Welcome, everyone. Thanks for joining us today for our 8x8 Investor update. We are going to handle this a little bit differently today, more of a talk show format with slides accompanying it. I am here with Sam Wilson, our CEO, Bryan Martin, our CTO, and Kevin Kraus, our CFO, and they will be here to answer questions and take us through. Before we get started, I want to transition to our safe harbor statement and a couple of other housekeeping items. I just want to caution, let me remind you that today's discussion includes forward-looking statements about future financial performance, including investments in innovation, focus on profitability and cash flow, and other statements regarding our business, products, and growth strategies. We caution you to not put any undue reliance on these and take no obligation to update. I also want to remind you that we will include non-GAAP financial measures, and the appendix to the slides will have a reconciliation of those non-GAAP to the corresponding GAAP metrics. With that, let's turn over to our regular content. Oops. Oh, sorry. You have a question. Housekeeping. Yes, housekeeping item. If you would like to ask any questions in the chat, this is how to do it. Hover over the bottom of your screen. The chat window or the menu will come up. Just click on the chat window, and you can enter your question. I will be monitoring that chat window for any questions that come up. Okay. I think, Sam, it is a good time for you to talk about why 8x8. Okay. I feel passionately about this because it's 8x8, and I'm the Chief Executive Officer of the company. I just want to remind investors some of the basics about what we do and how we do it, right? It's a large and growing market opportunity, and by large it's, I don't know, $100 billion, $150 billion, $200 billion. A really big number compared to our $735 million a year in revenue. It's super important that we remember that this is a large opportunity that is coming our way because we are still in the process of moving from on-prem to cloud. Our opportunity inside of the large TAM is a growing opportunity around the cloud version of it. That growth has slowed down from the heyday, like all technology adoptions. They slow down from the heyday. You still have a core tailwind around the on-prem to cloud. Second, voice network creates a structural advantage. There's this belief that with the hyperscalers in existence, the ability for software companies to create structural advantage, infrastructure advantage if you will, is changed. Maybe it has for some companies, but it certainly hasn't for us, right? We have a global voice network that we've been investing in. We offer PSTN replacement to 59 countries. We have users in 150 countries. We make billions of phone calls per year, and it transverses across our network. We believe this voice network becomes more important in an age of AI. I gave a talk not too long ago, and I showed a picture of James Kirk from "Star Trek" talking to his AI in the 60s. Gene Roddenberry clearly understood that Kirk was going to speak to his AI. He had no keyboard. He was not furiously typing away at 30 words a minute. He was speaking to his AI. I'm a firm believer that the next billion phone numbers used in the world will be with AI agents, and those will be used, and we offer a global voice network, and that is a structural advantage. We have a unified platform with native AI. What does that mean? We offer voice, video, chat, contact center, field service workers. We offer CPaaS. We offer it on one unified platform, which means common analytics, common administration, common user interface, common conversational OS, common capabilities that allow users and customers to mix and match that technology for success. We've re-accelerated growth, right? We've had four quarters of year-over-year growth. We dipped as we retrenched the company and expanded our product portfolio. There was much doubt in the investor community whether we'd grow again. We've had record revenues. Lastly, we've had record profitability in terms of dollars of profits over the last year or two, and we've used that to continue to de-lever the balance sheet, pay off debt, and drive more and more profits into the company. Remember, when we pay off debt, that means less interest. Less interest means higher EPS over time, all things being equal. I think these are just core aspects of what makes us a company, right? We're a software company in the telecom space. We have AI, we have a unified platform, we have global capabilities, and our customers value that tremendously from us. Okay, we'll come back to each of those as we go through the presentation. I am now going to turn it to Kevin to take us through the numbers. Yeah. Okay. This complements some of what Sam has already said. We are a growing business. Last fiscal year, $736 million in revenue. We serve over 52,000 customers globally. You heard from Sam, we're a PSTN replacement in over 50 countries around the world. We have a lot of third-party validation that goes along with our success. We've been a multi-year Gartner Magic Quadrant winner in both unified communications and contact center. Strong Performer awards for both unified communications and contact center in Forrester. We've got a lot of other customer success-oriented awards, lots of Stevies. We have a lot on our trophy case at the office. Very proud of what we've been doing as a company. Just real quickly, last quarter's highlights. Sure. Yeah. You heard from Sam already. This was our fifth quarter of year-over-year growth. We did $185 million in service revenue, $190 million total revenue. Service revenue up about 5% year-on-year. The profitability of the company, I will just say the multi-product customers is a metric that we really focus on here because multi-product customers tend to be stickier, higher retention, et cetera. All the things that we mentioned in our earnings calls. That customer growth was up 18%. A little bit nuance on the revenue growth rate. We bought a company called Fuze about four years ago. The people who follow us know this, and we've successfully transitioned those customers over to 8x8. After the migration headwinds end, or when you discount them rather, which is ending now. They've ended, we've migrated all the customers over. We had an 8% revenue growth rate, 5% with in total, 8% without the Fuze headwinds. On the profitability side, we are GAAP profitable. Last quarter, non-GAAP operating margin, healthy, nearly 10%. 22nd quarter in a row of positive cash flows from operations and non-GAAP operating profits. We focused on that. We want to generate the profits and cash flow to pay down the debt, for all the reasons you heard Sam just mention. We generated $17 million of cash flow from operations last quarter and ended the quarter with $92 million of cash and cash equivalents and restricted cash. We have a very healthy balance sheet that we continue to work on and improve over time. Great. Bryan, I do not want to leave you out here. You have been with 8x8 for a long time, and I think you are the best person to take us through the defensive moat that we have. We get that question a lot from investors. Yeah. It starts with what Sam talked about. It is that carrier-grade network in the cloud. It seems simple. A lot of investors wrote off voice long ago, but voice is the channel of choice that you go to for your most important conversations. When you need to call the plumber, or I miss my flight in the morning, I am not going to start texting with United Airlines. I am on the phone. I need a flight now, and that is the urgent channel that you go to. This little technology came along. We love acronyms at 8x8, and finally an acronym came along called AI that every one of our customers, it is the only acronym we use that I do not have to define what it is or what it means. The exciting thing about it for investors that have been with us through the migration to the cloud, industries like banking, finance, and legal, the late adopters of cloud are all early adopters of AI. Everyone is trying to figure out what it means for their business. How do they use it? They have got to go in front of the board, or their CEO and not just the IT teams anymore. That is the other difference is cloud was something we sold to the IT team. AI is something that we sell to every business, every department. The solutions, the early solutions, and 8x8 was applying AI to communications very early, way back before 2015. We were bolting the AI onto things that we were selling. I see a lot of that out there. I see a lot of our customers trying to bolt it on here, different departments bolting it on, and applying it to a subset of their data, and I think it is a huge mistake. I think if you listen to the salespeople coming in from your CRM suppliers or marketing has got this marketing tool and they have got a bolt-on AI solution for that, you end up with disparate AI solutions that are working on a subset of data. What 8x8 has really figured out across our communications platform is we can apply a universal solution that works on every piece of communications data that comes across our platform. You think about, we see all of your communications. We see every message that is sent between your employees. We see every communication and interaction between our customers and their customers, and we can actually apply a holistic AI approach to processing all of that data. That makes a huge difference in the outcomes and the solution that we can provide versus a piecemeal approach. That, we have applied it to ourselves. We were customer zero of everything we have developed, and we are now able to take those solutions and make them real for our customers. You are saying context matters. The AI is smarter and gives you better outcomes with context. Yeah. The next slide. We just have a few things here about the Global Voice Network, and I know that you've been instrumental in helping create this. So maybe just walk us through a couple of the highlights and then we'll sort of move over to problems. Well, again, I want to actually give Sam credit because he's been in the chair. Are we at eight years yet? I've been at the company 10, but I've only been the CEO for three and a half. Oh, well, time matters. It's dog years. Sam, I mean- 110. at the same time when the industry was saying voice is dead, Sam really came in and doubled down on our investment in voice. We've been investing in really increasing our presence, especially in Europe and North America, becoming a stronger, I don't want to call it a carrier, but we're really investing in the strength of our cloud presence. We've also now, you saw the numbers that Kevin went through. We have the volume to actually tie in with the tier ones out there. We're not having to go through wholesalers in order to get to the tier ones. We can interconnect directly to the tier ones. It saves our customers money because we're not having to pay those markups along the way, but it actually gives us better control of the numbering resources, gives us faster porting, which is a four-letter word in our industry. Porting numbers and dealing with number management is one of the hardest things to do in the voice world in any country around the world. Tying those services together, providing better toll-free services to our customers. When you think about it in the world of AI, people are looking for things that will be durable in an AI world. The world of voice, you can't go to pick your favorite hyperscaler AI provider. You can't go to a Claude prompt, to use as an example, and say, "Give me a toll-free number in Indonesia." You can ask it, but it won't be able to provide it. Versus 8x8, we can give you a prompt that can do that, and we can do it inside of Claude or OpenAI or Google Gemini. But the actual resources that provide that are being supplied by 8x8. We have those resources. It's an extremely difficult capability to run and run reliably. It's truly mission-critical. I go back to, I missed that flight. I've got to have those voice resources available. They've got to work 24/7, 365. They are mission-critical in the sense that we're running tier four trauma centers on them. They are life and death, literally. They have to work, and they have to work all the time, and our customers depend on that day in and day out. We've been doing this for a very long time. When everything works, no one thinks about it. That's right. It's only when they stop working that people realize it really is mission-critical life and death. We have an incredible team of teammates around the world. We employ more than 2,000 employees now, which I pinch myself every night because I remember the days when it was just a very small group of us, sometimes on a Friday night around my kitchen table, making this thing work. It is amazing what this company has become and the resource and network that we've built around the world. I just want to add one small thing because I know you highlighted it, but if you look in the upper left of the chart, that's voice quality. When you are that tier one carrier, there's no wholesaler in the middle. The call goes through less hops. The signaling is cleaner. Yeah. It's going to be a higher quality. In a world of AI, it's different than the legacy world that we used to be in. The legacy world of 7x24 support coverage was, I have a contact center in the U.S., I have a contact center in India, and I have a contact center in Poland, or whatever the case may be, and that's my 7x24 coverage. But in a world of AI, I'm going to have one AI agent who speaks 50 languages with 100 accents variants located in the U.S. or located in the U.S. and Europe for GDPR reasons. We need to transfer those calls. Those calls need to be crystal clear so that the AI agent can pick up that clarity and understand how and what to do effectively. Otherwise, the AI benefits won't be there. That is so important. Bryan, you're so spot on when you say no one notices bad voice quality like a cell phone. Nobody knows bad voice quality until you say, "Can you hear me?" for the fourth time. Yeah. Right? We see it all the time in our low-grade competitors. This is an easy place to cheat, buy cheap services from crappy wholesalers. I was going to use an S word. Offer low-priced VoIP, and the consequence is, yeah, your AI is not going to work very well. That's a great segue into where we're going from a vision. Let's start Sam, you just outlined part of the problem. Let's talk a little bit about what customer expectations are and what data fragmentation really means. Right. When you think about our platform, it is one platform that covers digital channels, Viber, Signal, WhatsApp, SMS, et cetera. Covers the voice side of the network. We have the capability, since it is all passing through our network, to grab the context, the interaction, the transcription of every single message. What we can do is put that together in one context of the situation. We know we can be able to see in a real-time type of dashboard what was said on the call, what was the messaging, what are those kinds of things. When you do that, you can easily capture context. One simple example, we at 8x8 have the capability of grabbing all of our internal calls, all of our external calls, unless they are specifically cited to not be transcribed, and say, what was the number one reason our customers were upset yesterday? Or the number one reason why people called our contact center yesterday? Or what was the number one thing on people's minds yesterday? Internal and external to our company. That is such powerful information. These are the things that people have guessed at for years by asking sales reps, "Hey, what is the customer thinking?" You no longer have to do that. You do not have to ask one sales rep who dealt with five customers yesterday. We can get a snapshot of every single customer interaction yesterday globally. We can slice it and dice it any way we want. Right? Number two is, from a customer standpoint, this allows a substantially better customer journey. I was on the phone with a tier one financial service company not long ago. It happens to start with an F and be located in Boston who runs our 401(k), and I had to have a simple thing done, and I had to repeat myself 5 x. 5 x I had to repeat myself, four of which I explained I sell a product, so I never have to repeat myself again. It was ridiculous. They had to transfer me from department to department to finally get to retirement services and get it done. This gets back into the whole thing, right? Data fragmentation, separation, systems of record, systems of workflow, et cetera. IT professionals do not want another product, an AI bolt-on, that has data located somewhere else in the cloud, not interlinked with everything else, and no ability to measure the quality of the performance. I think one of the biggest crazy things, and we offer products that do not do this, by the way, but one of the biggest crazy things is you ask the AI agent vendor, "How is the AI agent doing?" The quality management is from the same person who sold you the product. As an industry, are we surprised when they always go, "It is not my fault. It was perfect. It did everything perfect." You have no ability to see that. Those things should be separate. What does the voice network give you? The ability to separate those things out. So AI raises CX expectations. We see the data for Metrigy from others very clearly. Customers don't mind dealing with AI as long as the experience is fantastic. If you want the experience to be fantastic, it can't be siloed, it can't be data fragmented, and the AI agent has to have context to be successful. That's the problem. We can solve that. That's a great way to talk about what we're trying to do with- That's right. What does it take to solve that, right? Number one, you have to have one unified platform. Look, with every vendor, you end up with a separate set of contacts. With every PBX vendor or every tenant vendor is a different call recording system, a different administration, a different contract, a different everything. Stitching it together becomes a complex data science problem. I don't understand why you'd want to do that. We give it to you all in one platform ready to go. You want one workspace, right? You don't want half your vendors on one UC provider and another half on another UC provider and constantly trying to manage what all the employees are doing. What about all the employees that aren't knowledge workers? They need to be on something so you can capture what they're doing, what's happening. You need to scale without complexity, right? It needs to be easy. Seasonal staff, new locations, onboarding, et cetera. I mean, usage is now 26% of our revenue because we are actively working to get rid of complexity and make it easy to scale up and scale down. AI that works for everybody, right? It needs to be seamless, easy, buildable, customizable, those kinds of things. AI for everyone is not only every call, every meeting, but AI for me. If I'm 8x8 and I want AI in my tech support, it's different than AI in my billing engine, right? If I'm a retailer in pet goods, that's different than a retailer in women's clothing or a retailer of sporting goods, right? You want the ability to have AI that works for everybody. That doesn't mean a generic AI that sort of blah, gives blah answers. What it means is the ability to post-train and be successful in offering AI that works in every vertical situation where it makes sense. Because if you're in the medical healthcare industry and you're scheduling an appointment, it's pretty different than if you're scheduling your pet for a grooming thing. Right. Bryan, the next few slides are your slides, where we're talking about why every conversation matters. We want to make it count, but you're going to talk about why, and I'm going to let you just go with the slides. Tell me when you want to switch. Okay. We already talked about this a little bit. The voice is the dominant channel for really, really important conversations. My dishwasher's ruining my brand new hardwood floor. I'm going to call a plumber. But Sam already talked about the Star Trek example, that it's also the dominant. It'll become increasingly I can talk really, really fast, not as fast as Sam. But the AI can keep up. Like try to outtalk, you can't. You can go really, really quick. Go ahead and go forward. I think we made that point. This is what's really important is that the paradigms changed. I used to go to a classroom with my notebook, and I tried to take notes on what was important about what the professor was saying. The compute power of AI has changed the paradigm. I don't need to take notes anymore. I go to Sam's meetings, I don't need to take notes because I can take the transcript from the meeting, and I have a perfect record of everything Sam said. I have a perfect impression of what mood he was in during the meeting. Plus, you even have a to-do list coming out of this too. I know everything that he asked me to do, unfortunately. Right. I have no excuse to say, "Well, Sam, I forgot that you asked me to do that." Yeah, of course he does. Next week, he's going to know exactly what he asked me to do, I'm going to know exactly what he asked me to do and which things I didn't do. So now you have a perfect record of the conversation, it's flipped the paradigm of how we think about how we store that information completely on its head. I no longer need those notes. You can see at the very bottom a study that was done, they took 10 million call recordings, compared that with the notes that were in the CRM of those same interactions, guess which one was more accurate, right? The actual recording was a better record. Go forward- Hold on. I want to interrupt. Go ahead. We recently did something, I don't know if you know about this. We recently did something with one of our top customers. With the permission of one of our top customers, we asked them, we wanted to pull all their call transcripts for two days. Okay? Then we asked them, "What do you think the number one reason your customer was calling the last two days into your local stores, and what was the number one reason they were calling into your contact center?" They got both wrong. Because they were using notes or because they were- They were just using tribal knowledge guesses, ask somebody, et cetera. When you actually pull 17,000 phone calls, drop it into AI. Now, 10 years ago, we would say we're going to statistically sample 3% of those phone calls and spend 12 hours or 18 hours listening to these phone calls and take some sort of guess. With AI today, we can take all 17,000 phone calls, drop it in, get a cup of coffee, probably get a burger and fries, come back, and there's the answer. And with a unified platform, we're capturing those conversations, whether they're into the contact center or into billing or technical support. The local store. Exactly. The local store, the billing. Well, 8x8's taking it one step further. So the traditional way in the market companies are thinking about this equation right now is you're capturing every conversation between the contact center and your customers, or maybe between your salespeople and your prospects, right? At 8x8, we're capturing every conversation, every employee chat, what your employees are talking about. Billing department got an escalation, we want to know what our employees in the billing department are talking about that escalation. How are they resolving it? What problems do we have that are causing that issue, so that we can resolve that quicker? And we're tying all that information together. We are getting it omni-channel. We are getting it across all. Email- Digital voice channel. Digital, video, meetings. But- WhatsApp, texting. think about the old days. I'm going to go meet one of our customers tomorrow. In the old days, I want to know what's the last interaction someone at 8x8 had with that customer. I would go into my favorite CRM system. I would look up the customer. What do I typically find? Nothing. Because the salesperson that last visited the customer didn't even bother to take notes and put it in there. Right. Now, if I've got a recording of the last time that salesperson went to the customer, I've got a perfect record of what happened in that last interaction. Okay, go on. Go to the next slide. I don't know what other slide. This is. Okay. Then you can build, and I credit Jeff Pulver, a good friend of mine, for building this concept. You actually build what we're calling a business conversation stack. The way to read this is bottom up. You've got the actual conversation stored in the bottom. You actually store them in a very structured way, which is a global standard that 8x8's supporting, called virtual conversations. You actually now think about all the data we're storing. This is a company's most valued, because I got our employee conversations, I've got to worry about security, compliance. How's this being audited? Did we have consent to store this information? How's that being tracked? There's a whole layer of now that you're storing all this data, you've got to secure it properly. That's what that, is that teal? I don't know what that color is. Then you let the AI start comping on it. That's the next layer in the stack. Now you actually start getting intelligence out of it, and then you start driving outcomes at the top. That's how the entire stack works. That's a huge problem, but it's very valuable if you can actually turn this loose inside of your business. Now you're actually making a huge difference in the world, and that's what 8x8's supplying to our customers. You asked me a question about vision earlier, right? When I look out what we're doing three to five years, eventually what we'll do is as we run through this, it'll start to be a loop back to that AI platform. Right. Right? As we get that trusted conversation infrastructure, it's really easy for us to start the process of saying generic answers are no longer appropriate. For customer ABC, you can get a custom answer. For your customers, here's a custom answer for you to solve that problem. We will not only go from a situation where you can query the system and say, "What was the number one reason people called? What was my last interaction? What's happening?" We can actually get to the next steps, which starts to say, when the customer calls and he asks for ABC, for that individual customer, we can answer their specific question. We can get the context of who are they, what products do they have, what are they doing, what historically have customers in their customer journey done, all those kinds of things, and start to make this a cycle over time. It's personalization at scale based on each customer. We can do that for our customers, and our customers can start to do that for their customers. Right. I think that's a great way to transition into the product and the platform. The power of the platform, we'll skip through this pretty quickly. I think we've told people what we do, but we have our product at a glance. This kind of just gives you the overview for those of you who- All right. I want to stop you there. Yeah. Think about this from the journey perspective, right? We are known for the west, right? We are known as a unified communications company. Bryan, thank you for all your hard work. But we have like 500 patents in UC and everything else. We have been in the business since it was created. Since Gartner had the first Gartner Magic Quadrant, we were there. And that is what we are known for, right? We have been in the contact center business since 2011. We bought Contactual, et cetera, and we have been in the CPaaS game since 2019 when we bought Wavecell. But the part that I think people actually misunderstand is also that CX beyond the contact center, right? And it is one of our fastest growing products. Every business has a whole bunch of people, about 40% of their customer interactions, that are dealing with customers that are not in their contact center. Here is the secret. The secret is, with AI, the contact center sleeve may shrink over time. It is not shrinking for us today, but it may shrink over time. But as it shrinks, the CX beyond the contact center is going to grow, right? That is the key. We are not losing agents and therefore we are losing business. What we are losing potentially, and we are not seeing it yet, but let us just hypothetically, as AI gets better and better, we may have less need for a human being sitting in a contact center, sitting in a workspace waiting for the next phone call to be more of a person out doing a job who takes phone calls on the side. And we have built products specifically for that. And that I think is why it is one of our fastest growing product areas. That is the 8x8 Engage product. It is. Of course, we've already talked about our carrier-grade network that sits underneath all this and empowers it, as well as the communication intelligence, which is that ability to capture and analyze all the data. The last thing, I know it was on an earlier slide, but I'm super proud of this. I think people miss this platform right here is doing over 16 billion interactions per year. 16 billion. That is phone calls, SMS messages, WhatsApp, everything, right? 16 billion interactions across this platform. That is not an insignificant number. The sheer internal computer science to have 16 billion transactions running at five nines reliability every day is a pretty gosh-darn big moat. Kevin, we'll have plenty of time to talk about financials in a few minutes. I know that would be kind of letting me sit over there, but I think we're going to transition here to a little bit of a technical explanation of the platform, and Bryan's going to walk us through this. A little bit about data security compliance and data privacy. Yeah. I will just cover it at a 20,000-ft level. Again, I will read it just bottom up. The global network that we started the conversation with is at the bottom of this slide. The intelligence we have been talking about sits above that, but it is connected to it because one of the things that we see great value in is actually utilizing data from the network and with the network to drive some of this decision making and some of this intelligence. I think that is also very unique. A lot of the AI solutions in the market are really divorced from that network connectivity, and a lot of those messages that Sam was just talking about, the WhatsApp and the Viber and the SMS, and there is a brand new channel out there called RCS, which is, think of it as a very graphical kind of WhatsApp for old style text messaging. If you are not connected to the network, you are missing all of that data. There is a lot of data down there. So it may look strange to have intelligence down at the network level. I think it is very unique, and I think it is an 8x8 value add. The rest of this is we have a burgeoning ecosystem of partners, people like Microsoft and their Teams product, that we have been partnered with since, I think we made the decision in 2018, maybe late 2017. I remember very vividly, I was sitting with our head of sales at one of our largest customers, still a customer today in New York City with their CIO. He said, "Bryan, before you guys leave, I want to show you this Teams thing and see what are you guys doing with Teams?" I just remember so vividly this guy named Scott Sampson and I said, "What is Teams? Never heard of Teams." He said, "Well, come over here. A lot of my employees are starting to use Teams." I came back to 8x8 here in Silicon Valley, and I remember calling a special meeting and said, "We have got a new Microsoft thing we got to talk about. It is called Teams. I think it is going to be important, so let us talk about it." Sometimes it is better to be lucky than good. We decided back then to partner, not to compete. To this day, we are one of their largest global partners for connectivity. That ecosystem there, and Microsoft is not the only partner, they are just one of the largest ones. It is a big part of what we do. That connectivity and the intelligence and the data that feeds into our AI ecosystem and our capabilities includes the data that comes from some of those partners in that part of the chart too. The rest of it, I can just wave my magic wand and say the rest of it, Kate. Bryan, I want to add one small thing because I can't help myself. There's all this buzz in Silicon Valley about one small box here. Like Agent Assist, teeny box, $2 billion valuation. Voice and digital bots. Oh my God, there's like 400 of these things. Look, we're one of the few companies across our entire industry that actually has the complete platform. And we have voice and digital bots. We have micro persona finance. We have an enterprise voice network, et cetera. Everyone else goes to the customer and says, "Here's a box of LEGO. You figure it out." We're the company that's differentiating ourselves from our competition because we go to them and say, "We've already figured out how to put this together for you." And that is a key differentiator. In a world of cloud code, where any particular widget can be built relatively quickly, it's building the platform and the systems that will differentiate the companies, not the individual LEGO blocks. I want to emphasize that point, but also the security compliance and the capabilities that are built in. I was going to say that. We also bring that part of it, too. Right. All of this doesn't work if your data's not kept secure, if you can't supply GDPR in Europe, all of your security compliances in the U.S. We do HIPAA. We were the very first cloud communications company to do PCI, HIPAA, E911 emergency service. The list goes on and on and on. The FCC, in just the last four months, has put out over 300 pages on STIR/SHAKEN robocalling compliance. Yeah. This is a regulatory barrier. We meet it. We will meet it. We continue to meet it. We're awesome at it. We block robocalling every day. Yet, when people talk about, "I'll just go build a voice network." Sure you will. Start with a couple thousand pages of FCC regulations on STIR/SHAKEN alone, and oh, by the way, the U.K., France, and other countries have completely different versions of the same thing. I'm just picking one of whatever five boxes that are up there. Right. I just remember the days I cited those banks, financial, legal, the institutions that care about this stuff. In the old days, "We're not going to communicate through your cloud." These days- Right it is the best practice. Because we've got more than 2,000 employees who spend 24/7 of their lives worried about this stuff, as opposed to a bank that's got a little tiny department with half-time people that spend a fraction of their time worried about how to secure these communications. This is best practice now. This is state-of-the-art in the industry for security. We don't throw rocks because we live in a glass house. Right. Security and compliance are, they always have been the number one, but in this day and age, it is very difficult out there. We spend a lot of time at 8x8 worried about this stuff. I'm going to go back just one. Whoop. I went the wrong way. Sorry. Whoop. Never mind. We talked a lot earlier about how we could see every conversation and everything, but I want to make the point, and I think we'll go into it a little bit further later, that we don't use our customer's data. It's that we capture it so the customer can look at it. There's a data privacy capability. We are huge believers that customers' data, it's their data. We're not in the business- Right of holding data hostage, and there's plenty of people in this AI space that won't be ever able to say that. I think partners that we work with and end customers that are interested in talking about that, they should come talk to us because it's something everyone should be aware of. Yes. That there are walled gardens. There's walls going up every single day, and you need to know where your data is and who you're entrusting it to, and make sure you're working with the right vendors. And how much they're going to charge you to get your data back to you. Absolutely. One platform, every connection, but completely private. Okay. Now I'm going to go forward where I should've been before. The AI tailwind. We've been talking a lot about where AI is in the platform, where it's going. I want to talk a little bit, and this is where we're going to give Kevin a few minutes to shine, I think. Sure. Although maybe not right away. Katherine, when I saw your question, we will be able to answer that as well. I put together this little slide on the history of AI innovation at 8x8 because I think that a lot of people miss how early we were in integrating AI capabilities into the platform, and taking it all the way up to today. Bryan, if you want to give us a couple of highlights. Before you do, I think I want to mention one. Kate was really nice to us. She actually should have started this in 2019. Well, I was going to say. You remember when we made the voice bot? I didn't do this slide. We made the voice bot in 2019. It was a disaster. It was that text-to-speech, speech-to-text voice bot that worked like crap. This is the one slide she didn't steal from me. So much earlier. We've been doing this for a long time. It's just this is when it started to kind of get interesting. Yes. Yeah. It started to really work. Well, this is when we all became aware of ChatGPT. Yeah. And we were like, "Have you ever heard of this before? Yeah. I would just say, this is kind of the timeframe. It's even earlier than this, because I'm even remembering, I would actually credit a guy named Alton Harewood Yeah who started telling me, and hopefully he's listening because I invited him to this, but I think it was middle of 2022 that he's like, "Yeah, we're getting some amazing transcription results." In Scottish. Scottish is one of the worst dialects to transcribe. Yeah, we've all seen that. We were getting like 96% accuracy out of this little company, and we actually started working with OpenAI because of their transcription. Yeah, before it became a household name, it might have even been late 2021. I'll have to look. Anyway, yeah. Like I said, it's better to be lucky than good. You find some of these things before they blow the world apart. Yeah, I think what happened was you suddenly had this amazing compute ability to operate on vast data stores that just suddenly changed everything. That really is what changed the game. We had a team of R&D people that spotted it early and then immediately applied it to Studio, which hopefully we're going to have time to show. Let's move on- This may be a truncated history of- Yeah AI innovation. Just the positives. Kevin, we have some stats here on momentum of AI at 8x8, and I'll let you walk through a few of the things here. Sure. We have some exciting going on in the company. In the same vein how we talk about multi-product customers, we're also looking at customers who are purchasing our AI products. The exciting thing for me isn't just the numbers and the growth here, it's just thinking about how the customers are having such a better experience using our products. I had my own light bulb moment using AI in my daily working. To see some of these numbers here, like the 67% year-over-year increase in the number of customers with paid AI solutions is exciting to me because I know how I felt when I started using it regularly a while back and how it made my life better. You're talking about hundreds of customers here that are growing with the products and making their lives better and making the customer experience with their customers better. So internally at our customer and between our customer and their customers. 18% year-over-year increase in recurring revenue for customers who buy our AI products. It obviously translates into monetary benefit for us while the customers are benefiting from these products that we're offering. But these are really big growth numbers. 9% of our recurring revenue in the company is attached to an AI product that we sell. This is tens of millions of dollars. So these are real numbers now, and it's growing, and we're really fortunate that we're able to help our customers in this way. Just like three-product customers, we talk about how retention is better with multi-product customers, and AI can be one of the multi products that we sell. The retention, over 100% on average for customers who purchase an AI solution from 8x8. It is a good average for us. The size of the customers, 14 x larger on average for customers, the deal volume or rather the deal size, 14 x more than the average deal size for customers who are not buying AI products. There is huge benefit there to the company. On the AI portion of the deals where customers are running AI, there is about a 10% revenue uplift in those deals due to the AI product. Great. These are real meaningful numbers for us, and it is really just a really exciting time as we release all these products to market and seeing the impact that they have. Still super early. Yeah A lot of this stuff. I know I was looking at the data that you used to come up with these stats, and I noticed that even though enterprise class customers represent a huge portion of that ARR, the distribution of the size of the customers that are using this, we have lots of smaller customers using that. In fact, somewhere in the range of about 40% or so are what we would consider small, less than $25,000 ARR a year. That is the beauty of having such a broad base of customers, right? We have a big base of customers. It is over 50,000 customers, and we have a lot of opportunity to sell into that base. There are customers of all sizes that can benefit from it. Certainly, that circles right back to the TAM. Okay. Let us talk about AI Studio. This is the most exciting part of this presentation. Bryan, take us away. Yeah. AI Studio is something we launched into our customer base beginning of this calendar year. It spans every part of our platform. It is not a context in a product. It works with our telephony services. It works with our messaging services. It does not care about the licensing or the technology silos of the platform. It even works outside of the 8x8 platform. It works across our integrations. If you are integrated with Salesforce or one of our other integrations, it can easily do things with those integrations as well. At the heart of the technology is something that we call the Builder. Builder does exactly what you would think of it. You tell it what you want it to do, and you tell it in English, by the way. That is the first time we have ever had anything like that. You do not have to go to 8x8 university. You do not have to get certified. You do not have to know anything. You just have to be able to speak or write, and tell it what you want it to do. I know, Kate, you got super excited. That's right. You got to build something. That's right. Yep. This is 100% native to us. As everybody knows, with phase one of AI, we partnered with another company because we knew that phase one wasn't going to be the end solution. From our previous experiences with AI, we knew it was going to be temporary. The whole text-to-speech, speech-to-text was not going to be the end answer. AI Studio is 100% native to us. It is our code. It does not have partners in it. It is our stuff running on our platform in our world. We have made it available to every 8x8 customer. That is right. No matter what they buy from us, no matter what size they are, it is completely free of charge to use and build things. We even give them a bunch of, we call them credits. They are essentially tokens. Think of them as tokens, but for accounting reasons, we call them credits. Our customers can play with it. We send sales engineers in to help them get started if they need help. As Kate found out, you need very little help to get started. Kate built her own little agent. In minutes, literally, you can spin something up. The way we make money off of AI Studio is when a customer starts using what Builder built for them. It is a consumption-based model, and it has got behind-the-scenes LLMs. We support out-of-the-box Google, OpenAI, and Groq. That is what is built into the platform. But if you want to bring your own favorite LLM, you can do that as well. It's open platform. Here's some stats on what we've seen since we launched it to our base. I'll let Kevin characterize it in proper investor terms. Yeah. So look, we have lots of customers in the development environment, like Bryan said. Look, I just want to mention one thing about how we're releasing the product, right? We're releasing this, there's no upfront license fee. This is a land and expand type of motion. The customers will pay for what they use. So we're trying to make it as frictionless and easy as possible for these solutions to be deployed in the customer as quickly as possible. So that's where we can see, I expect to see a pretty big ramp. We've already had a ramp, but it's a pretty big ramp in this product area. This is a function of our three-year model, too. It just launched in April. Yeah. We've got a substantial number of customers, and they've already built over 3,000 agents. Well, that chart is as of August 22nd. Yeah. Which is like two weeks ago. Yeah. It's already massively outdated, right? Yeah. I know what the numbers are because I get a report on it weekly, and it's growing high double -digits month-to-month. Yeah. The way we have done it is, as Bryan explained it, you give the, call it freemium or whatever term you prefer to use. It is open. It is open to everybody. We are deploying it in such a way that anybody can use it, any size customer. It is picking up steam. It is great. Lots of customer excitement. Sorry, I am going the wrong way. Go back. I think you missed one of the key things, though. Right here. This is key. What is it doing, right? You can get a healthcare bot or you can get a reception bot or you can get whatever. Builder, because of the way it is built, can do just about anything that has an API or a data hook or a web hook or something that it gets hands on. It is being used across a whole range of applications, and this is how it eats those niche-y little bots. There is like 400, 500, 600 companies out there. But it has this capability to do it all, and it all deals with the fact that they are sort of communications are the thing that underlies all this. I am going to skip a couple of slides, and I am going to introduce everyone to IRA, our virtual investor relations assistant. We built this using 8x8 AI Studio. Bryan was very generous in saying I built it, but I did have a little bit of help from our IT department. What it does is it actually looks through everything, and it answers your investor relations questions. It has a number of tools that it can leverage. Some are voice only, and some are digital. It covers both the digital and voice channel. We built guardrails into it. It does not make up answers. It does not go looking out on the web for someone's opinion. It uses our financial information that we have posted on our investor relations. It is all the hedge funds out there. You cannot get material non-public information. We put those guardrails in, too. It took a little bit of time to do that. I am going to give you a little demo of this is the digital version. We will just watch that for a sec. I think it answers some interesting questions. There it goes. While it is typing, I should have said it is, I hate the word omni-channel, but it works across every channel that 8x8's platform supports. It can send text messages. It is fully digital. It is also fully voice-enabled as well. Let us be clear. It speaks, I think, 60 languages and over 100 accent variants. It speaks English, Wales, U.K. English, Scottish, Irish, and every other version of English that we have floating around the world. It understands all those dialects as well. Yes, it understands them. To any Australians listening, it speaks Sydney and I forget, East Melbourne, which I guess is a different accent completely. The digital version, since our IR site is hosted, is not yet live, but the voice one is live. I am going to go live. [Presentation] Hi, IRA. Can you please summarize 8x8's most recent financial results? [Presentation] All right. Thanks. [Presentation] Sure. [Presentation] Yes. Can you tell me what was 8x8's most recent annual guidance for revenue? [Presentation] Not really. One last thing. Can you tell me how can I talk to a real person? [Presentation] No, that's it. Thank you. I'll call them then. Even with the- [Presentation] You could have had it transferred directly to you. Let's see how he does with our Spanish. [Presentation] Immediately transferred. It is so mind-blowing to me. It is. It is so mind-blowing to me. It really is. What is so- I am going to move on to the next slide, is I did not give the prompts for what we wrote for IRA, but Bryan shared with me the prompt that he used for the perfect CTO assistant. Is that what this is? Yeah, the perfect CTO assistant. The point of the example isn't that IRA's some breakthrough agent. Although, I will say our agents are. You get to pick the voice. You get to pick, as Sam said, the language, and it will default. If you start speaking Chinese, it'll go to Chinese. You can interrupt it. The latency's amazing because this is coming directly in. It's native to 8x8's platform. We're not going out to some third party, so that you see the back and forth is very natural. We're not hopping across a voice network. But the point of the demo is not to say, "Hey, my agent's better than XYZ's agent." The point is Kate built the agent, and she did it in a few minutes, and it's so easy to do. I just wanted to show you behind the scenes. This is a little application that's running on my direct dial number that rings all my devices, and I get between 30 and 50 junk calls a day of people trying to sell me AI, and I get really tired of it. I just want to show you how easy it is. There's something that lets Kevin, Sam, or Kate, anyone that works at 8x8, I want them to be able to reach me 24/7. But everyone else, I really don't want them to be able to reach me unless they know the passcode, 1444, to get through to me. So all of you investors know how to get through to me now. This is literally all I told Builder. I said, "I need a voice agent that only lets employees or people that know my passcode through." That's literally it. I typed that in. Go to the next slide. Builder went off for 30 seconds, and it literally gave me a much more formal, structured version of exactly what I typed, except it's now. This is what's left in my application. If I ever want to change the code, or I want to change the rules, or I want to let. Who's on the line? Katherine. If I want to let Katherine through on her mobile phone, I can add Katherine to the script. This is how I maintain the little application. Then one more screen. Last screen. Then I say I want this to run in Google Gemini because they're our favorite partner. I pick the voice that I want spoken to the people calling. I pick whether I want all the calls recorded or whether I want a transcript, and that's it. I just say go, and launch it, attach it to my phone number, and it's done. It literally, when I put this up, it took. Actually, you can say, "Hey, Builder, test this." Kevin had trouble getting through to me one Sunday afternoon, and I went back into Builder, and I'm like, "Hey, my CFO couldn't get through to me today. What the F? Can you go check why Kevin couldn't get through?" It's like, "Oh, yeah, I see what happened. You want me to fix it?" I'm like, "Yes, I'd like my CFO to be able to call me on a Sunday afternoon. Please fix it." It did. It's literally that easy. Even the little things that you can't really go back into it. That's what we're trying to. It democratizes every one of our customers' abilities to use our platform and customize it and make it do what their business needs it to do without having to come to us and say, "Oh, can you guys do this or that for me?" Now, anyone Right. Any one of our customers and anyone that works for one of our customers can go customize our stuff for them. Make it work for their business. Makes sense for small business, mid-market. Everyone. Enterprise, everybody. Everyone. Yes. Back to IRA. We talked about in past earnings calls and so forth about case resolution using AI and so forth, right? This example got perhaps the case resolved. Think about it from the standpoint of the experience that you can have with your customers that require human connection. For us, it could be Kate could spend more time on the phone with investor that needs to have Right. the human back and forth experience. Maybe the call is a little bit more detailed, so it's not just about, "Hey, when is your next investor? When's your next earnings call?" Just like a bank could say, "What's my balance?" right? Right. Well, okay, but take it one step further. That's clearly one in IRA's clear one, but that's practical. Take a bank that wants to, because we have a bank that does this, that uses AI Studio in conjunction with AI routing and says, "Okay, here's what I need you to do. First, when the call comes in, I need you to figure out what the person needs, authenticate them." Remember this used to be done by a human. No, I need you to authenticate them. They can pick one of three different ways. I need you to SMS message them. I need you to get the SMS message back, do the OTP so that I am 100% sure fraud is being committed against my bank. I need you to talk to them, and then I need you to route the call to the agent with the skills that are most likely to be able to help that person with their problem at this exact moment. That's the future. That is, and that's that mass personalization. Mass personalization. That you can achieve when you have that full context, the SMS, and you can build. That is a great thought to keep in mind. Kevin's going to shine. All right. We are going to turn to the financial model. It is just a few slides, so we will not take very long. We are a little past the hour here, but Kevin is going to walk us through. Sure. You heard earlier, look, we are back in growth mode as a company, five quarters in a row of revenue growth. We have extended our high-level model, for the public to consume here. Clearly, we have been driving our revenue growth with platform usage. We have shown that growth over several quarters. The long tail Fuze customer attrition is largely going to be behind us. This is the post-COVID created headwinds, and as we migrated those customers over. Again, excluding the Fuze headwind, we are growing much greater rates. We have said 8% last quarter versus the five or so that we reported. We have good revenue growth happening in the company right now. We have demonstrated that over multiple quarters. On the gross margin side of the business, we have publicly mentioned this. There is a different margin profile for usage or consumption versus our subscription business. We are focused on gross profit dollars and operating profit dollars and cash flow generation, for our investor base. We use that cash to pay down the debt. We are less concerned about the margin percentage than we are with the dollars that accrue to the bottom line, to the gross profit line. A little bit more about the platform usage. I will restate, it is a lower gross margin percentage, but the operating expense requirements are much lighter than a standard subscription model. More falls to the bottom line from the gross profit line. We can enjoy that bottom-line profitability as the platform usage portion of our business grows. In our model, we have from 2026 - 2027, in our return to growth model, we are seeing a relatively flat operating margin, down about a point year over year, but we are trying to preserve those dollars, and the dollars largely are being preserved bottom line. Again, generating the cash flow so we can use that for debt service. On the multiple years here that we are showing, the past three years or so, you can see that the composition of the revenue, and where it came from. The Fuze customers revenue has gone down over time because it has migrated into the 8x8 revenue base. The headwinds largely behind us. We fully migrated those customers at the end of calendar 2025. You can see the revenue growth here, 6%, 5% or so. 8%, rather, without the Fuze headwinds, 3% total, with all in here. For the full year, we are showing growth, in our guidance midpoint, mid-single digits. Next chart, I think we have a longer-term view. On the three-year model, we carry this out to fiscal 2030. CAGR numbers for three years. In total, the revenue 8% CAGR, from 2027 to fiscal 2030, with platform usage growing to about 20%, a CAGR basis, and the subscriptions growing 2%-3%. This is not too different from what we have seen from a platform usage perspective. Now we are growing, 60% or more each quarter, but this is a three-year model. Our growth drivers, continued adoption of our AI products, continued consumption growing in the business and the retention of our existing base on the subscription side. I would add, you get the law of large numbers playing in the platform usage. You also, this is roughly what a consolidated market estimates are for growth. We are growing with the market, if not a little bit faster. We are anticipating that. Let me go to the next slide, Kevin, which is what we are looking for in profits. Sure. Profitability. We went through the 2026, 2027. There was a lot of numbers on this chart, but fundamentally what we are seeing here is the revenue mix of fiscal 2027 guidance, 25%-30% platform usage. We expect that to go up over time, and that is no secret. We see the growth there becoming a bigger It is fast. It is the fastest growing component of our business. 35%-40% of the revenue in the three-year target model, with 60%-65% being on the subscription side. There is your 8% CAGR. Other revenue, we are holding it roughly flat at about $20 million a year. This is the product revenue and the deployment services revenue, things like that. Gross margin. We have a mix shift going on, which I just said, and we have been saying in our earnings calls. Again, we are seeing this may be four points this year per our guidance, and the mix shift will continue. Where we see it in the low to mid 50% range. But profitability of the business in dollars, and in margin percentage for operating margin, we expect to increase over time because of the high scaling of our business, particularly around the platform usage portion of the business. So focused on operating profit dollars, focused on continuing cash flow generation so we can move to continue paying down our debt, which I believe is on the next slide. Over the last few years, we have paid down 40% since the end of 2023. It is about 44% since the peak, which was August of 2022. So we have done a terrific job, I think, of paying down our debt with the cash flows that we have generated in our business. Again, it has been 22 quarters in a row of cash flow from operations generated. We do use that to improve our balance sheet over time, and we have been doing that for years now. We paid over $200 million in debt, as you can see in this chart. Our ultimate goal being getting back to negative net debt, if you will, or the cash plus debt is a positive number. We have done a really good job, in my view, of taking down our leverage ratios, as you can see here. Just a few years ago, before it is on the chart, but we were at like 6.5 x leverage. Now we are down to about 2.3x with the objective to go to zero or better. We are on that trajectory, and we continue to make improvements because we are very disciplined about how we manage the business, investing in the right areas to grow in the right areas, which we have discussed AI being one of the key areas, and continuing to generate the profits and cash flows so we can get this leverage ratio down further over time. I think that is the last financial slide. I am going to try to. Yep, there we go. I am going to send it back to Sam to sort of wrap it up. Look, I think we told a good story here. Monster market opportunity, competitive barriers to entry, profitable business model, re-accelerating growth, big moats compared to our competitors and where the industry is going. An AI story, which is a big part of the growth industry today. I think we have it all. I think sometimes people do not know us and think we are the company of 10 or 20 years ago, but they do not know what we are today. As this chart shows, we are these things. Re-accelerating growth, paying down debt, and AI driving growth. When we run out of debt, we'll start buying back stock. Or lots of other opportunities. Or lots of other opportunities. Thank you everyone for joining us today. Really appreciate it. We will take any calls or any questions that you have, and I think that wraps it up. Thank you, everyone. Thank you. And thank you to Kevin, Bryan, and Sam. Thank you, Kate.