Some people in the firm who grow up in their career and they're marketers, or they're in IT, or they're in finance, and those are essential contributors to the success of these businesses, but really it's only about 20% or 30% of the population of these firms, contrast over here. The vast bulk, majority of the people in these firms start out their career as analysts or associates, and they figure out which kind of specialty they want to learn and focus on, and they move up in their career through a variety of levels, and they aspire to partner or managing director roles at a later stage, or maybe a firm leadership role at a later stage. They're not specifically marketers or salespeople or IT specialists or finance. They have a very well-rounded set of responsibilities in their professional domain. It could be M&A deals, or it could be particular types of capital financing, or it could be litigation of various flavors, right? So it's that specialization of expertise that really defines the professional as they move up in their career. And so if you imagine how do you build software for an organization like this, it's very different from how you build it like this. And to the extent that the horizontal systems have made their way into these markets, you generally see them concentrated down in some of these functional departments rather than at the professional level. And so our whole strategy as a business is to recognize the unique shape of this organizational model and to build a modern AI-powered cloud platform for that shape of organization. In addition to the structure, what actually happens operationally inside these firms is quite different too. So one of the unique things about these firms is that they're bringing on new deals, new projects, new matters, new engagements continuously, and they set up expert teams to deal with each of the clients, each of the opportunities, each of the projects, bringing together all the experts and the expertise across the firm into a client team or an engagement team or a matter team or a deal team in a way that does a whole series of things for the people working in that. They're developing their professional experience because these teams have a range of professional experiences that are coming together. They're bringing together experts who are going to help create the right outcomes for their clients. They're generating knowledge and expertise as they go through the work of that project. And if you think about how these firms really build enterprise value and communicate to their clients what their differentiating skills are, it's the aggregate history of all the deals or engagements or matters that they have executed over time. That's the experience of the firm. And when you watch them go and pitch to their clients, they produce a pitch book that has a list of all the deals that look like you or all the engagements that look like you, and that's the way that the firms compete, and it's the way the professionals compete and build their careers. So there's this concept of experience and expertise built into the model. One of the trickiest things if you try to build software to support this operation is that these firms also have very complex obligations when they take on these deals or these matters or these projects. Every one of them has their own engagement letter which has been negotiated. All the issues that have to be figured out for each client are specific to that engagement or deal. Sometimes the clients will negotiate an overarching agreement under which each of the individual engagements have to be managed. And so the people assignments and the fee structures and the information governance in particular has to forever respect all those promises that were made. The complexity of this as the firms have scaled and become more global enterprises with thousands potentially of partners around the world taking on business in 18 different ways, sometimes calling on different parts of the same end client from different parts of the world with different aspects of expertise and value proposition, trying to keep all that straight in the information system is almost impossible by hand, and it's completely foreign to the way that traditional enterprise systems have been architected to deliver. So this whole series of unique traits about the way that these firms operate have been central to us from the very first days of the company. We built the company in a bootstrap strategy starting all the way back in 2002. We went to get a patent for our technology, and the patent lawyer gave us his application, and he said, "By the way, my law firm is all screwed up in Zurich. Can I buy one of these?" And we got started in legal that way. And we built the whole business from the beginning with a bootstrap strategy working with the CIOs in these firms who were struggling with the classic horizontal software applications. And they were building their own software. And when I got to the company, it was about nine people, and I just found this fascinating. Why in the world are law firms building software? It's a sign that the software industry is not building for them, isn't meeting their needs. And so over the years, as we grew the company, it was directly in communication with the CIOs looking at what they were struggling with, looking at the areas where the traditional horizontal software wasn't connecting, and where they were, as a result, trying to build their own. And they said, "Hey, can you all be our commercial supplier?" And really, the way that we were able to grow the company was by working directly with these people, solving their issues problem by problem, starting at the very deep data technology layer up to a whole application space. So if you look at the expansion of the business up to our IPO, it was a whole series of iterative step-by-step expansions from the very earliest data integration technology into additional organically developed technology areas like our Time product, like our Compliance product, moving into the marketing and BD functions. These were all invitations from the CIOs and then ultimately the other leaders in these firms. These are areas where the horizontal stuff doesn't work. Can you all help us? And so they led us that way. And then financially, we had the great benefit over many years of bootstrapping to start to work with some of the private equity investors. So Great Hill Partners was our first private equity investor. They came in in a secondary transaction. We didn't actually raise money there, but they bought out some of the original founders who were no longer with the company. And then Temasek came in in 2017. So with their participation in the business on the cap table, we got access to some of the private credit markets, and we were able to do some M&A. So we did use M&A even as a small company over the years, and we acquired technologies that could help us answer these points that our advisory boards were raising with us. How could we help them? And over the years, we built out a whole series of extensions to our technology, and some of those led us into adjacent markets. We started getting referrals from the accountants, the consultants, the investment banks, some of the private equity firms, and then some of the acquisitions already had a footprint in some of those adjacent industries. And we were very careful in our selection of whom we were acquiring to make sure that we were bringing in technologies that fit this unique operating model of the firm. That was a key filter for us, to make sure that people understood the technology architecture that we needed. And so we get out to 2021. We'd reached a pretty material size, and we had a great opportunity to bring the company public. We raised some money in that IPO, and we paid off all of that debt. So the company's debt-free, and we got here without actually raising primary capital. We were very excited. That was the first time we had to do that. And from that point, we were able to start to form some very significant relationships with some key partners like Microsoft, like KPMG, as we started to expand into a more significant size of client base. And then throughout this period, all the way back here, we were starting to do AI work built into the technology, and we rolled out a whole series of AI solutions. As AI advanced, we were building that into our platform. Then today, the generative AI thing has captured the imagination of the whole world, and we feel very prepared to be the people who apply generative AI to this industry building on our history and tradition. You can see the whole experience of the business has been deeper and deeper understanding of these special markets and a technology platform and a business strategy that serves them and expands into this gigantic marketplace. We think there's a huge opportunity to continue this and grow the company from here. Competitively, there are many aspects to what we do and what we've learned over these years that make us unique. One of the ways that we are unique at the core of the technology platform is the original Industry Graph data model technology that we built into the platform. This is a way of storing information and manipulating information about the business of the firm that accurately reflects the complex ecosystem that we're participating in. So if you think about the way that investors look at potential companies, you might have a private equity firm selling an asset. The private equity firm has a whole series of advisors that's helping them to do that. The asset is interested in getting as many bidders as they can, so they bring in a lot of other bidding groups which might have an investor and some bankers and some lawyers and some advisory consultants all participating in that auction process. That whole ecosystem each plays their own role in how that deal occurs, how that auction occurs. All the people who are working in all of those firms, each with their own professional specialty, really want to know who's doing all the different types of work because that professional network is what's going to help them win and pursue deals. Who won the deal? How did the bids go? Who were the people in all of those? Who were the intermediaries that introduced us for the first time? The kind of relationship map that people try to keep in their heads is very complex for an individual deal with all these players. And then the next day, there can be another deal where those same people are configured entirely differently. The people that you were bidding against yesterday can be on the same side working with you today. If you actually try to model all this and help these professional firms accurately get a picture of their universe and all the ways that they want to know all the different types of relationships, you need a different structure than the traditional linear make a widget and sell it through a pipeline architecture. This Industry Graph data model is at the core of our platform, and it comes directly from the uniqueness of the industry model itself. That's one of the things that we built into the baseline of the Intelligent Cloud system. Everything that Thad's going to talk to you about is built up from this unique architecture at the core of our system, and it's totally different from the way that the classic CRM, ERP systems are architected. So we strongly believe that it's very difficult to replicate this whole system because at the core, the data model is actually differentiated, and for good reason, to meet the unique needs of this market. It's why when we introduce any of our solutions to the marketplace, the professionals say, "Oh, this is actually how it's supposed to work. This is what I was always trying to do. This is what we were trying to build internally." They just have that experience because we have the data architecture right. Now, as we've built the business over time, there are many additional differentiators. Compliance is a key one, and there are others that Thad will talk about. But I just want to give you that anchor point because I think there's a real technology differentiation at the core of everything we do that's been built over many years and is purpose-built for this industry that's hard to replicate anywhere else. Competitively, then, we really have three buckets of folks that we compete with. There are point solutions in the market that actually do understand how these firms work. They tend to be smaller solutions. There's the horizontal players who come in with a big platform, and they're great. There's a lot to offer from those systems, but if you actually try to deploy them in the firms, they run into this problem. They try to do it with overlay consultancies usually who say, "I'm going to verticalize this platform for you." It's a good strategy in the absence of an alternative, but when we come in and show a purpose-built solution that has the correct data model all the way up, people say, "Oh, that's what I've been missing." And then there's a lot of in-house built software still in the market. So a lot of what we're doing still is replacing the attempted solutions that the firms themselves have invested in. We've reached a scale now in the cloud with security, the Microsoft partnership, now AI, that it's just hard for any individual firm to keep up the investment pace compared to what we can offer. So overall, we're bringing a very well-rounded, highly differentiated story to our clients, all the way from the expertise of the team and the company through the purpose-built solutions that are really designed for them. We've reached a scale now where our platform is pretty comprehensive. We're bringing a lot of applications and products to the market today that are all integrated in a single system. It's infused throughout with Applied AI, and more and more so every day. You're going to see some more of that. We're increasingly viewed as the leader for this end market, the vertical industry cloud company for this market, and I think that reputation has really helped us. Frankly, I think the IPO and coming public was a big part of adding that credibility to us. Then the partnership network, relationships with people like KPMG, Microsoft, and others are really reinforcing the leadership position that we have. Then you're going to meet some of the management team here today, but you're going to hear a fluency with the markets that's very difficult for anybody else to really replicate. And if you look out from here, what's the opportunity in front of us? There's an incredible number of ways to win, which give me a lot of confidence that we can really grow this company to significant scale. As you have talked with us about, we have a land and expand strategy, so there are more clients for us to win. We win more every quarter. We do have a very strong footprint, but there's a big market here, and there's many years to run to win new logos. But we also don't just win them the first time. The comprehensiveness and the scale of our platform now allows us to grow very deeply inside these firms, across the many practice areas or strategy teams, as well as into many aspects of the firm's governance. So the expansion opportunity is huge. And then, as you all know, we're moving some of our last remaining on-prem clients to the cloud, so that's an opportunity for SaaS growth that Dave's going to talk to you a little bit more about. As we do all this with our existing offering, we're also innovative. We've had a strong organic R&D tradition. We're bringing out new technology and new products regularly. You're going to see a bunch of announcements here that talk about the new solutions that we can bring to market and monetize. We have a lot of geographic expansion still yet to go. There's many parts of the world that we're not serving. We've started to expand gradually into some of these other areas, but it's exciting to be able to bring this whole platform geographically. One of the things that's unique about these end markets, because they're so specialized, we can go deep into many of them by expanding inside the subverticals, and you're going to see some examples about that. On top of that, we've had experience successfully seeking out and acquiring additional technology that we can build into our platform and monetize through our client base and increasingly the partnership ecosystem. We've talked on the recent call about our strategy to get more leverage from our partners. So as we grow the business from here, we think there's a very significant range of flexibility and opportunity for us to grow the business in several ways. And then finally, this has captured the world's attention. The GenAI moment has done the work for us. All the professionals want to know, "How do I get some?" And it's one thing to enjoy how ChatGPT works kind of in the common parlance, but what is it going to do for me in the business? And I think this is really where we are uniquely positioned for this market. The click. Well. Can somebody help me advance? I can tell you about it. Thank you. So the angle on generative AI that we're taking is to recognize that, like the cloud transition and the digital transformation opportunity that we're still going through but has made a lot of progress in many markets, the vertical specialization of this generation we think is going to be equally, if not more powerful, for AI applications as it was for cloud. If you like the vertical industry cloud strategy, you should love the vertical AI strategy because the real release of the potential value of generative AI is if you can build it into the specific industry solutions of the marketplace. And so that's our strategy, and you can see why we're perfectly positioned to be the people that create the vertical AI generation for this market. What's particularly exciting for me is that this end market that we call on, all the professionals who are working in each of their areas of expertise, they really trade on their intelligence in the first place. They're not manufacturing widgets and selling them through a pipeline. They're trying to survey the world and the markets and the issues that are valuable to their clients and incorporate all this massive information and filter it and summarize it in a way that really helps them maintain their expertise. Then they're trying to pitch on the basis of that and win business on the basis of that, and then they're trying to deliver value based on that. These are the ultimate knowledge workers. And so for generative AI to come along and propose to help people with that kind of work, I really, honestly, it's an outsized potential opportunity for this community if we can figure out how to bring the generative AI techniques to bear on exactly the types of work that the professionals here are doing. And that's the reaction that we get even from the managing partners at the firms who were not very techie 20 years ago, frankly. But today, when you talk to them, people know, "If I'm going to compete as a business here in this next decade, I've got to figure out how to take advantage of the potential of generative AI, but I need something that works for me. I need something that works for my professionals. They've got to be able to absorb it. It's got to speak their language. It's got to be built for them." That's where we are. We think we have an unusual capability to go create this new world for these folks. That's the framing for our brand update here. The intelligence, that is, at the core of how our professionals compete, it's also the intelligence at the core of AI. How are we helping people manage this giant set of information and use all the modern AI techniques and generative AI techniques and applied, applied specifically to this end market, all of our years of study, and Thad? We get it. It's just beautiful. I mean, I just love it. And because I think it captures so clearly the strategy of the business, the opportunity in the marketplace, the uniqueness that we have, the difficulty of someone else to do it, the scale of opportunity in front of us, we're right there. So, global leader, unique needs of the professional financial services industry, an industry-specific data architecture that creates a wide competitive moat, several drivers to long-term growth, years of experience already in applied AI, a very large total addressable market, and from our bootstrapped history, we've been cash flow positive from the beginning. So the discipline of the current era where you've got to show profitable growth is second nature to us. And so this whole story is going to take place in a profitable growth framework, and we've already proven we can do that for many, many years, and now we're doing it as a public company. So I think you should have a lot of confidence in where we're going. Okay? All right. That's the big picture. I've touched on a few themes. I want to invite my colleagues to talk a little bit about some of the aspects there. Let me introduce Thad Jampol, one of the co-founders of the company, and our Chief Product Officer. Thank you. Thank you, everyone. Good to see you. Well, there are these moments in technology, which you all know well, where there is a step function in advancement in sort of the state of the art of the general technology, horizontal technology world. And we've seen this again and again with the internet era, with smartphones, with cloud. And there's this special relationship that happens. So after you get this step function advancement of the general technology, there's a whole wave of value creation opportunity, of wealth creation opportunity that emerges by applying that technology, by applying that innovation to all of these different specialized domains and specialized niches and industries and verticals. And I think we are very much in this moment right now with generative AI. And as John said, this is a very specialized market. There is a specialized business model. There are specialized operating requirements. There is just specialized partnership culture. Because of these differences, this is one of the reasons why the sort of digital transformation wave has not really returned the same level of outcome and benefit to the financial and professional services world as it has to conventional companies, conventional sectors. The same pattern is repeating itself in this era of generative AI. This is why we built the Intapp Intelligent Cloud. This is purpose-built for professionals. It is purpose-built for all those nuances, unique characteristics that John talked about. I'm just going to sort of quickly walk you through a few aspects of this cloud. I also want to call out. John talked about the Industry Graph data model. These are examples of product and technological defensive moats. These are areas within our software that will be incredibly difficult and time-consuming for even the largest horizontal software company to be able to deliver. So let me start with industry solutions. Ben after me is going to go into a lot more detail on this, so I'm going to go through it pretty quickly. But this is how we leverage the hyper-configurability of our no-code, low-code platform to create these tailored experiences, not just at the industry level, but at the subvertical level and down to these expert teams, these practices, service lines, strategies, asset classes. This is where we get the professionals who have been used to pretty generic one-size-fits-all departmental software to say, "Oh, this was built for me. I get it." There are a set of very complex industry-specific workflows that exist in each of these markets, and we have a whole set of applications and products to support those. On the kind of the compliance side, we have conflicts of interest to sort of navigate a lot of the sort of strategic, commercial, and ethical decisions that firms have to make before representing or taking on business. New Business Intake sort of orchestrates that workflow with a lot of enhanced due diligence. There's a lot of AI embedded in each of these. We have a Terms of Business product. Terms of business, think of it like obligations management. So often, for firms to represent or take on a business or do a deal, you have to make promises. The promises could be billing promises. I won't charge a first-year associate. I won't charge for research. I won't charge for a telephone call. There could be a whole range of these different ones. There's engagement letters, NDAs, outside counsel guidelines. I'll talk more about that in a minute. Then our ethical walls, confidentiality product. This is the market leader within our sector. We have hundreds and hundreds of firms who rely on this every day to ensure that sense of information is kept safe. This is going to play an outsized role as we're entering this generative era, which I'm going to talk about in a little bit. In Intapp Time, we have time entry, time management. This was one of the first places where we used AI. John talked about that AI is not new for us, that we have had AI in our products for over 10 years. These are different forms of AI. So there's rule-based algorithmic AI. There's machine learning. There's deep learning. This is Intapp Time. So we go out and we capture what every timekeeper has been doing electronically throughout their day, and we're able to bring that together and automatically fill out most of the timesheet for them. And it's just an incredible sort of productivity and time saver. And then through a recent acquisition, we've augmented that through pre-billing and sort of invoice creation. And then we have a document management and sort of Teams-based collaboration product and Workspaces that is powered by the Microsoft 365 suite underneath it. And so there's almost a you can think about this almost as a flow in here. So the deal starts up here at the DealCloud platform. You have to go identify, source, pursue, and win, leveraging all of your experience and history and expertise to go win the business. Then you have to go through a fairly rigorous, complex, hyper-nuanced set of onboarding and intake steps in order to make sure that you're ethically able to, you commercially want to, it makes sense for your strategy, all kinds of things to be able to take on that business and to secure it. Then as you deliver work, you have to work together in teams, particularly in this hybrid sort of distributed world. You have to store your content in a compliant way, and then you want to be able to track time in some of these industries and to be able to get your invoices out and do all of that in a pretty consistent, efficient, and profitable way. So that's number two. Compliance, John kind of touched on this. This is going to be one of the conversation points that continue for this whole generation. This is a market where this is particularly important. These firms are bound by an incredibly deep and important set of obligations to their clients, to their investors, to their regulator, professional codes of conduct, and ethics. And not only do we have a team, a whole dedicated team that is focused on staying up to date on all of the constantly changing regulations across the world in all these jurisdictions, they're meeting with regulators, they're meeting with insurers, they're meeting with firms, they're meeting with investors, but we embed, we productize the codification of all of those rules and regulations into our software. And I'll give you two examples of that. One is when you go create a confidentiality policy, there's some scenario, we're taking the company public, and this is price-sensitive information, we have to be extra careful with this. There is a dropdown of every policy that might be relevant to your firm and your jurisdiction in this particular moment, and baked into that dropdown item are the whole set of rules that are required in order to make that work and make that be compliant. Each of those different rules then has to be able to be interrelated with each other and compiled down, and we have to know the relationship between each rule and when there's an overlap between them, which one wins. That's constantly changing as the rules change. Another example of embedded compliance is in our Time product. So I talked about this terms of business capturing all these obligations. Well, that gets embedded into our Time product. So when the timekeeper is filling out their timesheet or modifying their timesheet or modifying the narrative that the machine is pre-populated in there, and they put something in there that violates one of these stipulations from a client, they may not have paid much attention to it, they just wanted the business. But now, all of a sudden, they're doing something that violates it. They're billing time in the wrong way, or they're doing something else. It flags it right there. In real time, it won't let you do it. So that way, the bill doesn't go out, it doesn't get rejected, the time doesn't get written down, and you don't have the revenue leakage that has just plagued a lot of these organizations because the compliance is embedded. Applied AI is going to be the theme of today. So you'll see that everywhere, but just know that it permeates everything that we do, and we really lean heavily into that applied part. This is the whole intelligent applied. This was my opening point, which is we see our opportunity, we see our differentiation here not in inventing the next unique LLM-based library. It's around applying this technology to all these specific moments and workflows within these very specialized organizations. And then lastly, the Industry Graph data model, which is the beating heart of everything that we're doing. It really is incredible at how much effort and energy has gone into refining and perfecting this over a decade plus. So again, just to sort of tee up and foreshadow Ben who's going to come up, just know that these industry solutions are a big, big part of our strategy. We've been investing very heavily in the teams to do this. They come from these industries. We pair them with the best technologists. And this is just really moving us into an area where we are not an empty vessel, low-code, no-code platform where you just sort of hand it to you and you're like, "Okay, now you're on your own," or you need an SI, or you need some sort of third party here to make it do something for you. This is how we do this out of the box. And the bottom of the architecture that I showed had our partner ecosystem on there. This is incredibly important for us to have a robust, thriving ecosystem. We had our partner show yesterday. It was a packed room. It was awesome to see the growth there. We have our data partners who help bring in the market intelligence and the data feeds into our system to help stay on top of your market. We have our technology partners who augment capabilities of the intelligent cloud. We have our delivery partners who help bring the whole thing to life quickly. And then we have strategic partners. So KPMG is a strategic partner, and we rely deeply on their advisory capabilities and other capabilities, and Microsoft. Microsoft is a special partner. We are very, very close. It has a lot of aspects to it. There's a marketing and sales dimension to it. So all of our software is on the Azure marketplace. We try to make it very easy to buy, particularly for Microsoft customers, which is pretty much everybody in our market. But really, I think the most important part of this partnership is the co-innovation. It's the technology. It's the product. It's the engineering. We are very close to their core architectural teams. The head of Copilot is here today. He'll be on stage with me later today in our big client show. We've got a nice video from Microsoft's global head of AI and cloud. So we're very connected to them. We're in their roadmap. We're talking about strategy. This is a really important thing for us, and I have some more details on that later. All right. So let's get into applied AI. I said that was going to be a big part of what we're doing. It is. And we're making a lot of announcements later today, which we are both incredibly proud of and sort of relieved to get to this moment where there was a lot of work in late nights. So I'll just reiterate the point again. AI is not new to us. It is everywhere across our portfolio today, but we want to take it to the next level. We really want to continue to move that needle and add generative AI into everything that we're doing. We are making investments in five sort of key areas within generative AI. Zero Entry, this has actually been a North Star aspirational journey for us for a while. The idea is, how can we use technology and AI to do everything we can to minimize the thing that everyone hates most, particularly professionals, manual data entry? I'm sure you all could understand that one. We just want to get that data in. You want to get it in. You want to ensure the quality. You want to add that productivity level and that efficiency. That's something that we've done effectively over the years. Conversational, I think we were all struck by this ChatGPT where you're able to type in English language, and you get this incredibly well-constructed response. So we are working closely. We'll be extending Copilot. We'll be embedding natural language interfaces and search across all of our products, embracing the new paradigm of just making it easy to find information. Summarization is actually really, really cool. So Microsoft CEO Satya Nadella said in their last earnings call just a couple of weeks ago that summarization is Copilot's number one use case by far. And it kind of makes sense. It just really reduced the cognitive load of these oversubscribed, incredibly busy professionals. And I'm going to come back to this point in a second. When you can infuse that summarization or the generation with very proprietary, firm, and professional-specific information, it just comes alive. Generation, same point. We're helping to just make it easier, automate different steps of these daily workflows. We take a first draft approach to generation. So there's still a human in the loop, but there's just a psychological impact when you go from kind of a field with a blinking cursor, there's nothing there, it's blank, to suddenly having interesting content that sounds like you that you can correct and modify. It's just a nice aid, a nice productivity enhancement. And then recommendation. This one is crazy powerful, and it's just the beginning of what we're doing here. So the idea here is we know this industry so well, we know the firm so well, and we know you, the professional, so well. You don't even have to go into an application. You don't have to go into an agent or a bot or a Copilot. We can just push to you a lot of very interesting, actionable, insightful information in the moment you need it. You don't have to go in and run a sophisticated search or navigate menu items. So you'll see an area that we're going to be really leaning into to augment everything else we're doing in this recommendation area. All right. So this leads up to our first big announcement that we will be making at the show, which is Intapp Assist. Intapp Assist is our generative AI offering. We are announcing specifically Assist for DealCloud. And so this is going to be a new SKU. We have elements of our AI, which are just going to be included in the product to support our continuing drive to deliver more value and continue to raise prices of our existing software. Some of our AI is going to be new monetized SKUs. This is an example of the latter. This is just for one product. This is Intapp Assist for DealCloud. We are going to be adding Intapp Assist for every one of our products over the next 12-18 months. We're incredibly excited about this. This is the first of many. Let me dive into one point here, which I think is important, which is, yes, this uses GPT. It goes through the Microsoft Azure OpenAI services. We're benefiting from this incredibly powerful large language model. But it does something that no large language model can do. These large language models, as you know, were trained by scouring publicly available information on the internet. This is why they are so incredible at generating natural language responses and processing that input. What they don't have by design is the proprietary knowledge that lives within each firm, right? So when you ask GPT without that knowledge or without that, we'll use the word context, you ask it, "Write me an email or a follow-up between two people, Jim and Sam, about the Franklin deal," it's going to give you an incredibly well-constructed, grammatically perfect response. But it's not really how you would talk or how you would send an email as a professional because there's no context. All of that context lives within Intapp. Everything about your deals, your clients, your interactions, your matters, your engagements, that's in our system. And so now when you start to infuse that information together with GPT's natural language skills, there's a term of art for this. It's called grounding. It's a totally different ballgame. So now, okay, we'll give it a Franklin deal is an asset sale, $500 million enterprise valuation. We spoke two weeks ago, so there's a history there. There was concern around valuation. We have a long history together. We've done four deals together. The last deal we did was GHL Industrials. So you just imagine, this is just a small example. Now, when you look at the email that GPT can generate, it starts to take on a little bit of a different flavor. It starts to feel like, "Oh, I might write this as a dealmaker, as a partner, as a professional." It includes acknowledgment, recognition that there were some concerns. It acknowledges that we have spoken recently. It asks about, "Yeah, how is that old GHL deal doing? Is that going well? I want to make sure that you're happy." So it's just, again, a small example of how we're able to build on top of the power of GPT and large language models specifically for this industry, leveraging this incredible wealth of knowledge and information that we uniquely have within our systems. So I'm going to show you sort of a quick demo of a couple of examples of what I just talked about. Welcome to an overview of Intapp Assist, innovative applied AI designed to push efficiency to the next level. Let's dive in and explore the transformative capabilities at your fingertips. Here we are viewing a DealCloud dashboard, a powerful tool to assist firms in managing their deal pipelines. In this example, we are focusing on Avantius, a transaction target. Let's take a closer look. Notice the concise description of Avantius in the transaction target overview? This is AI-generated. It concisely captures the essence of Avantius, crafted from more detailed and expansive content sources. With just a click, we can easily create a streamlined description. Now, let's check the company correspondence tab. It's a comprehensive view of all interactions related to this target. But here's the game changer, the AI-generated summary. It distills every note, email, and meeting down into an easily digestible overview, saving time and keeping us informed without sifting through the raw data. Moving to the contacts tab, we can see the people we know at Avantius, as well as all our team members connected to this target, including scores indicating relationship health. Let's focus on two key company contacts, the CEO and CFO of Avantius. It's been a while since our last interaction, so let's initiate contact with CEO Daniel. Here's where our applied outreach feature comes into play. Notice the AI-powered insights? They provide a personalized summary of recent interactions, key relationships, and relevant news. This context-rich briefing is crucial for effective communication. With just one click, AI generates a draft email tailored to Daniel. It looks great. Let's send it off and maintain that connection. That concludes our tour of Intapp Assist, new applied AI in the Intapp Intelligent Cloud. With these tools, managing client relationships and transactions becomes more intuitive, efficient, and insightful. Intapp continues to push the boundaries, empowering firms to lead with intelligence and innovation. All right. Just a small, quick example of what we'll be talking about later today. All right. So let me change gears a little bit here. Intapp Assist is really focused on driving productivity in these everyday workflows across a firm. By the way, I mean, when you think about the combinatorial power of that, even if it's a small enhancement or efficiency, when you start to combine that across all the times you do something across every day, across all your professionals, the level of productivity and really force multiplier function is actually pretty material. So your BD team, your coverage team, your research team of 20 can do the work of 25 or 30. That's actually an incredible advantage for these organizations. So that's really kind of the assist part. Now, I'm going to show you a little bit of a more transformational example here. So we engaged a really incredibly pedigreed research organization, the lead of which had wrote the book, The Challenger Sale, and spent his whole career studying sales and really initially focused on the B2B space and wrote a new book and a new study of interviewing thousands of professionals through a business development and revenue generation lens. The results are absolutely fascinating. He came back and identified five key archetypes of behaviors, only one of which was really successful, and they call that the Activator archetype. This has gotten published in HBR. There's a lot of attention here. We talked about this at the CEO Managing Partner Forum we had the other day. Everyone was on the edge of their seat. This is getting a lot of engagement. Firms have been asking us for something like this. We really try to stay close and listen to what our clients, particularly senior leaders, are talking about. This is what they asked us, "How can you use technology and AI to help us drive more growth? How do we get our professionals and our partners and our younger partners to be more effective at developing business?" We are announcing an Activator experience. All of these best practices, all of this primary research that we've commissioned for this industry is getting codified and configured and baked into the software that we are delivering. There really are three main parts of the Activator. It's really committing to business development, making it part of your every day, staying on top of your network, particularly the people that are really influential and impact your business, and to be able to proactively bring the right insights, the right opportunities, and discuss issues together. As part of this, we have Signals. I mentioned that in Intapp Assist earlier. Signals is incredible. We all have the phones, and we're all very used to it telling us the best route to the airport or how much water to drink or the Instagram pictures to share. It's a pretty well-understood concept, right? But no one has really brought that to the enterprise space, and no one has certainly brought that to these firms and to these workflows. That's what we do. Signals is an intelligent feed powered by really sophisticated AI. It does two things. It looks out at your network. It looks at your external network, so all the people that you know that impact your business, and your internal network. And it can tell you in near real time, "Hey, one of your major LPs or investors has moved funds. You need to know about that right now because there's a window. There's a moment where they will be particularly receptive to being engaged with to talk about their new strategy." That window will close fast. Promotions, changes, company news, internal meetings that you're going to, and then even internal conversations. So there's nothing a partner hates more than walking into a meeting, feeling embarrassed because one of their colleagues was in there yesterday, or talked to somebody there that they didn't know about. So if you have a key prospect or you're sort of a key client partner, and a colleague in another office that you may have only met virtually has talked to their assistant general counsel, you will be notified. You remove that embarrassment or potential for embarrassment. Perhaps more importantly, there's an opportunity for better collaboration, better coordination between you to help bring the full platform, the full power the firm to bear for these opportunities. So we're really excited about that. So I talked about the productivity. I talked about the transformational opportunity. Data powers everything underneath it. And we are announcing Intapp Data. Intapp Data is 85 million company records, 200+ million contact records that just turn on and are available within the system, within DealCloud. This is one of those examples of something that we're just including. So this is just more value we're bringing to our customers. This is more, I think, credible ammunition for us to continue to increase prices from our large customer base. And it's awesome because it is baseline jump-start information that you need to power a lot of these AI capabilities that we're talking about. So now we have Intapp Data together with this Intapp Graph data model. And this is where Delphai fits in. Dave calls it the outboard motor. This is the rocket boosters. This is how we're taking the whole thing to the next step. Delphai does really three things. First of all, they are cutting-edge AI talent. They are on the forefront of their field. These are MIT, Stanford, Google, Meta. They come from the top pedigree. They're really pushing out there, staying on top of this. We're bringing them in to augment our already incredible team of data scientists, ML engineers, data ops. It's just we really are investing in the team that's going to make all of this possible. Two, they come with models. They come with a lot of the expertise and technology to be able to bring these natural language search and a lot of the models that we need to embed within our software. And thirdly, they're bringing this concept called provenance. If you don't know that, I think this is a word we're all going to hear a lot more about soon. Provenance is really attaching an audit trail to the data. Where did this data come from? Down to the entity and field level. And we're in an era of generated content. People are going to want to trust that content and know, "Okay, where did it all come from?" Particularly in this industry where accuracy and trust are sort of paramount to what they do and who they are. So we're really excited about this group. We're going to bring CEO Founder on stage later today. He's brought some of his team, and so it's pretty neat. Okay. This is the sort of, I think, our fifth and final kind of big announcement that we're making. So I talked about Microsoft earlier. We announced the partnership two years ago. It's incredibly compatible. I made the joke earlier or yesterday in our partners' forum, but I didn't know Microsoft was in the room, and I was a little nervous what I said, but it actually worked out okay. Their mission statement, I looked it up. It's like, I can't remember it exactly, but it's like, literally, we're going to empower every person, every organization on the planet to do more. So they're pretty broad in what they're trying to do. I don't think you could go broader. And so they're building these foundational technology, literally, for every industry on the planet. And we are building on top of that and leveraging a lot of that componentry to bring the focus and the solutions to our market. And so it actually is an incredibly compatible relationship between us. They are on the forefront of where I think the kind of the LLMs and these bots and agents and copilots are. So there are going to be a lot of these. There are going to be a lot of LLMs. There's going to be a lot of AI technology that comes out. But I think Copilot is the one that our firms are really thinking about first. There's an interesting sort of challenge here, though. I talked about our markets being bound by these incredible special obligations. And it is very deep. These firms make foundational promises of trust and confidentiality to their clients. This is not about getting fined or maybe even going to jail. This is about an existential situation. If this is broken, if this promise of trust to a client is broken, these firms go out of business. So this is a really, really big deal. And Intapp has a 15-year history in helping firms solve their confidentiality and compliance situations and requirements. So we are announcing Intapp Walls for Copilot, working very closely with Microsoft. This is addressing one of the most fundamental issues or concerns or pauses with Copilot. We call it the oversharing problem. So Copilot is very good at indexing and looking through all the information across an enterprise, almost too good. And it finds something. It finds something that it gets revealed, sensitive information, and it starts to push against this trust that these firms really are based around. Now, the good news is Copilot respects and honors the native security of each piece of content and application. The bad news is the firms have to have their house in order and have all the security and the permissions set right. And when you add in the point John made that says there is this constant fluidity and formation and change and reconfiguration and ending of these teams, these expert teams, these matter teams, engagement teams, deal teams, project teams, all the time, every day, it's really, really likely that something gets missed in there. And that's what Walls for Copilot does. It comes in. It secures everything there. It has telemetry and instrumentation directly going into Microsoft to say, "Here are all the surface area that might be at risk. We think this area is particularly at risk. Here's where Walls is securing information. Here's where it's not." It's really the thing you need to be able to deploy Copilot and other bots or LLMs responsibly, with confidence, and with trust. So it's a lot of stuff. Intapp Assist for DealCloud, our first of many to drive new levels of productivity, more transformational experience where we can help embed best practices to drive up to a third more business for professionals who are not usually formally trained in how to do that, often powered by this new intelligent feed signals. Intapp Data, so 80 million companies, 200 million contacts out of the box, supercharging everything with some top AI talent in the industry and bringing provenance in. And then Walls for Copilot, working carefully and closely with Microsoft to try and solve this oversharing problem, which right now impacts Copilot, but will impact any similar bot or LLM-based deployment. So that's Intapp Intelligent Cloud, and we're really, really excited by it. Thank you. It's awesome. All right. Good afternoon, everybody. My name's Ben Harrison. Very glad to have the opportunity to talk to you this afternoon a little bit. I'm going to follow up on what John started with and talk a little bit about the end markets that we serve, the position that we have in those, and how we got there, and how we're thinking about really expanding that TAM and getting very specific into a lot of those verticals. So we've got a history that comes from Intapp being a vertical-specific company in legal. I was a founder of DealCloud about 15 years ago, and the heritage there was on the private equity and the banking side. So we got a great position there. And then together, really over the last six years, we've been able to launch our products into tangential markets organically that look and feel a lot like those that we started in. So you've seen this a lot today talking about our technology, but these are each of the markets we're getting into. And we've got varying degrees of penetration and position here, but there's a lot of white space that we're excited about, and we have a very intentional strategy with which we're pursuing each of these. So you saw in the last earnings release, it's about 2,400 clients across those markets today. There are tens of thousands of businesses that operate in each of these sectors. So we're very excited about the opportunity to go a little bit deeper there. So to talk about the strategy and how we're going after each one of them, I want to rewind the tape just a little bit to some of the original ways that we did this because this has really set the foundation for how we formalized this and started to templatize this and repeat this on a consistent basis. So when we first got into the market with the DealCloud product, I'd been a private equity investor, and we had some people on the team that had worked in that space. And we said, "Hey, we don't see really good technology for buyout investors today." So we had a platform. It got very specific in terms of its capabilities to support investors, in particular in the equity asset class, in particular in the private markets of that asset class. As we started to get through parts of that market, we realized that there were a lot of other people in the industry that were doing the same thing very similarly and that we could get into those markets with slight tweaks to the product. So what started out as a private equity vertical software or what started out as a legal vertical software business started to have these expansionary moments with the platform. Originally, this was entrepreneurial hustle. But today, it's a very intentional strategy. So as the company has grown and scaled, we've been able. I mean, big, exciting technology company. We've actually been able to hire tons of colleagues directly from this industry. It started out we were learning from our clients. We were listening, learning. They said, "Let's do this. Teach us about these." But today, we're hiring former attorneys, accountants, consultants who are partners in these industries. We have a lot of former principal investing professionals, investment banking professionals who are actually on the team. So what we've learned from our clients, we're also using our team directly and expanding our expertise using our HR strategy. So we got into the private equity market, and quickly, the most tangential spots for that were other equity investors. So that started to look like the growth equity investors and then the VC investors. And of course, there were nuances to each version of that style of investing, and we catered the product that you heard about from Thad with the low-code, no-code platform to each of those individual markets. And then we started to realize, "Okay, this market's getting pretty big, and there's a lot of other flavors of private asset classes out there, not just equity." So we quickly started to get a position in credit because of seeing the news about the private credit markets and the maneuver of a lot of that capital from the banks to these alternative asset houses. We've been a big participant in that market and a big benefit of that market. But in addition to that, there's a lot of other subvertical asset classes. Infrastructure, real estate are very big, the real assets market. And organically, over the past couple of years, we've built great businesses in each of these markets. So as we started with the deal teams and the pipeline, you just saw some demonstrations of pipeline technology. That was one module and one view. We actually, from an NRR basis with the client, started to expand our position in these types of accounts. So we got into different functions of the business inside of these firms. That looked like servicing the fundraising teams, not just the teams that were allocating the capital into the companies, but the individuals who were raising the money from the limited partners and investors and actually bringing it into the funds. So we started to build modules and capabilities for each of the individual functions inside of these alternative asset houses. That was a great way to grow the account, expand the NRR. And as the market has really grown I mean, this is what started out as a $4 trillion market is now a $14 trillion market in about just the last 10 years. There's been a lot of additional flavors to the product. It's gotten a little bit more liquid. You've heard about the secondaries market and the continuation funds. We've started to build capabilities there and service those types of firms. And we've even worked with the GP stakes groups who are buying out positions in those GPs in the top two categories. So this was the original way that we did tangential TAM expansion using the DealCloud platform, looking at people who did similar things and using the configuration environment to get very specific in our expertise there and get into those markets. We moved from the alternative assets and private capital markets space, and we went to the advisory community. They weren't allocating the capital into the company. They were providing the advice to the company to actually take that capital. And so while they were doing two different things, the way that their markets developed were very similar. They were dealing in different things. They were either dealing in the dollars going into the business or the advice for the business. But the way the pipelines were forming, the way the relationships in those markets were forming, the way the professionals in those markets worked was almost identical. And so this was how we saw the software moving from these different markets and different TAMs and how we got tangential expansion. DealCloud and Intapp got together six years ago. It's been an incredible marriage of markets that we serve and also technology that we have. You saw a full stack from Thad. And we've been able to take that DealCloud platform from what started in the private capital markets and investment banking to the broader professional services markets, the accounting markets, the consulting markets, and take that platform into a lot of our captive legal relationships that we've had for decades at this point. So this was what it looked like when we first started going from one subvertical in an industry to the next subvertical. So you saw, aside from Thad and from John, where we were talking about our industry solutions and the things that these different industries have in common. These people are very unique. They don't manufacture. They don't distribute. They don't have a high-volume sales team with thousands and thousands of people pushing hundreds and hundreds of widgets through the traditional operating company. They wake up in the morning. They pitch three pieces of business. They do client calls all afternoon, and then they draft pitches, documents, execution work at night, sometimes till 2:00 A.M. and 3:00 A.M., and they start again first thing. These are incredibly demanding jobs. It's an impatient audience. This is a high-maintenance, very special category of person to deal with. We have tremendous respect for them because a lot of us were in that seat or worked in that industry. But really, they don't have the patience for square peg, round hole software. If they log in and the screen is not immediately doing what they need it to do from a nuanced workflow, they're going to give up on it. This has been the challenge for the horizontal players in these markets. This is the thing that we've been studying. This is the thing that we have been respecting and that we are really delivering on for the buyer and the user of the software. You heard about the data piece from Thad. The market data in these industries is really different than traditional CRM or the traditional buying process. There are all these market data feeds. You got S&P and PitchBook and all of these versions of technology companies that feed information into these organizations. We have actually templatized that information. We've got our own captive version of that data and Intapp data, but we've also templatized a lot of the other third-party market data feeds. You saw it in our partner category to really try and bring together the screen for these professionals so they're not all tabbing from the software system that they have to use to the data system or if they have to pull the information to give the client advice or to see what happened in the market. So these are the common themes that are reality for everybody that we serve. It's six vertical markets as we present it to you and the architecture and the industry solutions diagram there. But within those six vertical markets, we have a lot of participants who do a lot of different things during the day. So you've seen this graph, and we've talked about this from the perspective of our graph database and our graph data model. But I don't want to use this to just talk about the reality of the industries that we serve and what it means for us from a go-to-market standpoint and what it means for us from a right-to-win standpoint. So the companies start here. They're the currency for all of the participants in this market. We started on the DealCloud side with the private equity firms and the investors. We expanded that to all the different asset classes. We got to a lot of the investment banks. Many of the firms who cover us in this market are actually customers of ours. We appreciate that very much. And Intapp had the history with all the lawyers who were working in and around the transaction. We've expanded that to the accountants and consultants. And so what this looks like on a daily basis is the investment bankers get hired to raise money for the company. The investors put the capital in. The lawyers draft the asset purchase agreement or the stock purchase agreement. They paper the transaction. The accountants, they're doing the financial due diligence, the quality of earnings study on the company to make sure it's good to go. You've got the consultants. They hire Bain, McKinsey, BCG to do the market study for the deal. And so the way that the pipelines for each of these firms, their sales pipeline, their revenue generation, it all forms very similarly around this ecosystem. And what's great about this for us is that all of these people work together. And you saw from John, they work together again and again and again and again, one transaction to the next or one opportunity to the next. And what that has caused to happen for the company is a word of mouth and really tangential sharing of our software platform for all the participants who work in this space. So we showed you this diagram from a software perspective and a tech perspective, but think about this now from the market perspective and what this means for our company in terms of getting to the TAM. There's tremendous white space, thousands of firms, tens of thousands of firms to get to. But our captive clients today are talking to, on a daily basis, everybody who participates in this. And they're saying, "I use that platform. I use that technology. It helps us run our business." So we're excited about the dynamic of these people working together because it's free advertising. It's a word of mouth space. And I'll give you one anecdote that's really fun. And this happens to us pretty frequently. The bankers go to these conferences with the investors. It could be a corporate access conference or it could be ACG or heavy hitters. They go there to source deals from the people who are advising and leading the companies. And they go into their meetings with their counterpart, and they're on their iPads usually or their phones. And they're looking at our system, and they're saying, "Okay, what relationship do I have with that investment bank, or what relationship do I have with that investor?" And as Thad said, all of the data, all the emails, all the interactions, all of the deal flow, all of the matter history, all of the background and the franchise value is there for the professional that's in that meeting. And they'll be going through it, using it to run their meeting. And halfway through the meeting, without a doubt, they'll say, "Well, what are you using over there on the other screen?" And they'll say, "Oh, well, that's Intapp. That's DealCloud." And every time they turn their phones around like this, they take a picture of themselves, both holding the phones like this, and they send it to us. They say, "Good job penetrating the market." So this is a bit of an eye chart, and it's a web, and it's actually the value of the database and the graph data model that we have. But it's the market that we form, and this is how we're getting tangentially to each of the end markets that we're working in and doing both that NRR and that new logo expansion. So you saw this from Thad for just a minute, but let me talk about the very formal way and the intentional way with which we get into each of the nuances of the end market. So we talked about going from private equity to private credit, real assets. That's expanded to the six verticals. But within the six verticals that we serve, these firms have gotten very big. They have multiple product types. In the investment banking market, you've got equity capital markets desk, debt capital markets desk, M&A, sponsor coverage, restructuring business, valuation practices. Got the commercial banks doing the credit and the loans for a lot of these transactions. Within each of the verticals, but consulting, accounting, legal market, we have taken what we've learned from our clients and the expertise that we've built in-house. We have built blueprints beyond just the vertical, beyond the six verticals that we've talked about. Within each of those verticals, we have best practices blueprints to show the client and the buyer that the experience can be for the partner and the practitioner. The big blue box that John showed about those partners and those investors and the people who generate the revenue for these firms and do the execution work, this is what we're building for them. So what happens is you walk into the pitch. We've already spent 10 years doing the vertical-specific version of this versus the horizontal version. So for the last decade-plus, we've been extending the lead from those groups. But when you walk in and one of the we've got 5 partners sitting around the table, and they say, "Well, I'm in the transaction advisory practice and the valuation group." And you say, "Okay, well, let's go to the blueprint for transaction advisory and valuation." What happens in that moment is the limbic portion of their brain connects with the software, and they say, "That's me. That's what I do during the day." And that's where the win rate, that's where our differentiation and the win rate against the competition just really starts to extend. So what started out as hustle and learning about the industry has been very formalized into end market blueprints. We're only showing nine here. There's more than nine in terms of what we're going to market with. And this is constantly changing. These firms, they launch new service lines all the time. The example we used on the previous slide here is very M&A-centric and private equity-centric. But if you actually look at the global practice groups in the law firms, there's litigation. There's IP. There's real estate law. It's not just the M&A and private equity piece that we talked about. As these firms grow and expand, as the practice lines grow and expand, as the service lines grow and expand, we're studying each of those, and we're building blueprints and templates to cater to the partners, the professionals, the people who are doing execution in each of these markets. The moment that they see this is really big, and the sales cycle really helps our go-to-market team in terms of their ability to win the business and appeal to the audience. We've talked a lot about the history of DealCloud and banking and private equity, but I want to actually share with you a couple of very specific instances in professional services, recent wins and big recent exciting clients that we've grown with. Let's start in the accounting market. We are deeply embedded with one of the Big Four firms now, and they had a global network of transaction advisory practices across about 50-75 member firms. So all of these groups use the same banner, the Big Four banner. They operate in different countries, and they actually run as a silo. They run a different P&L. They don't share data, and they don't operate off the same software system. And so using our data model and using our integration strategies, we were actually able to deploy transaction-oriented CRM and also integrated data for the global franchise and meet the needs of thousands of professionals in terms of unlocking the franchise value of that firm. So that is DealCloud platform win right there at the Big Four. We are fractionally through the number of seats that are available in that market. So we get the land of the client using the blueprint, using the capability, but we've got big upsell after that. Let's move on just to the consulting market quickly. So there's a New York-based consulting firm. They actually provide P&L consulting services to the private equity community. This was great because all of our customers were their customers. You can use them as references. The main thing that they were doing was calling on the partners of the private equity community that owned those assets, but they were also calling on the CFO of the company and the VP of finance of the company and trying to triangulate those three or four relationships to win the deal. Then there was repeat business with each of the sponsors. So when you saw that graph data model and the web of relationships on that prior slide, we were dealing with the exact same dynamic in this consulting firm. It was that data architecture. It was that data model that allowed us to solve the problem they had of their sponsor coverage business alongside all their clients that were the actual operating companies. And so we were competing there with big horizontal CRM, and we won the day. So another great example. This could be thousands of professionals in terms of total size. And let's move on just to the legal market as well. So we just want a really exciting client here. This is a firm that had a deep capability and kind of original founding history in the energy markets, a tech-space firm serving a lot of the oil companies. They had grown their law firm into a global offering. They had added IP capabilities. They had added M&A capabilities. They had added technology practice. They had done a lot of that through acqui-hires. They had done some of that through acquisition and merging. They had this big network of partners that they're trying to unlock because they want to cross-sell those practice capabilities, not just their energy practice, but all of those other practice capabilities across a network of thousands of partners. In this particular instance, we came in, and we replaced a very legacy on-premises CRM system. It was actually a vertical system, but not as large, not as scaled, and not as new as we were. We were up against some of the horizontal players in this process. One of the main winners of one of the main drivers of the win at this particular deal and with this particular firm was that Activator relationship behavior that you saw from Thad. So it was the data model to unlock the cross-sell to each of the different practice areas, but it was also that research that we had embedded in the experience to actually turn the lawyers and the individual attorneys into dealmakers and business developers. So DealCloud, what started, it's private equity software, moving to the banks. Now, as a platform, looks like this, not just siloed in one of those verticals, but across all of the financial services and professional services markets that we work in. So we're very pleased about the progress that we've made over the past five to six years since coming together. We believe that there's a long runway here. Dave's going to talk about the white space specifically, but this is a spot where we have a long runway of organic growth. Here's the kicker. We spent a lot of time building the vertical software and then building the blueprints so that we could talk specifically to the practitioners. That's been time in the practice areas or in the product groups that they work in. It's been the differentiator. It's created win rates that started in the 40s and 50% but are now extending up into 60%, 70%, 80% when we go to market against the competition. We think that with the Applied AI, the actual benefit to the individual practitioner we all know what generative AI does. It summarizes things. It digests data. But let's just talk about what this means. If you are in the private equity business, and you are targeting thousands of companies from a sourcing and origination standpoint, and you have the AI telling you which businesses to go spend time with, your job is to get that money out of the fund as quickly as possible. And if you have that assistant helping you get that money out and make better decisions, that is super meaningful. We think that helps extend our gap. We already have the vertical move, but now we have the vertical AI extension of the gap against the competitors. If you're in the professional services business, and you have a ton of clients and matters that you're trying to bring on, and you're trying to do it quickly, we can use AI to get through the conflicts process and the new matter intake process much faster than the competitors. If you're in the accounting and consulting business, and you're working on 10, 20, 30 engagements at a time, we've got the AI and the collaboration tools and with Microsoft that you heard about from Thad. So we don't need to go through each one of these, but we think the benefit of the Applied AI on the proprietary data that our clients have, but also on top of this blueprint strategy that we are after, is going to give the actual end user of our product and the buyer of our product significantly more value because that's captive to our system today. So we're excited about the growth we've gotten across the different industries that we're in and glad to be able to share that with you today. All right. Thank you. So Ben talked a little bit about our strategy of how we engage on an individual basis. I'm going to talk a little bit more about the structure of our go-to-market organization and how we implement that strategy across the field and across our individual clients. I think Intapp has assembled the leading sales and marketing overall go-to-market force across the industries that we serve. We are where our clients are. We meet them in all the global financial centers. I think we have some of the most impressive people there. As you have heard, expertise is at the core of all that we do. We are met with very demanding people on the other side, and they expect to work with experts who speak their language and know their business. We've assembled a team to do that. John began by sharing this picture from the perspective of the solutions we build, how our products need to be different because the industry that we serve, the industries we serve are different. I submit that it's the same issue also from a go-to-market perspective. This picture is what everybody in the world who sells software is used to doing. These people buy. These people sometimes approve. And so you become expert as a software sales executive in working departmentally across each of these. These tend to be very, very siloed systems, and they're very departmentally fragmented. If the organization model looks like this, it stands to reason that the buying pattern is different. The way you expect to engage is just fundamentally different. These people remain extremely relevant in departments. They have an important voice in the process, but this is a critical audience and a critical stakeholder that we have to cover. Not only is the organization different, but the expectations are different. These are the most time-poor people. Look at your own organizations. You know what the reality of the jobs are like. You're making the investments. You're servicing clients. You're with the engagement teams. And so the expectation, you're used to dealing with experts. You were yourself an expert, and you're used to dealing with someone on that side. As we have built our field team, there's a set of people who interact up here we cover at this level. So for example, if you're covering a real estate investment firm, you've probably done real estate investment previously in your career and shared his history of previously being a banker. We hire people like that who are previously bankers covering those industries. We cover senior executives at law firms who are in that. Additionally, we have solution experts down at those individual categories. That is the combination of our team. At the simplest level, someone in our team who covers an account has a pretty basic responsibility. Know your client. Have a plan. We talk through a lot of detail about the type of plans that we look for. Deliver overwhelming delight. I think the reputation that we have earned over the last 20 years has been that we're pretty proud of this, that we are very focused on our client outcomes. The mastery that you hear when Ben talks, when Thad talks, when John talks is something that we expect of our team, and we expect to take care of those clients. With that, you protect the franchise you've got and then grow it. It's all very obvious, but you aggregate that up. That's ultimately what our go-to-market organization does. When we think about the market, there are 28,000 accounts that we're currently actively pursuing. These are in our database. We have coverage plans. We're going to market against them. These accounts are scored for their economic potential, what they might buy from us. We look across each of the verticals, each of the subverticals. All of our solutions say, "Which ones fit? What's the right price point? How do we measure and model that?" And then we get up with an aggregate score. Based on that, we segment those accounts into coverage models. For the purposes of this conversation, we have two primary coverage models. One is a named account approach. What we've described is sort of this heavier weight, expert-based deep coverage against a population of 2,000 named accounts. Additionally, we have 26,000 long-tail accounts. We're a little bit more opportunistic there. Demand comes to us a little bit more. It's an efficient model. We're a little bit more prioritized against the named accounts. You can see these threads come together and build this ultimate coverage piece. The first axis is by industry. So we talked about that. Experts in industry who can speak the language just as you heard, either Ben or Thad, come and be able to be a domain master. Additionally, product expertise across these. It's very difficult to be able to also be perfectly fluid in the risk areas as well as it is to be deal origination. Those are very deep domains, and very few people have the ability to go both. So we pull teams of both categories in a pursuit, and then, again, is segmented across our geographies and firm size. We've talked recently about the segmentation at the top, the strategic accounts. These are the largest and ones that we think have the most opportunity. I'll give you a little sense of the priority placed here. We think about 70% of our SAM is resident in the top 2,000 accounts, that named account population. So you can imagine that this is an area of disproportionate focus and investment for us. We're really excited because many of these accounts are clients, and we'll show you a little bit about the story of how that client journey goes and how we expand with them. John shared this slide. Dave's going to share a similar view. This is really the core of the summation of what both Thad and Ben talked about. We're trying to land logos any which way we can get in. The story is different in each industry. The legal industry is the one we have the longest heritage, where we have the most history with our risk products in that solution. Similarly, in financial services, DealCloud was how we got our start. Across all of them, we're trying to expand the footprint. We're trying to expand the offerings and the solutions that we bring, thus those specialized experts by products that come in and help expand. We have lots of ways to win. It can be additional products. It can be additional seats. It can be new products that we bring to market, as Thad shared today. All of those are ways to win. The platform is designed to scale for that, and it's designed to slot in as we add additional capabilities inorganically. We expect to be able to sell it through the existing field organization that we have. I love this. It's a view post-IPO of just revenue per client, and it gives you just a taste of the focus that we've had of both of those threads, both the expand against existing logos, how do we grow that footprint, and also the growth in named accounts and growth at the larger end of this. I think that we have a lot of opportunity. It's no surprise. The clients that we serve have significant ability to spend, particularly if you bring significant value. And I get very excited in the role I've got hearing presentations like Thad's to just see no one is innovating in this industry like we are. And I think that there's going to be considerable reward for that. To this point, I've focused on our direct efforts. We, though, exist within an ecosystem. Intapp, particularly as we are gaining in importance either in share of wallet or the position we hold in our client firms, are at the center. I think of it as the center of a three-legged stool. The top are our data partners in this view. Most of the industries that we serve have some type of specialized data that you need to augment the job. You may need to know what the sanctions list is for a particular geography. You may need to know what funding rounds were in the asset you're looking at. You may need to know who's a board member of this client. Lots of different ways. Each of those systems requires their own proprietary interface, login, way to get it, way to work, go back and forth. Our technology natively connects via Data Cortex to all of these data providers. What that means is the professional can live within Intapp and access and consume all that data. You can imagine we have an opportunity as a result of that window to be able to monetize many of those relationships. Intapp Data is going to increase our ability to do just that. Second, we have technology partnerships. So given the role we play, people want to connect to us, get in, and have relationships. I think that as we become more and more of an enterprise provider in the industries we work, this will be an area of increased focus. The last one I'll talk about briefly is our services partnerships. Dave mentioned in our last call that we're increasing our work with a partner ecosystem. We have been in development for many years of an environment that can enable our clients to find success via their choice of provider. Some of these are insanely focused. They just do a very, very specific task, but they are literally the best in the world at that. We have partnerships at that level all the way to KPMG, who are building an Intapp practice for deployment. We seek to make our partners successful and leverage that partner ecosystem servicing our clients for deployment and choice across that. I want to highlight one partnership in particular because you just saw so much of the fruits of the technology side of our Microsoft relationship. Thad talked about the cool stuff that we're going to do with Copilot and some other places. There's a lot going on in that kitchen. There's also a lot going on in the go-to-market side. I want to offer three points about the commercial side of the relationship with Microsoft that I think are impactful. First, every Intapp solution is available for transaction on the Microsoft Azure Marketplace. What that means is it's sort of like the App Store, not exactly, but it's Microsoft's preferred way to transact and come to their visibility, which is relevant in the world of Azure and Azure consumption. So all of our solutions can be purchased on the Microsoft Marketplace. Second, all of our solutions, when purchased on the Microsoft Marketplace, count for your MACC. You may say, "What's a MACC?" A MACC is what a large enterprise does with Microsoft, and it's a plan for how much I'm going to spend over the next 5, 10 years. That way, I'm not purchasing on the spot market. I'm buying a long-term contract at a discounted and preferential rate. Intapp solutions count against that MACC, and that's a big deal because a lot of times, some of these are very significant commitments made far in advance, and you don't exactly know how you're going to use it. So we're finding a lot of progress with clients who purchase under the MACC. The billing relationship is direct with Intapp. It's all direct credit with Intapp, but it counts against this other accounting that they have, and it's very impactful for us. Third, when transacted in this way, it's dollar-for-dollar quota relief to the Microsoft sellers, dollar-for-dollar quota relief for the Microsoft sellers, which means they get the same credit for us selling as if it had been a Microsoft solution. So these are pretty impactful elements of our go-to-market strategy and go-to-market alliance that we have with Microsoft. I'm very proud of what we've assembled in terms of the client rosters and the industries that we've been able to serve. And I think we really are at a point where, with the technology innovation and with the trust that has been earned over many years in serving this, I think there's a lot of excitement ahead for the next chapter. And with that, I think Dave's going to tell you about it. Thank you. Good afternoon, and thank you. Just a couple of items. Walk you through kind of what I continue to be really excited about six months in. We'll talk about power of the platform, some durable growth, and operating leverage. Again, I know you've seen this multiple times. Now we're going to talk about how we actually do monetize and kind of some of the key KPIs that will add some further disclosures that will be new insights to you all. Before we get into that, when we did our IPO, we had our SAM and TAM as presented, $9.6 billion and $24 billion, through the product acquisitions, through M&A, as well as just simple CPI things of how we've evaluated $15 billion from a SAM and $31 billion from an overall TAM. So it's a large and vast ecosystem that we're selling into. When we think about our application and how we're going to achieve the $1 billion, we believe we have everything available today with our current offering, both from land, expand, cross-sell, upsell. You've heard about some of the new client subverticals. We really haven't advertised that much, but real assets. So we'll start articulating that and some wins there in future calls. New geographies, we're still working our way through. That will be some more investment on that. But there's a lot of opportunity out there when you talk about the named accounts, specifically the 2,000, the 28,000, and beyond of what's available, and then obviously some new solutions, notwithstanding acquisitions this morning, which is non-dependent on the billion, but acquisitions, applied AI, and partnerships. And we view these more accelerators. So getting into that, clearly, we've demonstrated strong, durable growth. And this has come across different perspectives, both from professional services, licenses, and now SaaS and support. And really, the key pivot is getting into, and where you'll hear more of an articulation going forward, is just pure SaaS. And over the last three years, by the way, this has grown 49% CAGR, which has been very, very healthy. When you think about, okay, our cloud journey and what we've talked about from both IPO and moving forward, our original story was really a cloud transformation, and we're much more than that now, eclipsing 67% at the end of FY23, and then looking at kind of the durability. Now we're talking about this on-prem. And we'll talk a little bit about that conversion and expectations and kind of our thought process is that we'll continue to evolve. But when you step back and look at the whole ecosystem that we serve from a client, again, 67%, today's terms, it's over 77% of our clients. So they're not anti-cloud. In fact, pandemic, COVID really changed that narrative. And even pulling that thread a little bit more, 89% of our clients, not dollars, but 89% of our clients have at least one application in the cloud. So the appetite is there. It's got to get through execution and work to move that remaining $100 million over. But that's the least of our opportunities. When we talk about our durable growth, continue to be really excited about our overall clients, 2,400, and our cohorts. I know Don had showed the total application from total ARR. But if you step back, our 100K clients continue to grow really, really steady. And then if you look at the million ARR clients, that continues to grow even at a faster clip. So we haven't necessarily disclosed on a quarterly, but just to bring everybody up to speed, we have over 61 clients spending over $1 million. When you think about just cloud specifically, and I know traditionally, we articulate total NRR. Cloud specifically, our NRR rate is close to 120% this past quarter. And so when you think about how this is going to continue to evolve and how sticky our software is, and as we continue to promote more here and continue to bring out more value, we continue to bring value with our industry blueprints. We believe this is a fair characterization of go-forward business. And to just give some more color to that actual expand motion, you can look at this genesis all the way back to FY14 to FY23 that we've updated post-IPO. And visually, not only has it been steady and consistent, but the lands are getting bigger, and the expands are getting that much bigger. So it's been just a nice evolution of that expand motion. And to just really bring home the point of how some of those characterizations are, some couple of case studies of actual clients. Investment banking, we landed in DealCloud. We were able to do a cross-sell with Conflicts, upsell again with more DealCloud licenses, and then another cross-sell with Walls. 3x within 5 years, accounting and consulting. We landed with DealCloud, cross-sold with Documents, cross-sold again with Time, upsell with DealCloud, 4x in 4 years. Private capital, we landed with DealCloud. Then we had some incremental upsells with direct funds with DealCloud. And then we signed an enterprise deal, over 6 years, 10x. And then the last one being legal, landed with Walls, cross-sold with Intake and Conflicts, upsold with DealCloud, 10-year relationship, 30x. And we have many more of these examples of not only upsells but also cross-sells across our whole platform. When you think about, okay, well, how much whitespace is just available within your top 200 clients today? So these are 200 clients that we serve today that we have logos. Across that, obviously, we started in compliance, the history that John walked us through and we've articulated, very, very mission-critical, the whole trust transference of how we came and earned that relationship with our end clients, which then moved to Time, which then brought on more of a front-end CRM opportunity set. And oh, by the way, bigger value, bigger SAM, TAM, and then on to collaboration, which is still very nascent, as you can see, only 2% of this whole opportunity. But DealCloud, we've spoken a lot about today and a lot of the new product introductions. And even within that and all those success stories that you've heard earlier, it's only 8% penetrated across our top 200 clients. And that doesn't even include the remainder of the SAM and TAM opportunities that we're going after. So we look at this as a very powerful indication and durability of Intapp. We announced Delphai this morning. But since IPO, we've put approximately $42 million to work. That's opened up an additional $3 billion of SAM. And you can see we've managed about one or two each year. And we'll continue to do that, as not only are we going to continue on with our own organic innovation or the innovation with our technology partners, but also at a point in time where it makes sense or where some of our clients are pulling us into opportunity sets for their needs, we will take that opportunity. Last but not least, operating leverage. Since IPO to today, 7%, it's over 950 basis points of improvement. Same thing with our free cash flow, great momentum, a lot of diligence, scaling, but there's more to come. Stepping back and thinking about cost to serve, what is your cost of acquisition? What is your lifetime value? Here's 2 years' worth of cohorts, FY20, FY21, recents. You can see year one invest and then the remaining margin uplift. Obviously, this was a heavy spend FY20, but that's curtailed in the FY21 cohort. And so these should be very emblematic going forward. But it's got strong returns and gives us the ability to continue to invest. If we think about some of the key drivers longer term, we have opportunities in our gross margin mix. You've heard on previous calls about de-emphasizing professional services. You've heard our articulation of moving more on-prem to off-prem. So we're going to see a software margin mix. We have go-to-market opportunities, both as we continue to scale our industry solutions, our partner economy, as well as brand alignment, which a lot today has to do with that brand alignment. And then within G&A, automation and location strategy. So across these vectors, long-term target, we see a path to over 25% and a near-term commit of 300-500 basis points per year. And as far as a financial framework longer term, things that we've been focused on, and these shouldn't be new to many of you in this room that have followed our story, but clearly, we're going to continue to prioritize SaaS. We showed the last 3-year CAGR. It's a highest growth vector. And that's going to continue to be more and more material within our top-line revenue. Secondarily, we've continued to de-emphasize professional services. We are transitioning more to that as a CSAT, customer satisfaction. Yes, we will still have revenue generation, but we are letting a lot of the experts help us out here in this space too so we can focus more on our own internal innovation, transition on-prem to cloud. Again, we are making a concerted effort. This will be part of our FY25 and beyond planning. Part of that is we really are discouraging multi-year on-prem deals. So you talk about, as I've been here for about six months, these are kind of the new orders of operation here that will start having an impact within our P&L going forward. Then last but not least, we are committed to leverage as we are a vertical SaaS model. You saw that from a previous. So with that, we do see a path to $1 billion in revenue. You've heard the context from John, Thad, Ben, and Don. When we went IPO, total revenue was only $215 million. We've almost eclipsed that within the first half. You can see the cloud as a percentage of total ARR, 52%-70%. Long-term target, 90%. So that's how we're thinking about de-emphasizing some of the professional services and making that transition. Longer-term target, obviously, of $1 billion. Not only are we saying that as kind of an asymptote and a lofty ideal, this is something that we have in our plans and that we're investing towards in a very methodical way. You can see our Non-GAAP gross margin and the uplift, 82%-86%, approximately 88%, and then the total gross margin, 69%, 73%-80%. Then within that, the non-GAAP operating margin, 4%, 7%, 25%-30%. I showed you that framework of how we get there. And then obviously, that will dovetail into our free cash flow.