we brought in our cloud practice as well to do a whole bunch of their pipeline automation. So, you know, just the fact that we can do that is very exciting for me. That was a, that was a client that Converge acquired through Newcomp, and we've been able to go and extend them all into the Converge family. So being able to do even more of that is just super exciting for me. So Shaun, I'll take some questions first, if anybody has them. Yeah. Oh, good. Just a quick question. Yeah. That's very interesting, all that you talk about here, but what is the true interest in AI for your clients? Because you—like, you know, Converge has a very different set of clients than some of the other larger tech, technology services companies might have. So what is? Are they still ramping up on their technology ecosystem before they even consider considering these AI discussions there? I think they are scrambling, and that is our, our experience. I was just on with an insurance company that all of you would know yesterday. They have 500 people in their AI group, what they call their AI group. I think that's made up of data engineers and software engineers, and a bunch of computer scientists, but they are lost. So their users want to use tools like ChatGPT and other open source platforms. They are trying to do a hybrid cloud, so, you know, they haven't made commitments to AWS or Azure, and so they're going to try and deploy on both. They need to abstract all of that complexity from their business community who wants to go and develop AI-infused applications, but they don't know how. And so a lot of this is still an architecture question. And these aren't even the technology folks. This is, like, from CIO through the organization. So yes, it's this balance between everybody can think of great ways. "Yeah, we want to put a chatbot inside of our employee handbook," or, "We want to have a, you know, call center automation," or whatever. But at the same time, behind the scenes, they are scrambling, and I think that, you know, data warehousing of the past just is not going to be enough to keep up with the compute demands of AI, and so we're burning this candle from both ends. But like, we are—we're building right now. So if you have enough data, we can go and do pilots and build actual applications, and we've got dozens under our belt already. But when we talk about deploying it at the enterprise scale, there's still tons of work to do. Yeah, and Jimmy, one comment I'll make there, too, is when we talk about our mid-market strategy, when we say mid-market, it still includes large enterprise clients, not the Fortune 100. Yeah. That's where we're seeing a lot of larger services projects, right? Multimillion-dollar services projects that we've signed in 2023, right? So when you think about our customer base, those enterprise clients are driving lots and lots of services with us, and we'll continue to focus there to drive the high-value growth in AI, in cyber, right? To ensure we can deliver on those big projects. Yeah. Yeah. A Midwest bank found us on YouTube, and their CTO sent me a note, and he said, "Hey, I need help 'cause everybody's asking me, and I don't know what to do." And that also turned into a $1 million client for us about a year ago. So, you know, just thinking about how to deploy this dovetails into a whole bunch of services that we are doing, which is awesome. Yeah. Yeah? When you, when you mentioned that the clients are scrambling a little bit, do you find that they're scrambling more on the plumbing and the infrastructure, or on the data, and the setup, and the cleansing of the data and whatnot? Mostly on the infrastructure end. So a lot of them still have a lot of legacy systems that they are trying to figure out, a lot of point reporting, and they, you know, w e like to think everybody has moved to the cloud, but some applications have and some haven't. And then the other half of that is just organizationally and culturally, they don't know how to structure it. Should all of this be funneled through one steering committee that decides where to invest or not invest? Do we let each of our departments, like finance or HR or operations, do we let them hire their own data scientists, and then therefore, just build them a platform to go develop against? So it's a centralized versus decentralized thing. There, there's a couple of patterns that are emerging out there, but you'd be surprised at, you know, who needs help doing this. I think it's still early days, and we're you know, just being in the thousands of accounts that we're in right now, we're getting those phone calls every day. Good question. Thanks. Yeah. Could you dive into the significance of the Snowflake relationship and how you have an inside track with them versus some of your peers, perhaps? Sure, yeah. I mean, so we end up spending time with their engineering groups, so we get feature previews from them. So they'll say, "Here's the next year and a half of development that we have," and they throw a timeline up there. And they'll say, "Okay," so when they, you know, I won't get technical, but they say, "You know, we're going to support some open source data store, like Iceberg." They'll give us a preview of that. We have our own environment. We can go test integrations against it. Greg mentioned tools like Alteryx, which are downstream of Snowflake. A business user might go use Alteryx to go build a predictive model. We'll test how that integrates back into some of these new preview features with them. They give us access to a lot of their assets as well. So whether those are industry blueprints or models that they use to, you know, so that we don't have to go invent demos from scratch every time and do custom demos, they'll give us a lot of that as well. And then, yeah, just spending the time with their engineers, like, not their customer-facing engineers, their product engineers. We get to see what's coming, which is awesome. You have to be at a certain tier of partner for them to open, and these are by invite only. So a lot of the time they'll host this workshop in one of their offices, and they'll invite a handful of their top global partners strategically to come sit in those sessions, but they do not do them publicly. Yeah, no problem. Yeah, so when we're talking about clients potentially being lost with AI, and even the best specialists in the field aren't exactly sure what's gonna happen- Over the next year or two, not everyone's reflex is gonna be to throw money at the problem. Do you see the market being in a bit of a freeze in terms of assessing what's going on right now? Does this slow down other type of work that could be done on the cloud side as well? How is the dynamic in terms of these companies investing in new product, given all the AI questions we have? It's hard to say where it's going. Where it is right now is that it's driving way more conversations. Those are inbound questions, whereas we would've had to go do outbound outreach, right? And invite people to events and say, "Okay, we should have an AI conversation." Now they come to us. And so for us, it's immediate lift in that we're identifying: Hey, we need to organize your data or get ready for this organizationally. So for us, it's not a, I don't, the hype may die down, but the lasting impact is that all these organizations have realized they're not ready to a certain extent, right? So that'll have a long tail, and we're staffing up accordingly. So for me, data engineering and all of that kind of data architecture and design, cloud infrastructure, all of that, these AI questions will drive that in the future. And that's what we're seeing, right? As we get brought in to have the Gen AI conversation or any AI conversation, we're now getting introduced into that account. We're branching off, right? So AI might not happen, or the project we're talking about, or the use cases we're developing might not happen for two-three years, but now we're engaging on a cloud platform project or an AppMod project, right? Yeah. So then we expand from there, and we're in there continuing to talk about, as we build this application, here's how AI is gonna be leveraged in the next two-three years, right? It's just pulled everything to the forefront. You know, even a couple of years ago, data scientists in an oil and gas company, they were kind of kept behind the scenes, right? They were building models, and they would just kind of throw it over the fence to somebody. Whereas now, those skills are being pulled forward, and they're sitting in front of people and saying, you know, "Here's what these models mean." And so anytime that gets pulled forward, that pulls us forward in the organization, from the depths in the back offices to, you know, these are boardroom discussions now. So I'll take that, and it's going to drive it for the next, you know, foreseeable future. Yeah. Thanks. There's currently a war for AI-related talent, so how should we think about your, you know, your manpower in terms of R&D and implementation? The- Also, you mentioned at the beginning of the conversation that you're based in Calgary. Yeah. Is also AI major center for Converge is like global strategy for you guys. Okay, I'll start with the first one, too. So just like a war for talent, you're right. There's some, like, wildly inflated numbers. In the markets that we operate in, I think we're-- so far, we're finding it okay to go and, and grab that talent. The AI talent, we're trying not to be a victim of the hype as well, right? So we're hiring smart people with real-life skills. That doesn't need- that doesn't mean they, they need to, you know, have worked at Google or something, right? For me, somebody who's willing to learn and build these models and understand and do the training that we ask them to is, is powerful enough, and we're seeing the results with that. They're able to go out there and build, you know, really cool things for our clients. Calgary itself, I don't know, guys, is this strategic? It was one of the dots. It was one of the dots on the, yeah, it is a great market to be in. There's a lot of—you know, there's some cool startups in Calgary that, you know, have drawn funding, like Neo. I don't know if you guys know Neo Financial or Benevity or companies like that that have drawn talent to the city. So no, it's great. You know, we don't struggle with job posting. You know, they don't last long. I think that's where the scale and expertise comes into play, too, right? Technical resources like these guys are enjoying being part of Converge because they can work with peers outside of just AI. We're seeing the same thing on the recruitment side. So as we've acquired all these analytics companies, now that we have the mass, people wanna join the Converge team, right? Whereas we're not struggling to find talent. And Chris mentioned earlier, the talent organization, right? That has a whole team of 1099 resources that we've tapped into in the past, that as the projects come on board, we can then bring them on full-time as well, so. Yeah. Hey, Chris. How big is your team right now? How many openings do you have, and where do you think the team will be in about a year? Okay, I don't know within our, a ctually, I don't have a good count. You probably know better than I do. About- A little over 100. A little over 100? Yeah, yeah. And about 20% of that, I would say, are, like, raw, pure data science folks. So these are people with that holy intersection of business acumen and math skills and computer science skills. So, you know, these are our design thinkers and application builders who are doing this. So, you know, proportionally, it's a heavy part of our group, and then, you know, supported by a massive data engineering team. and as we look at head count, right, that constantly changes, right? We're always looking at what projects we're signing, right? Versus having a bunch of people sitting on the bench. What's the pipeline look like, and then hire as we need the resources from a technical perspective. That's right. Resource by resource, Greg. Every month- That's right. We go through utilization, who's forecasted to be on what. We have a close eye on this stuff. So yeah, we know exactly what's coming from a signed statement of work perspective. We know where we need lead time to go, you know, find either subcontractors, our talent pool, or go hire for our teams. So, yeah. Okay, we're gonna take one more, I think, and then we gotta move to cyber. Okay. We'll open it up again at the end. Yeah. Yeah, so just your stance on the open versus closed source debate with your clients. Like, how are they approaching it? It can't be the last question. That's like a 20-minute answer. No. You know what? Open source is great because it's accessible to everybody, and you can get started, but it's open. So, you know, whatever you put into it is at your own risk, right? So we're seeing a lot of. So I was talking about the insurance company I had a call with yesterday. They blocked access to it entirely. So, you know, these are companies that you would hope are on the forefront of developing with, you know, ChatGPT and other large language models. If you go to OpenAI, it's blocked. So, their director of analytics told me he has his personal laptop sitting there, where he uses it on his personal laptop, and then emails it to himself. Oh, boy! So yeah, Shaun, just do one of these for a second. Yeah. But that's where we're at. It's lock it down. The open, you know, building your own walled garden, closed versions of these, they're expensive to train too, right? Like, GPT-4, does anybody know how much it costs to train GPT-4? $100 million. So it's about 10,000 H100s, is that what they are? Chips, and they're about $30,000 each, right? So it is very expensive to train on their own. And so we're seeing a lot of our clients use the public-facing ones, not just GPT, but like Llama or whatever, and get started, while in parallel, we're thinking, "Okay, how do we build their own version of this in their own infrastructure that's controlled and secured?" So it's very bimodal right now. We're doing a little bit of both at the same time in each of our clients. Yeah. That was the short version of a really long answer. Good, thanks. Follow up. Yeah. Ask away. Okay, thanks, everybody. Over to Shaun. Thank you, Chris. Yeah, of course. Feel like I'm following Paul McCartney there. No. Good job, Chris. Fantastic. Who? I know we're. Who? I'm kidding. Gordon Lightfoot, is that a better reference maybe? I'm kidding, I'm kidding. I don't know. I'm kidding. Yeah. Thanks, everybody. I know we're running a little short on time here, but I'm gonna do my best to talk- Sorry. Fast, but not furious, right? So good morning, good afternoon, or good evening, depending on where everybody's coming from. Wanna thank those in the audience. This is the first time I've been to Toronto in about 12 years. My, what a beautiful city, great culture. It's changed a lot since I was here last. Thank those on the webcast as well, right? So my name is Shaun Bertrand. The way I describe, I run the cybersecurity practice here at Converge today. I describe myself as a very passionate resource as it relates to cybersecurity. It's true. I've been doing this since I was about 13 years old. Here's my vertically challenged joke. You know, I was about that big then, and I grew about this big now. But, I'm excited to share with all of you here today a little bit of our vision, our team, our strategy, and the opportunities for cross-practice selling, right? So without further ado, let's get started. I'm a big data-driven individual, right? And I wanna talk first a little bit about the cybersecurity landscape and how important data like this is for our customers and for our strategy. We are a data-driven organization. We let data drive our strategy, allowing us to make more effective business decisions. Let's be frank, nowhere, in my opinion, is data more critical than cybersecurity, right? So when we look at some of these stats, right, cybercrime is expected to cost the world $10.5 trillion annually by 2025. That's more than the GDP of Japan, right? You look at a ransomware attack. I don't think a day goes by where we don't hear about a ransomware attack, right? Back in 2022, every 11 seconds, an organization was attacked as a result of ransomware. By the time I'm done with this presentation, there will have been 163 companies that have been attacked by ransomware. And I don't think, you know, ransomware obviously isn't the only attack vector that's out there, but it's one of the most impactful, right? Costing organizations and victims around $265 billion annually, and it will attack, you know, consumer devices every two seconds. Global average cost of a data breach in 2023 was about $4.5 million, a 15% increase over those last three years. So what, what does this tell us, right? What does it tell us? It tells us that 51% of organizations are planning to increase their security investments. And I think that other little data tidbit over there, the final one, right up your alley, Chris, right? Average savings for organizations that use security AI and automation extensively is about $1.76 million. They can eradicate the adversaries faster. They can leverage that AI automation to discover, and I'll share some more data points with you here momentarily. So a little bit about us, right? Who are we? We are a team of strategists, veterans of the industry, former chief information security officers, and resources who are driven to exceed our customer expectations, right? We align to the defined outcomes and the consistent outcomes of our customers. So what do we do? We defend and secure the endpoints, the networks, and the users. We test, monitor, and manage various different areas of operational risk. We detect and respond to incidents. We help our customers comply with a very wide array of different rules and regulations, and we enhance and upskill the cybersecurity resources, not just within our customers, but within our organization as well. So Greg talked a little bit about Converge, right? We talked about our 60+ locations. We talked about the 4,000 clients, the various different partnerships that we have. I wanna talk to you a little bit about the cybersecurity practice, all right? So over 30 years of cybersecurity experience, we have roughly 200 resources that are out there, 4,000 professional services engagements underneath our belt, and a lot of different data in regards to the threat hunting and the security alerts that we analyze. So when I look at that, I think, you know, what we do. We delight our customers. We delight our customers, proven by those industry-leading NPS scores, and by leveraging our differentiators, which I'm gonna talk to you a little bit about here momentarily, we drive strong retention, right? World-class retention, leading to those strengthened relationship strategic alliances that we build with our customers, that help promote the success with the cross-practice strategy that we have as well. So let's go through our core differentiators here a little bit. I'm, I'm proud of the team, right? I really am, and I'm gonna talk to you about passion, right? Passion runs through the blood and the DNA of pretty much every one of our cybersecurity resources, all right? It's at the heart and center of what we do. We really don't stop until we achieve our goals, and one of those goals is to exceed our customer expectations. World-class delivery, right? I talked a little bit earlier about, you know, those NPS scores, but I feel strongly that we perform at a higher and more consistent rate than our competitors. Specialized expertise. We do a lot, right? We don't do everything. We are authentic with what we do, but here's a good example of that I like to make on the specialized expertise side. We do a fair bit of defense contracting, all right? So we have around 20 active, top-secret cleared resources. I don't usually talk about that a lot, but do all of our customers need somebody with an active top secret clearance? No. But does it give them the warm and fuzzies, and the trust, and the credibility, and the confidence that they're working with the right firm? Yes, it does. Compliance and regulation, you know, we have a wide array of specialized resources that focus solely on helping our customers with that diverse set of governance, risk, and compliance. I'm gonna talk to you a little bit in the future here in a couple other slides about some of the emerging frameworks within the United States that we feel we can align to strongly. Partners, our ecosystem of partners, is, you know. We have—I think the key to partnerships is strong relationships, right? But also aligning specifically to our customer, customer demands, and we'll talk about those as well here moving forward. Thought leadership, I think this is an important one. You know, what I wanna do is, I want to empower our customers. I wanna educate our customers, right? It's really simple as that. So through workshops, through blogs, through white papers, social media, you know, we are true evangelists that allow our customers to walk away smarter from our publications and materials, and that makes me feel good. It really does. I got into cybersecurity when I was this big, you know, before, it was really the Wild Wild West back then. But the reason I'm in it today, for as long as I have been, it feels good. I know it sounds kinda, like, cheesy, but it feels good at the end of the day, walking away, knowing we've made a difference. We've helped our customers improve their risk resilience, reduce their attack surface, and at the end of the day, that sense of accomplishment is real. Global reach, you know, a majority of our, our work is, you know, based in North America clients, but certainly expand into that global reach, right? We operate in. We help facilitate work in EMEA and Asia Pac, obviously here in Canada, and so we're expanding that reach as we speak as well. All right, this is intended to be a little bit of a condensed overview of our practice and the services that we facilitate. So I'm gonna start with the advanced testing. Advanced testing, otherwise known as the penetration testing team, otherwise known as the red team. It depends on who you ask and what day of the week you're asking in regards to this. But what do we do? Application testing. We focus on emerging threats like AI-driven threats, like ransomware. We facilitate penetration testing, which is a real core competency, and we developed a penetration testing as a service that I'm gonna talk to you here again in a little bit. I wanna talk about application testing, though, right? Application testing has driven significantly over the last two or three years, right? Our business is growing in that space significantly. The drive towards application security testing and the growth that we're seeing, it's generally supported by the cloud. What do you think about when you think of the cloud? What's the primary interface that you're interacting with the cloud? It's a mobile application, it's a web application, it's an API, right? And those risks and those threats are detrimental to various different organizations, but it requires a very advanced and unique skill set, a sophisticated skill set, to identify those threats before the bad guys do. GRC, right? We focus on things like cloud security, a wide array of regulations and compliance, right? The list, I mean, PCI, HIPAA, GDPR, some of the new stuff coming out with the ADPPA that I'll mention here momentarily. We are great at what we do in that space. Incident response. As I talked a little earlier about letting data drive our strategy and our vision, you know, one of the organizations that we work with is a group called the Ponemon Institute. World-class research group, all right? Organizations that have a tested incident response plan, they're doing things proactively before stuff hits the fan. They're gonna reduce their average cost by 35%, all right? So that's why we are seeing a tremendous amount of growth in our incident response planning, the preparation, tabletop exercises, and we really help our customers be more proactive with incident response. That said, not even the best-run organization, the most prepared organization, is immune to cybersecurity attacks, right? So in those cases, our incident response team and our partners are well-positioned to help eradicate the adversaries and get that business back into a viable state. We talk a little bit about strategy and defense here. So our strategy and defense is really centered to a lot of implementation that we do, whether it's controls, countermeasures, deployment of our various partner technologies. We also have a very strong focus on data and user protection. I mean, data is king, right? Data follows us from a consumer level, from a business level, all over. So we have a very refined strategy, great partnership with IBM in that space that we'll talk about momentarily here. You know, network is the evolution of cloud, on-prem, SaaS, PaaS, has, has evolved considerably. You know, we still focus on those various different networks, where the data is located, and, and tying that together as well. Threat and vulnerability, threat and vulnerability management and implementation, I mentioned already. Strategic staffing. I wanna talk a little bit about strategic staffing, AKA residencies. It is one of our most prominent services. All right? What we do here is help our customers fill skill sets that they don't have, and I'd say more importantly, what we end up finding is that, you know, customers have an initiative. They have a solution that they're trying to resolve, but their team is already underwater. Their team is busy just trying to keep the lights on. Our value add is we can come in with the advanced and sophisticated skills that we do and help accelerate the organization's ability to get these solutions implemented and to address their challenges. Managed security. So talk a little bit about managed security. Our value derivative here is quite simple. We help our customers detect and respond to cyber threats. I wanna talk to you real quickly as I talk about enablement and empowerment. I hope a lot of you walk out of here smarter as a result of some of these data tidbits I'm mentioning. The average breakout time, and I'm gonna explain that here momentarily, from the time it takes from an adversary to gain initial access into a customer environment, to the time that they compromise the entire environment. So let's say they send a phishing attack, somebody clicks on that phishing attack, then the actual adversary is able to get inside the environment and compromise the environment, 90 minutes. It takes 90 minutes from that initial access to the full compromise of an organization. Why is that important? We have 89 minutes within our managed security services team to identify and to eradicate those adversaries, and that's what we do. We're different than our competitors here. We're not just automated. Absolutely, we leverage AI and automation, but it's also complemented through the advanced human threat hunters that help more effectively detect and prevent those attacks. The Advise, Implement, and Manage. We heard a little bit about that earlier, right? I'm gonna hone in on that here on the next slide in a little bit more particular detail. So let's look at the Advise, Implement, and Manage methodology in a little bit more detail. Not every customer goes through this methodology, but this is the approach where we see customers lean in. They understand the approach. What do we do? We advise and assess, facilitating services that help discover and remediate those vulnerabilities before the bad guys do. We unify and we integrate GRC using that risk-centric approach. We then move into the implementation phase, helping customers proactively position themselves with that more risk-resilient, you know, perspective, and then move toward, move forward, towards building, integrating, and optimizing a diverse set of those controls and countermeasures. And then lastly, managed security, right? We talked about it. We finally position these controls and opportunities in a managed services fashion, whether it's cloud, data protection, detection and response, and threat management, and it's real. We are doing this. I know this is an eye chart, very similar to yours earlier, right? What I wanna do is I wanna take you on a journey, all right? Very similar to that advise, implement, and manage methodology. It all starts in the middle, protecting our customer's brand, their reputation, their data, right? And that's the goal. We start on the left, identifying vulnerabilities, threats, and risk for our customers, and as we shift to the middle, this is where we implement and integrate a wide array of different controls and countermeasures that align to the data, the applications, the user, email, endpoints, network, and cloud. This is where a couple things come into play. First of all, our partners, right? You're gonna talk to me. I'm gonna hear you. I'm gonna speak a little bit about our partners and how we are relatively vendor-agnostic, but this is where we can apply the right partner technology to the customers, depending on what their challenges are. This is also where we see the cross-practice opportunity really start to develop, all right? I'll give you a couple examples. When our application testing team finds those application-related vulnerabilities that we spoke about, many of our customers are very challenged in how quickly they can remediate those threats. I mean, I've been in this business a long time. To fix some of these vulnerabilities and threats that we find could take months, sometimes years. That's where we bring in our app mod team, right? So we bring in our app mod team, they can come in, and they can help remediate those things often in days, right? Then we can start talking about, you know, more of a strategy-based focus. So why did they get to this place in, you know, in the first place? Software development lifecycle, CI/CD pipeline, integrating security earlier on into that development lifecycle, that's what we do, right? Same thing with incident response, right? We talk about incident response. Post-incident, what we are very successful with right now is then being able to position our digital infrastructure team into the equation. Because I hear a lot of our customers after the incident say, "We need help. We know our network is not as resilient or robust as it should be. Can Converge come in and help?" Absolutely, we can. Absolutely, we can. So, you know, as we move forward across, kind of over and to the right, I talked a little bit about, you know, the ability to help our customers manage their various solutions and technologies through our managed security services and the strategic staffing piece as well. Partners, our core partners. I wish I could put all of our partners on here, but I could not fit everybody on here, right? But what we do is we emphasize a vendor-agnostic approach. We choose who we go to market with based on the best solutions or those emerging technologies. Relationships with these partners are key. They really are. Whether we're fighting for more points or whether we have an issue or an escalation, you know, we have everything from strategic relationships with the utmost level and the highest layer of these organizations, with the CEO, the CIOs, so that if there is an issue, I can pick up the phone and talk to these individuals right away. And then we have sales ownership and accountability in relationships, and then we have technical accountability in relationships, and it works. We're also really heavily vested right now in figuring out who is the next up-and-coming AI, ML partner that we want to hitch our wagon to, right? Companies like Anomali or Vectra AI, we're looking at these in a different set of optics than we did two or three years ago, and we're excited. But we're also better understanding where is it that some of these existing vendors, where we feel confident that over the next two or three years, they're gonna take this AI world by storm. CrowdStrike is one of them, right? So CrowdStrike just released a tool called Charlotte, which why is it everybody's gotta come up with a name for the AI piece, Chris? Is that just a common kinda thing, right? I guess. Well, what does Charlotte do, all right? You know, we have this thing in the cybersecurity world called SOAR, Security Orchestration, Automation, and Response. It allows organizations to take action on the things that they're seeing in a much more efficient way. Well, that's what Charlotte brings to the table. We've struggled with SOAR over the last three-five years significantly. So now, what you can do is use some of this capability from our partners, like Charlotte, to say, "Show me all the vulnerabilities I have in my cloud. Run some scripts to go and patch and fix those things." You know, that's what we see AI doing within the partner ecosystem. Where we see forecasted growth opportunities, right? You know, identity and access management, this is big. The market is projected to reach $34 billion by 2028. It's growing at a clip, a CAGR, a current annual growth rate of around 14%. We're aligned to these growth opportunities today and continue to diversify our technology and partner portfolio. Cloud security is going nowhere, right? I mean, if you look at some of the things that we've seen with Microsoft and the cloud breach over the last week or two, we know that cloud is here to stay, and we know cloud security needs to be woven into the fabric of not just cybersecurity, of AI and everything else in between, right? That was a big one. If you haven't read up on it, you know, multiple U.S. e-commerce secretaries, State Department officials, and some other organizations that have not yet been publicly named, cloud security is here to stay. As-a-service offerings, this is one of the most things I'm really proud about, right? So take our penetration testing as-a-service as an example. You know, about three years ago, we built this service for a couple reasons. Number one, we wanted to disrupt our competition. Nothing makes me feel better than disrupting my competition, right? Number two, we wanted to provide strong value to our customers. What we did here is we created an offering that is a cost-effective and continuous solution, and what it resulted in is a service that grew in ways we couldn't imagine. Today, we have some of the largest organizations in the world that span a lot of different industry verticals focused on our as-a-service offerings. Data protection, privacy regulations, I talked a little bit about this, but a raise of hands, anybody know what the ADPPA is? That's the opportunity. Who, who knows what GDPR is? A few. All right. So the ADPPA is the American Data Privacy and Protection Act. GDPR is a European framework that is designed to have penalties and teeth in it. So if an organization doesn't protect your data adequately, they get fined. The United States has been focused on trying to develop and implement and integrate something like this over the last three-five years, and it's finally starting to come to fruition. All right, so we are aligning. Why is that important? When and what, what is the opportunity? Because customers, specifically in the United States, are going to have to prove and demonstrate that they are doing the right things, they've got the right controls installed, their diligence is there, and that means opportunities for us, right? Ransomware defense, AI, ML, we talked a little bit about. How am I doing on time? Okay. All right. Application security, we talked about. Anticipated growth verticals, right? Municipalities, specifically. Schools, specifically K- 12, right? And even in the higher ed space. It makes me mad when I read something in the headlines about a K-12 school district getting hit by ransomware, right? It completely brings them down. It impacts our children's education and their ability to learn. That's where I get passionate and excited about fixing things. So we feel there is a tremendous amount of space there, and we're actually building some services to give that K- 12, and even the higher education vertical, an opportunity to do better. Healthcare is a big one, too. You know, we see healthcare moving at light speed right now. IoT-based technologies, struggles with the way that they have all these different technologies segmented and siloed and controlled. And then critical infrastructure, right? As I mentioned before, we got quite a few folks with active TS clearances, whether that's nuclear or other, you know, gas pipeline, tremendous amount of opportunities in that space. And then lastly, the SMB sector, right? When we look at our ideal customer profile, you know, it's largely going to be between, you know, the mid-market space and within enterprise for cybersecurity. But we also feel there's a tremendous greenfield approach and opportunity within the SMB market itself, maybe a little bit to the left or to the right than the spectrum that I just gave you. All right, a couple stories. All right. So this is a large U.S. airline organization, and we formed the partnership with this organization about two years ago, as a result of what I'll define as some tactical initiatives. And as a result, we formed relationships at the highest layer of the organization: board, CIO, CEO. And this is where I wanna talk to you about the practice, the cross-practice strategy being real, all right? So as a result of our cybersecurity services, we were then able to land and expand, no pun intended, with the airline into our digital infrastructures team, right? So then, as a result, we started to sell them a lot of product, VMware, F5, and Rubrik, and we built that strategic alliance, we built that partnership. As a result, we are very well aligned with this customer, and we're currently executing on a very large cybersecurity strategic initiative to make sure all of their controls and countermeasures are locked down in the manner that they need to be. Global automotive manufacturer. This one, I am also very proud of. You know, our relationship with this company has spanned about five years, and as a result of our thought leadership, the advanced and sophisticated skill set that we bring to the table, and also driven from our penetration testing as-a-service offering. I think it's important when we talk about the result, every year, this very large organization brings in all of our competition, and they put us into what's called a capture the flag event. And really, it's just a technical validation test to make sure that they're using the right vendor who brings those skills to the table. Every year, we have destroyed our competition. They bring us back year over year, and that feels great at the end of the day. An enterprise financial organization. So this organization and firm we've been working with for over the past 10 years, and this is what we strive towards, being an extension of their team, right? Being that aligned partner, building that strategic partnership. We do a lot in the GRC space here with them, with frameworks such as PCI, Sarbanes-Oxley, GLBA. But the result is now that we are focused on helping them with a very large data protection strategy. So over the last two years, we helped them establish the foundation of their data protection strategy, aligning to those various different GRC framework and requirements that they have, and now we're in the midst of actually executing, right? So when I talk about a team, we've got five to seven resources out there doing nothing but helping them with their data protection practice and strategy. Almost done. All right. So this one's important, right? When we talk about kind of closing slide, I got one more after this. Choosing the right cybersecurity partner comes down to what matters most to you and to our customers, right? We're not the right fit for every organization, but what makes us different is, from other firms, is often exactly what works for our customers. The collaboration, the focus, the expertise, the portfolio, the services, the solutions that we spoke about, that's really what makes us special, unique, and proud of the team that we've established today. So last slide that I have here is this one. I'll let. These are customer references, all right? As a result of my colleague here, David Luftig, helping us to operationalize the NPS process, right? And this just speaks a little bit about who we are, what we do, and what our customers think about as far as our cybersecurity team. We're proud of what we've accomplished thus far, but more importantly, we feel we have a tremendous opportunity ahead to drive the growth, the revenue, the strategy that we shared here with you today. Our vision is quite simple: It's to establish the Converge cybersecurity team into an industry-recognized name, a force to be reckoned with. I appreciate everyone listening to me talk for the last 30 minutes here. I think I did okay on time, but I hope you all feel the same level of intensity, excitement, and opportunities that we do as well. So that's it. Little time for Q&A, or do we need to move into your Q&A? No, you had five minutes. Okay. Great, great job on the presentation. Just going back to the slide about your partner ecosystem. So you'll use CrowdStrike for the EDR, Arctic Wolf for the MDR, Zscaler for browser isolation, whatever. Got it. Have you been able to create any of your own proprietary tech along the way? We're talking about that. Dashboards- Yeah. Whether it's false positive detection, whether it's something else, patch pushing, something else. Have you been able to do that to increase margins? Yeah. You know, one of the things that we did is we developed a partnership with an organization that has allowed us to build our own penetration testing platform, all right? It's a fair bit of a SaaS, but also some intellectual property and our own built-in. And what that platform allows our customers to do is get real-time data as we're finding vulnerabilities with our pen test. That's one of the biggest drawbacks that we heard five, six years ago is, you know, why does a customer have to wait for the report to find out these critical, jaw-dropping threats? Now, it's real time, right? And we're operationalizing that infrastructure and that platform with various different API calls that give them a lot more value derivative. But I also feel there's opportunities with a lot of our other business, too. When we talk about the thousands of penetration tests that we've facilitated and the very unfair advantage that we have in regards to the techniques, tactics, and procedures that we use, I feel there's an opportunity from an AI perspective to help automate some of those things, and we're talking about that today. Great. Thank you. Good question. In the back? Yeah. As you look at your pipeline today, how much of that is advisory versus managed implementations and then professional services? Like, how do you kind of look at that? Yeah. So advisory, I don't know if you guys wanna answer that a little bit, but for us, the advisory, we wanna turn ourselves into more of a professional services organization, right? So from the advisory perspective, it makes up a pretty great amount, and vast percentage of what it is that we do. What we need to be doing better on is driving those opportunities into the managed space. We're doing great in the managed services space, and we talk about the integration of managed infrastructure services with managed cybersecurity services as well. But a great example of what we're operationalizing literally as we speak is what's called a pull-through opportunity process. At the end of every single engagement that we do, we sit down as a team, not just cybersecurity, but DI, DW, AppMod, Analytics, everybody, and we understand what are the recommendations that we're leveraging today that can help drive that cross-practice strategy and opportunity. Just ask a quick question in continuation with the data and AI discussions. As you, as the company in general, is creating pilots for some of these AI solutions is cybersecurity a part of that pilot at all? Are the companies considering it, and are you guys talking about it, and to what extent? Yeah, we are, especially with our clients. You know, our clients are coming to us right now, talking about how they harness it and how they control and govern it. I think you have three company kinda profiles: those that are embracing it, those that are completely against it, and then those that are somewhere in the middle, right? So what we're helping primarily from a cybersecurity perspective is making sure that we build the governance. We leverage their controls and countermeasures, so if somebody wants to. You know, as Chris was mentioning earlier, it's real easy to inadvertently type something into ChatGPT, or Bard, or whatever, that is proprietary, confidential customer information, right? And so helping our customers better establish those controls, the visibility, the notification and alerts, is something that we're moving forward with as well. I think you said you had roughly 200+ in terms of resources? How would you break that down between, you know, development, implementation- Great question And accounts? Yeah, we have about 125 to 140 consultants. Those are the professional services resources that we have within the team. Then, we have an overlay of solution specialists and solution architects as well, probably a couple dozen there. Then, we have a handful of contractors as well, and that does not include the Portage resources, Portage resources. That answer your question, sir? Yes. All right. All right, now I think it's time to bring some of the other audience members up here. Thank you, everybody. Appreciate your time. I'm gonna sit on stage. Let's go. Let's everybody- Sit down. Yeah, nice try. Nice try. You're the interesting ones. Let me sit down here. Oh, wow! Okay. Yeah. I threw my back out this week, so I'm gonna stand. So. All right. Thanks for the presentation. It was great to get some insight into the product. I was curious about the sales team. It was mentioned that, you know, some of you are doing rounds to train up the sales team to sell some of these newer services. Where are we in that process, and what is the opportunity, you know, in the three- to five-year timeframe to ramp up that sales team? Sure. Yeah, so, so if you think about the evolution of the company, right? I mean, we, we started doing these national sales meetings back in 2020. And we've continued to change the enablement roadmap, right? We've learned where we have local coverage, those reps are getting the story down faster. I'll use the Northeast, for example. We have a lot of pre-sales resource, a lot of solution specialists in the Northeast. 80% of our sellers are now selling four-plus practice areas, specifically in the Northeast. So what we've started to do is, as opposed to. We were doing, and David Luftig, who runs our, our practices from a solutions and strategy perspective, we used to go out and do weekly roadmaps, right? We would go out, do an enablement session, and then jump to another city, do another enablement session. So this year, what we learned was, if we spend more time in that region, the reps are getting the repetitive knowledge, and they're really starting to learn how to sell the solution, how to drive that engagement with our customers. So we've now evolved from doing weekly sessions to doing six-week, what do we call them? Six-week- Eight-week sprints. Eight-week sprints, sorry. Eight-week sprints, right? So we spent eight weeks in a particular region for just analytics, eight weeks in a particular region just for cyber. So the reps are definitely learning the story more and more, but where we have that regional presence, they've definitely, I'll say, taken to the approach much faster. But, you know, we'll never be 100% there, and we never expect our account execs to be able to tell the, the story 100%. We expect to have the regional presence to be able to bring in front of the clients. So the smart guys like Shaun and Chris and their teams are regionally aligned, so we have solution architects in region that can go in and tell the story, and that's really the key thing. We just want them to be smart enough to hear the buzzwords and then jump in and drive the story. And realize this is a very different model than the traditional IT reseller model. So when I was back running Pivot all those years ago, I would have died to have these kind of resources in the customer. We were a resale business. We didn't have smart guys like Shaun and the teams that they have, you know, across these different practice areas to meet the customers in a very different way. And some of the AI conversations that you've heard, those are not things that a reseller has, right? Your CGIs, your Accentures have those conversations, not a reseller. And one of the things, we bought so many companies that kind of in the midst of that, what was lost is these highly capable companies, CBI, you know, from Lighthouse and, and from Essex, and then LPA, Carpe Diem, Newcomp Analytics, Five Analytics, these teams. And the, one of the things that I've done a poor job is being able to why we want to have these capabilities days. So you can understand the kind of conversations that we're having with these customers, which are very, very different than the resellers that we bought. We bought them for their customers, but we bought them so that these kind of conversations could happen. And where you see the progress of where this goes to in three to five years, to answer your question, is how many of those reps are selling four more practice areas? Well, the Northeast is 80% now. Our goal is to get all of them cross-selling these initiatives, and these sprints are having that engagement. These kind of conversations were, are like, again, if I looked at all the resellers that we bought, not one of them would have been able to have the AI conversation that Chris spoke about. I got a call saying, "Help." None of them would have been able to have that conversation. That's just not a reseller conversation that they have. They go, "Okay, go talk to Accenture or CGI," right? And this is something that Converge can do. So I'm incredibly proud. I'm so glad we had this today. I see a lot of analysts that I've done a poor job of explaining this to, so, you got the guys now that can do it a lot better than I can. And David, the other comment I'll make is, it takes us two-three years to really ramp up these teams, right? So as we make acquisitions, a company that we acquired in 2020, that sales organization is where we want them today. The companies we acquired in 2022, takes a year for us to really get them up to speed. Then the customer sales cycles are six-nine months, right? So you, you have to figure, for us to truly transform an organization that we're acquiring, it's a two-three-year journey, right? So the fact that we haven't acquired in 2023 has allowed us to ramp up that enablement even faster, and that's the goal, right? Well, you look at the time that the management team has spent on these sprints. Last year, we bought 10 companies for CAD 1.2 billion of revenue. Our focus wasn't on the sprints and training up people. It was on buying those companies and integrating, you know, from more of a structure. The details now around the organic growth and these models and how the teams are working together, the management team has been able to do that this year, and that's really what you will now see the results of. But that takes time, focus, and attention. I think we're doing the right thing by focusing on that. Hey, Rob. When you look at the North American market and the European market, how distinct are they in terms of the clients and what they look for? Yeah. So I think from a client perspective, it's very public sector-focused in Europe. But when you look at the overall comparison, North America is three-four years ahead of where we are in Europe, right? So, you know, you have the one organization in the U.K., you have a number of companies in Germany. But from a go-to-market perspective, we're light years ahead here in North America with the skills we've built up, with the capabilities we've built up, the acquisitions we've made, right? We've really have, I'll say, call it phase one part of the journey in Europe. We haven't acquired the capabilities, that we have here around analytics and cloud and cyber. So what we're starting to do in Europe is take a guy like Chris and do a webinar to our U.K. customer base and start having conversations, at least around AI, to generate some of that thought leadership. But we're not, we're not where we are in North America or Europe today. Yeah, one of the things I'll say is vendor engagement. You've heard a lot about this, around the specialists, whether it be CrowdStrike's latest initiative around cybersecurity, or here's what Snowflake and the roadmap are doing t hose engagements happen first at the company level, and then at the regional level. We're not having those conversations to the same degree in Europe because we haven't engaged like that. This is where the time and the training and like these—when you buy a CBI with that kind of level of cybersecurity, their relationships in with a CrowdStrike give them that ability to go and do that, or with Snowflake. Those, the depth of those relationships we really have here and the engagement with the vendors, which will take time, we'll get there in Europe, but we're not there yet. I'll just ask a question here, especially, and that was briefly discussed on the talent acquisition standpoint. So now that Chris and the Newcomp Analytics is a part of Converge, there's a lot of demand for data management globally, like, you know, leave North America alone. Chris is one guy, Chris's team is one guy, and you said it takes two-three years to ramp up. At what speed are you truly hiring or training? And forget the account executives, I'm thinking more about the solution architects that you already had from a data and AI standpoint, and where is your new talent primarily coming from? Well, so realize, though, we bought Lighthouse, we'd had a team in the AI space, and we bought Essex. Buying LPA, Carpe Diem, and Newcomp, when you build by pre-built teams. So the whole strategy of having these teams of specialist, you know, companies that do this for a living was, that's all that was really in the marketplace. In the Pivot days, I would have hired a Chris, right? "Go talk about it. We have no ability to go and deliver it, but, you know, that looks great. We can kind of talk about it." These teams of people like to work on cool projects, right? They like to be surrounded by other cool people. We had lost a senior tech person to one of the large cloud providers, who came back after six months because they surrounded them with a bunch of junior people, right? You want to be around other people, so you're not the only one doing all the heavy lifting. But you talk with the global size. What, what do they do? Even on the analytics space, right? They have the, when you're signing the contract, you meet the senior people, then you get the new grads, right? That's not the model when you bought these specialist companies, how we built that practice. Now, you can kinda go through how we're now evolving the skill sets across all the different practice areas, but what allowed—we raised a lot of capital, we were able to buy some very specialized companies that I wouldn't want to have to buy today, especially in some of these spaces, because of, you know, what the capabilities that they're driving to our customers. But then, once you have that core, you can add to it. Developing that core from scratch is really, really hard. Back to the Europe strategy. In that strategy, do you feel it's possible to have the same kind of roadmap in, in Europe without making acquisitions? Can you take your solutions you've developed in North America and take them to Europe? Because, as you said, it's tougher to build these capabilities now. So it won't be as easily in, like, Germany per se, versus l ike, you know, getting Chris, hey, your U.K. vacation, you know, that'll work for him, right? But a lot of your resources as well, the time zones don't work. But because of the reputation we've built, especially with the vendors in North America, it becomes so much more straightforward, and there are all the models that we've built up. Does that mean that? Oh, blame the finance guy all the time, right? Absolutely, we can take those. Like, so what Chris is doing on the AI side, we can add that practice as a way of getting new customers. Like, I've never seen the kind of growth and interest, like, I think a lot of people that are listening in today, is because of AI. Our customers are the same way, and it's unusual. So usually, we'd have to, like, give people free alcohol to come to one of our events, whereas instead, they're coming to us. So using some of these unique capabilities that we have in order to get to the commercial sector, as Greg mentioned, we're very much in the education space, but I think in the U.K. in particular, that'll be easier, a little more challenging to do it in Germany. Yeah, and I think what we're doing is looking at solutions to Shaun's point, right? So IP4 G, which David's been instrumental in, you know, that does translate to Europe, right? There's other solutions that were built up on the cloud side that will translate, but it's gonna be harder to build up the technical resources to deliver the AIM strategy over there outside of managed services. Just to follow, so sorry, does that mean there's a right sizing of the footprint that would be possible in order to fully transition all at the same time, or you're happy with what you have? I'm not sure the right sizing. I'm not sure what that means, but the plan was always to follow the kind of strategy. Over North America, we led with Red Hat and VMware because everyone wanted to be hybrid IT. What the AI conversation is allowing us to do is come with a real present need that everyone has to allow us to have those different conversations from the existing customer base. I mean, you've heard from the cybersecurity, one of the key areas is K- 12, right? And higher ed. Well, that's an area that we tend to be in. Leading with cyber and AI probably make a lot of sense to get to the same result that we got to in North America, but it's all about how quickly that happens. Thanks. One question on NVIDIA. You've done pretty well on NVIDIA this year. Can you give us some case studies on how those hardware sales are translating to maybe managed services or professional services sales, and what kind of customers are buying those? I'm guessing it's more of the bigger customers, but if you can give us some more- Yes. So there's a couple of things. NVIDIA also has a bunch of partnerships. So there's a company called Vast Data, where they own 30% of it in the financial sector. B ut the, the GPU cards, you only buy them if you're interested in gaming or high-performance computing. So when you see they used to be our 20th vendor and now they're our 4th, that tells you that, like, it's a symptom of what we're doing. And why I showed the, the hardware sales is because all these smart guys are doing all the upfront work, that's just a symptom of what we're deploying. But I think we've talked about how healthcare, automotive, and finance are the three key areas that we've seen deployments of that. When you see the compute coming through, it means you've gone through all the advisory assessments, and you're actually deploying, and so that's where you've seen it. You will see this happen more and more in the future, though, as well. Yeah, do you wanna talk to the, the use case? Don't use the name, but just talk about the customer that used to buy cyber from us for a while, but they are doing now an AI workshop with us, right? We just completed that. So 'cause and I'll let David talk to some of the specifics of it, but ultimately for us, what we're seeing in those large infrastructure transactions is we're driving assessments, you know, $200,000, $500,000 dollar workshops around AI. So we're getting the, we're reselling the hardware, but the goal for us is get in there, do a workshop around AI, and then that's gonna lead to more software opportunity, more services opportunities, and I'll just let you talk to a high level on that one. Yeah, and those workshops are important 'cause it's not about. C an you guys hear me? And those workshops are important. It's not about the technology, it's— and Chris mentioned this a little bit in his presentation, it's about bringing the business users in, right? And understanding how can they use AI to enhance their business, right? To grow their profitability, to reduce risk, to reduce costs, right? And you get a lot of people in the room, and there's a lot of use cases that AI doesn't apply to, right? But at the end of the day, you leave that room with basically a boardroom presentation that they can bring on where they're gonna invest and where they're gonna continue to grow their business, or even create new lines of business as a result of what they learn in those workshops. Yeah, a lot of the time, those are, like, therapy sessions, right? So they'll come in the room, and we kinda speed date somebody from each department, and they say, we just say: All right, tell us your, where it hurts, right? And so, you know, when they trust us, they'll spill all their secrets, and they'll say, "This is slow, and these two systems don't integrate. I do data dumps and extracts out of this thing, and then I paste it into another system." And so, you know, we furiously take notes, and, and then we know where all the hotspots are. There's a question there. There are a lot of discussion today around AI and data analytics around your customers. So I'm just curious if you can share with me any examples that Converge itself has been using the, you know, the same set of tools to improve the internal optimization and stuff. Yeah. Do you, do you wanna speak to that, or you want me to talk about it? Do you guys maybe wanna talk about chat, internal chatbot? Sure. Go for it. Yeah, yeah. So actually, Chris mentioned this a little bit before, right? One of the things that we're doing. So we definitely wanna use the tools ourselves, right? That's for sure. We have a lot of the team members that are working on data warehousing for some of the things that we're doing. We're also doing some demos around some of our HR policies, right? So building chatbots to be able to review our handbooks and provide that to our users. Reports that we're building across the organization, right? To be better at our data, to be better at running the business, right? So whether it's AI, whether it's analytics, whether it's the data warehousing side, right, we are, I'll say, eating our own, eating our own, that's for sure. Drinking our own champagne. Yeah, yeah. That's better. Dana? Portage was mentioned as a resource, so I'm curious to hear in what context do you pull in Portage? Is it for a specific use case or a specific type of vertical? So what we were saying is the resources that he was including excluded the Portage resources. So Portage is a cybersecurity company, so they're a. We're just actually now running campaigns around their citizen portal to get to the U.S. Portage is only, its customer base is only Canada right now, but there are, they have a product that we can use. We've got a wonderful channel ourselves. We've gone through, and I think it's 596 of our municipalities and government-type organizations that are great potential customers for Portage. They just released their 3.0 product, which really reduces the implementation time and cost. So they're now ready for us to be a good channel to them, as we are to other vendors as well, and that really should help them get down to the U.S. So we're running a campaign with Portage, just like we would run a campaign with some of our other vendors as well. But it's outside of everything Shaun talked about today, right? It's really citizen portal-focused. Shaun P. Smart Shaun. Yeah. People spell our names the right way, though. Yeah, yeah. Any other questions? David? I have a question on the cybersecurity. So cybersecurity, obviously, it's one of the most prevalent topic right now, AI aside. CBI came into the Converge story two years ago. The customers that you had already had their cybersecurity service provider sorted. So how are you bringing the CBI practices within your existing customer base? So when you say that they already have it sorted, I would challenge that and say you'd be very surprised at how many have that, that sorted. When you looked at what he was talking about with penetration testing as a service, right? That's an offering that most of our customers, our mid-market customers, definitely did not have. And so I think they had their own customers that we've been crossing other things to, but that's been one of the most successful cross-sells. Every single one of our customers needs penetration testing as a service, and most of them do not have it. And so to say that we, It's not really that, oh, this is such a saturated market, it is not, unfortunately. Well, fortunately, as the case may be. Interesting, and it just goes back to the discussion that Greg had on your breakup of the customer base as well. How did you see that differentiated between the true mid-market and the enterprise customers, if you may talk about that? Yeah, so, so let me just finish one comment on the, on the cyber side, right? So when we acquired CBI in March 2021, we had a cybersecurity practice, right? So we actually ended up, based on the leadership that CBI brought to the table, we implemented them as our leaders across our cyber practice, right? So they became the thought leaders across our entire cyber practice. And what that did was give us more trust and credibility with our account execs and with our clients to say: Yes, we've been talking about cyber with you for the last three-five years. We just acquired over a 100-person organization that now gives us the scale and expertise we need outside of some of the things they did, right? So they brought new skills, they brought new partnerships. So now we can not only go to their clients and sell the rest of the Converge portfolio, but we've actually gone back to some of our existing cyber clients and said, "Okay, now we have penetration testing as a service. Now we have other offerings that we didn't have two years ago, so let's get back into those accounts and tell the cyber story again on what we do across all Converge." In terms of as you look at the breakdown of, you know, mid-market to enterprise, we don't do that today. We haven't broken down the numbers on how much of our revenue is coming from the mid-market space versus the large enterprise space. You know, what I can tell you is, as we're driving the large multimillion-dollar services engagements, those are in the larger tier accounts that we're in today. But we don't have specific numbers to break that down. I think part of the automated services are much easier to run at a smaller account, whereas, say, the more the handholding, it's much more cost-effective for a larger customer rather than a smaller one. A couple of years back, you put out a target, about $1 billion in services. I'm sure that's, you know, that's kind of pared back now. So how are you executing against particular number or- Yeah. So we- Yeah. Yeah, no. The part of it, though, is after our year-end numbers, what we're gonna try to do is set more KPIs on the finance side. So, Avjit's come and joined us and really focusing in on what is achievable. Obviously, we had some acquisition targets as well that we've gone now to much more organic. Our, one of the things we'll be focusing on, as I say, once we finish off the year and introduce next year, is around those KPIs. So nothing for you today. So first, I want to do capabilities and then say, well, we'll do no-- Avjit's training me up now. So, you know, numbers, thanks. Anything you'd add to that, Avjit? No, I think you covered it well. I think at this point, I don't know if a $1 billion professional service is the target. We're still working through whether that remains to be the target for our future as well. So we're still working through, essentially. Any other questions? Maybe just, I was curious to follow up on the, the earlier sales question. I'm curious about incentivizing the sales team. These are obviously higher margin type, recurring margin type products. Have you made any changes to the incentive structures for your sales? What's encouraging them to push these products? We have. We've made a few changes over the last couple of years. You know, the first change we instituted was, we do a club trip every year for the top reps, right? And as of two years ago, if they weren't selling three or more practices or driving 100,000 of recurring revenue, then even though they sold a lot of hardware, they weren't allowed to come on club trip. We've also put out incentives for based on various offerings that we want to double down on that we know are more profitable and higher value. We've given kickers out, to drive them, and it, it's a, it's an annual thing, right? We're always looking at the market. We're always looking at where we're investing and where we want to incent the sellers to drive more of those higher-value solutions, and I'm sure we'll make changes again, as we move forward. Seeing the results of these, since those? Absolutely. When you look at 80% of the Northeast selling 4+ practice areas, 60% in other regions, it's definitely working. I mean, we're definitely seeing the trend move in the right direction. Yeah, I understand the focus is on organic today, but can you talk about some of the capabilities you could acquire in analytics or cyber? Again, so we—like, the pipeline is still there. What we did was always partner with companies before we acquired them on the services side. So buying for customers is very straightforward. Buying for capabilities, it's the culture and the fit is just so important. So again, right now, especially where our stock price is, we're not looking at any acquisitions, but we definitely have active dialogues and pipeline and with some of the ones we're partnering with. All right. Well, thank you all very much for the time today. We appreciate it. As I said in the beginning, we'll do some surveys and get some feedback from you, and then we'll talk about when we do it again and what topics you want to cover. So truly appreciate the time today. Thanks, everybody. Thank you. Thank you.