Great. Thank you all in attendance here and for everyone on the webcast. This is truly one of my most favorite firesides because I think John, his team, Thad have done a terrific job, and we were very fortunate to take Intapp public back in 2021. They've just done a really, really terrific job. I just need to read one disclaimer just from a regulatory perspective, and then we'll open it up to Q&A. If anyone has questions, you can either raise your hand, ask, or it can come in through the iPad, and I'll answer it that way. But part of the goal here is to keep this as iterative as possible, so I just want to run through just one disclosure real quick, and then we'll be on our way.
So as a research analyst, I'm required to provide certain disclosures relating to the nature of my own relationship and that of UBS with any company in which I express a view at this meeting today, obviously Intapp. These disclosures are available at www.ubs.com/disclosures. Alternatively, please reach out to me, and I can provide them to you after this meeting. So with that out of the way, I think this is, prepare for this. John, this is, I think, our fourth one. You folks went public in 2021, and one of the things we always try to do is look back at kind of where you began and kind of where we are. And at the time, I think you folks were discounting about $200 million of revenue in 2022. Here you are at $600 million today. So you've done a terrific job.
And as we're going through the process, I remember part of the transition you did from on-prem into the cloud. But maybe take us through that journey over the last three, four years because it's been one that's been built on execution and really the caliber of your product. But maybe talk to some of the milestones along the way. I wanted to start there because I think it just really helps level set what you folks have done and just really the caliber of what you do each and every day. Next, we have Thad Jampol as well, who's a Chief Product Officer. A lot of this will be related to AI as well, so we're thrilled to have Thad as well because he's got a unique perspective on it. But maybe we start there, John.
Okay. Thanks. And thanks for having us, Kevin. We really appreciate it. The last few years have been a great story for the company. As we came public in 2021, we had less than half of our clients on the cloud. We had a great opportunity in front of us to serve this underserved vertical industry of professional and financial services firms. So the private equity community, the investment banks, the law firms, the accounting firms, the consulting firms, these folks that were set up as traditional partnerships were fantastic businesses with an incredible hundred-year position in capitalism and in the economy. They are incredibly affluent firms and success stories, but they really operate completely differently from a traditional corporation. And that was really the foundation for the company's story. We observed that they were building a lot of their own software because they were so different.
And our strategy was very simple. We were a bootstrapped company. Thad and I were there at the very beginning. There were a few of the founders who still run the business. And our strategy was to look at all the software that these firms were being forced to build internally and to realize there was an opportunity to build a commercial version of that software. So the roadmap for the business was really set from the beginning by the organically evidenced needs of the firms. And we worked with the CIOs of the firms over many years and built an incredible relationship with the CIOs, the COOs, and the management teams of these organizations to build up a cloud platform that would serve specifically their market. And it turns out it's a gigantic industry. It's 3% of the global economy.
It's shaped in firms like this, and they've never really had a vertically oriented company. Our original inspiration for that strategy was Veeva, what they did in the pharmaceutical industry. This end market is actually three times the size of the pharmaceutical industry, and they didn't have a company that was really focused on them. As part of that, we also had machine learning, generative AI because so much of the opportunity inside these firms' information management program was around unstructured information, and they really trade on their knowledge as professionals. So we did a lot of work with AI in the early years to bring technologies to the market.
Ten years ago, we had machine learning-based time recording software that took over the market as the system that suggested back to people, "Here's what you should probably bill for." We also had a very strong compliance angle to our business, very analogous to Veeva's, in which these firms are highly regulated. They're regulated differently under different regulations than the pharmaceutical industry. They're under insider trading rules and confidentiality management and all the professional obligations. But we built a very strong component to the platform in the compliance area, and that really set us apart from the traditional horizontals like Salesforce and that crowd. And then we did a lot of work from a business development point of view. How do we help the firms leverage their knowledge and expertise to win new business, win new clients, establish long-term relationships where they expand their share of wallet with the clients?
And so that was sort of the core of the business strategy that existed before and after the IPO. But coming out of 2021, we ended up building a whole relationship with Microsoft around this that has really helped us to expand. We brought a huge portion of our business from on-prem to the cloud, to your point, Kevin. So we're now over 90% of our clients have something in the cloud from us, over 80% of revenue. So a major transformation there. We still have a little bit to go, but a lot of trends are helping us finish that part of the project off. So COVID really helped us because people suddenly had to work from home, and they couldn't get access to all their in-house built on-prem software. So that was a big tailwind for us.
Then actually, this AI thing has really shaken the world up in this way too. Firms know they need to get to the cloud to take advantage of all of this opportunity. That's really helping us as a tailwind. We've built a whole ecosystem of partners in addition to Microsoft. KPMG came on as a systems integrator for us. That was our first Big Four-class co-deployment partner. Then we've built up an ecosystem of 145 partner organizations of varying sizes in technology, in services, in data to help bring a whole product to the marketplace. Then most recently, obviously, we've gotten strong feedback from our clients that they trust our platform and its compliance capabilities, and they want us to work with them in this new Generative AI and Agentic AI era.
So a lot of the roadmap that you've seen from us over the past two years has been in that direction. Thad can talk more about that, but those are some major milestones here.
Yep. Two. And I want to spend actually the majority of time with you and Thad because a couple of things that stood out to me at the time of IPO and just even you've proven that out, right, is architecting your client's data and how important that is in terms of their monetization, which, quite frankly, they couldn't do. And I think one of the data points that you've shared consistently, which has been stunning to us, again, off a basis of $600 million of revenue today, $200 million at the IPO four years ago is $1 billion of revenue amongst your existing clients just if they were to adopt all your modules, right?
And if you think about the power of that from an internal perspective and go-to-market motion, John, maybe talk to that a little bit because I think it, and remember, these are markets where it can't be 99.5% right. You've got to be right 100% of the time. So just the criticality of the go-to-market motion because part of what we're seeing emerge is the real winners are going to be the data differentiation, right? And they're serving very complex, very high-cost, high-stakes industries, legal, professional services where there can't be hallucinations. So maybe talk to that. And I know we're going to get to the Gen AI in a broader theme, but just really, it's just such a critical part to this story that continues to emerge, quite frankly, each and every quarter as you continue to deliver and walk up your RR and things like that.
But I know there's a lot there, but it's just such an important part to this story.
Absolutely. So from a go-to-market standpoint, one of the interesting things, if you watch these industries, they are less consolidated than Veeva's industry is. There are more firms at more sizes. But the trend over the past 10 years, and it continues every year, is that the industry is actually consolidating. The biggest law firms are much bigger than they were 10 years ago. The accounting firms, the same thing. The private capital organizations, the same thing. So we are benefiting from a drift in the industry overall towards an enterprise structure and an enterprise-grade organization. And more and more, they need an enterprise-class supplier. 70% of our SAM, which is about $15 billion, is in the top 2,000 accounts. So when we started quite a while ago now, the firms were smaller.
We were serving more of a mid-market model, but we had a conscious effort to develop the platform more and more towards an enterprise-grade class of solutions and technology. Today, we're serving some of the largest institutions in the world. We have Bulge Bracket Banks. We have all four of the Big Four that do something with us. We have some of the largest private capital institutions that you can name, the biggest management consultancies that you can name. We've just got a foothold in many of these, but the technology now has proven itself as an enterprise-grade class. The organization, similarly, from a go-to-market standpoint, we've shifted our team more and more towards the top 2,000 accounts.
So just this past year, we put more of our sales team against the top 2,000 accounts under a named accounts model, and you're seeing our average selling price move up and deal sizes move up as you look at the numbers, and that's conscious. We're moving into the area where that's happening. The consolidation trend is being driven by a couple of forces. There's a competitive force, which is firms that want global business need to have more footprint. And so there's a natural need to have bigger organizations. But there's also a very interesting trend in parts of the market like accounting where private equity, as an industry, has taken an interest in the professional services industries. There's a very rapid acquisition program going on and rollout program going on inside the accounting firms.
When the private equity firms put these institutions together, they need a technology platform to help all of those newly acquired people participate in the larger institutions. So that's driving a lot of opportunity for us, and we're actually benefiting from that trend. Then the AI trend, obviously, has caught a lot of attention. To your point about the market opportunity with the existing base, the SAM is meaningful because most of the market today is still running on in-house built software. So the greenfield for us to come in and be the major supplier there is significant. With the clients that we have, and we have 2,750 client firms today, and we release that number, it goes up every quarter.
If we just sold what we have to the clients we have in that base, we could get well over $1 billion just through upsell and cross-sell of the existing clients. But in addition, there's opportunity for us to go win a much larger number of firms, which we also do every quarter. So there's a growth opportunity in new client acquisition land, and there's a growth opportunity in expand. And then we do internal development of features. You see us every February with our announcements of new features that are monetized to go out. And then we've had an M&A strategy for certain parts of the platform that has brought new capabilities into the organization. So I think it really is a rich environment for us to grow into.
And so we've talked about the fact that our next target is $1 billion, and we'll see what happens after that. But it's a big underserved industry.
A question. And the technology is unique, and you folks have kind of discussed it in terms of thesis and delivered on it. One of the things we've always focused on is, right, your clients are your best ambassadors, right? And if you think about KPMG, having come out of Deloitte myself, right, they're not going to scale up unless there's a massive opportunity because they have so much fixed costs. So number one, they were able to underwrite your product because of how unique it was, right?
And again, you entered that partnership when you probably have about $300 million in revenue. So maybe talk through that alliance as well as Microsoft because what you've seen each and every year is those partnerships and alliances get tighter, and you've broadened that out.
And the subtle undercurrent to that, at least for me, is you've got a level of distribution that you just haven't had, not only from kind of the go-to-market, but also as they start to market your product. And it's a really important part to the story and just really endorses the caliber of your software.
One of the interesting things, we were privately held. We were employee-owned for a long time, and we came public. And I think part of coming public created a level of transparency that allowed us to form some of these much larger relationships and capitalize on the footprint we had started with. The KPMG partnership has been a very important one for us.
Several of the large consultancies have helped us to get into some of the large institutions. Many of them have existing relationships with the Bulge Bracket Investment Banks, for example. And when we have a chance to work with those, we can work with one of the big SIs, and we have kind of a trusted relationship from the beginning. There's a lot of opportunity in other parts of the partnership ecosystem. You asked about Microsoft.
Our relationship there is, we always were built on a set of technologies that were very Microsoft-friendly because the industry is very Microsoft-oriented that we call on. But after the IPO, when we got to a scale that we could really get some of Microsoft's attention on this market and they saw how we were growing and what we were doing for Azure, we were able to form this relationship with them.
So we have a technology relationship that Thad can talk about. We had the head of Microsoft Copilot on stage with us at our event, the client event last year. We have a co-marketing partnership with them, and we have a co-selling partnership with them.
So today, if you are a client in one of these industries that we call on and you have a Microsoft Azure spend commitment, you can use that dollar for dollar to buy anything that Intapp makes. So this has really helped us because it's taken the budget question off the table for many of the firms that we're dealing with because they're already committed to spending the money with Azure somehow.
And so our sales team can go and make that case. We talked on the earnings call most recently about a big Bulge Bracket Bank that we won, but there's some examples across each of the industries where we're doing that each quarter. The Microsoft team also gets quota relief when Intapp sells its products. So their sales team is closely aligned in interest with ours, and we're selling well together.
This fiscal year, for the first time, Microsoft set up a professional services dedicated sales force. So in prior years, we were working with a much larger number of Microsoft sellers, but this year we have a very defined team. And so our salespeople and their salespeople are really getting to know each other and calling on deals and winning deals together. And then this year as well, they've started to put some Azure credit into the mix when we're doing deals to help us land accounts.
So we've actually won quite a few deals with both the Microsoft Azure agreement, quota credit for the sales team, and also sort of an incentive that they're providing to help us get folks over the line to get onto the Azure platform.
And that's their interest really, is how do they bring industry-specific technologies and AI into the marketplace with us so that they get more Azure and Copilot consumption.
You're seeing this crystallize in the financials. I mean, you've seen upwards of 121% net revenue retention, which is just industry best, and you've been able to execute and walk that up over the course of time, which has really been important. Again, we're thrilled to have Thad with us today. We were introduced at their last investor day, and I thought Thad did an amazing job, very eloquent in terms of the AI strategy, which you folks have been at for a while. Maybe we'll talk to that a little bit. And as we think about the opportunity for you folks, it's across your income statement, right? It's not only on the revenue side, but also on the expense side. Maybe talk to the go-to-market motion, some of the early successes, and how you're seeing that expressed across your client base.
Yeah, happy to. So as John mentioned, we have been in AI very heavily for a long time, starting in the ML generation, working through deep learning. And with the emergence of generative AI, we think about it as almost this mini arc of innovation. And that mini arc has been heavily focused on natural language, and you're seeing a lot of the initial use cases focus on document review, document analysis, redlining, document generation.
And sort of that wave, which there are a number of companies focused on that, are really focused on sort of more of the junior professionals and their day-to-day activities. And we do have generative AI built into our products, which we've launched two years ago. But where we are really excited and where we see technology emerging in our industries is in the agentic AI.
And we think that is a massive, even bigger opportunity than sort of that initial wave of generative AI because we're getting into automating not just sort of tactical document manipulation, but the automation of the fundamental value chains of these key workflows that drive the competitiveness and ultimately the financial performance of these firms. So you think about how do they win and grow clients? How do they cross-sell additional services into their key clients?
How are they originating the best deals and leveraging the collective relationships to get first mover advantage? How are you converting billable time into realized cash? And then all the compliance regimes that they have to manage across global multiple jurisdictions. These are the areas that we think senior leadership and the senior partners are losing sleep over and think about every day.
That's really what our clients are asking us to go build, and we are running full speed at that. So we're really, really excited about where our AI vision goes and our AI offerings go.
It's helpful. And maybe talk about the consumption because we were chatting earlier, and I think you're seeing the adoption at much higher levels of the organization, I think, than what you've seen historically. So maybe talk about that a little bit because I think that's important in terms of not only the adoption, but what we've seen so far is, and one of the questions we've gotten a lot is, okay, does this get competed away? We haven't gotten the sense to get competed away. They're redeploying that capital elsewhere. And it's driving more, to your point, just deeper into the organization and allowing those folks to do a lot more with just more efficiency. So maybe talk to that a little bit. And again, it's legal, professional, very highly complex, very high risk areas that, quite frankly, you just can't get wrong, right?
And it's just you help that precision, really.
Yeah. So I'll hit the second part and come back to the opening part on the sort of the packaging and the pricing. But we absolutely see the collection of data from the transactional systems, the workflows that have gone into creating and curating that high-quality information, the compliance and governance that comes with that.
All of that has been built up over 10 years, and that is fundamental to how you enable high-quality, high-precision AI on top of it. So it really is almost two sides of the same coin, not a totally new separate thing coming in from the side. And one of the, I guess, maybe limitations of SaaS writ large has been adoption has typically trended to the more junior side of organizations.
With the emergence of Generative AI, it's almost like a new UI/UX paradigm being introduced for more senior audiences where they can get really easy access to highly accurate information if it's stored correctly and if it's structured correctly in a way that they would never have done before. They would never have gotten their own credentials, logged into an application, gone and generated a report and do that.
We have a really cool anecdote from the head of Starwood recently that John talked about on the last earnings call. We're walking onto the set of CNBC, was able to open his phone and just get instant access to some really, really important information that came from the Intapp systems, whereas he would never have done that before.
So we look at this as a real augmentative new experience and paradigm on top of SaaS and those systems of record and all that data that you were talking about that is fundamental. So it's two sides of the same coin there. In terms of the packaging and the structure, whether it's enterprise or seat-based or consumption usage-based, we have done every one of those over the history of the company.
We were telling the story earlier. One story from our history is we have the market-leading conflicts of interest product. And when we first launched it into the market, large law firms had very, very large conflicts clearance teams, typically made up of billable attorneys. And so there was a high seat count, and we sold conflicts by the seat.
As we started penetrating the market, our software helped them meaningfully reduce the size of that team to a very specialized, dedicated group of conflicts analysts that were not billable attorneys. And now that that group was 10% of the size, we were able to change the monetization structure to being an enterprise agreement, and we were able to get higher prices because of that. So we have experience in reacting to the best approach.
We really think about the most important part being, are we unlocking trapped value for these organizations and the way that we monetize it might differ. With the recent acquisition of TermSheet and the agentic platform there and the Starwood example, we actually are using a usage-based approach, which we expect to see more of as more agentic offerings will come out in the near future.
It's helpful. This is a very important topic. Open it up to the audience. If anyone has any questions in the audience around this, we'll keep kind of going into it a little bit deeper.
I'm curious to talk a little bit more about the transactional buyers. I was just curious about the shift to a seat-based model. If AI makes it so you need fewer junior people at these firms because they can do the work more efficiently, how do you monetize that if you're monetizing on seats now? And where are you in the process of developing that go-to-market scheme and conversation and pricing evolution?
Yeah. So the question is, if AI makes the firms more efficient and they find efficiencies in headcount, how does that affect us or any company that's based on a seat-based model? So one thing to understand about us is we actually have more than one licensing model today. So as Thad described, we've gone through evolution over the history of the business.
I think we've benefited from a consistency of serving this special, highly affluent, and regulated market over the years. We've actually served it through multiple technology generations. We're quite different from a traditional horizontal software company that tends to live as long as one of the tech generations lives, and then it gets supplanted by the next group.
We've gone from an on-premises appliance-based business to a software on-prem business to mobile technology to cloud, and more recently, over the past decade or so, machine learning-based AI and now generative AI and agentic AI. So our focus on the end market has allowed us to focus on solutions of applying these technologies.
So when you see our language, we talk about applied AI, and that's what we're communicating, is the ability to bring with our special expertise the opportunity and the potential of each generation of technology to the market.
And they really trust us. We've built relationships with these folks over the years that they stick with us. We've gone through the evolution from a seat-based model to an enterprise or a firm-size-based model. Sometimes that's based on revenue. Sometimes that's based on another metric.
In our contracts today, based on our historical experience with these firms, we have the option of pricing and packaging our software in multiple ways. We made that transition for some of the reasons that Thad explained. We're very interested in this evolution towards a consumption-based opportunity.
One of the things we want to be careful about is a pure consumption-based model has pros and cons, and you want to have a stable revenue stream. I think there's an opportunity for us to have more of a consumption-based factor, but also have consistent growth and reliability through ups and downs.
We bootstrapped the business right through the 2008-2009 recession. We grew right through that, which I think is evidence of the resilience and special nature of this end market to allow us to do that.
But we had some real benefits from our historical contracts with those clients. Ultimately, I think the clients will go with us as we change the model. When Microsoft came out with Copilot, they made a call to price that by the seat for the first years of the technology, and we wanted to do something that was familiar with AI, so we followed that pattern.
I think what you're seeing now with the TermSheet acquisition and some of the agentic platform is a little bit of a different pricing model. And I think as long as we stay focused on the value to the firm and they are experiencing the kind of retention numbers, as Kevin mentioned, cloud NRR of 121%, it's very difficult for these firms to take the stuff out once they get it in there. They're getting real value from it.
We will evolve the pricing to follow the model. And I think folks are happy to pay it, actually, if they can get the value for it because the people that we tend to sell to are the senior executive teams who are worried about these revenue and profitability issues that the firm is trying to manage.
Their own businesses can be under pressure too. What's been amazing is they've been very consistent in terms of beat and raise, beat and raise, beat and raise. They're not immune from a macro perspective. ECM's been light, M&A's been light. A lot of your clients are law firms, and you've been able to power through that. It's just the value, I think, you bring to bear from an efficiency perspective, but also how critical your product is to their revenue generation as well, right? I mean, it's a critical part to what they do.
Yeah. We've focused in both ways. So part of our ROI story, to give you an example, in the conflicts clearance area, we cut 60% of the cost for clearing new business, but we also cut the time for people to bring on new business from about a month to about a week or sometimes down to three days.
So when you're stuck in clearance and you can't get the matter open and start billing for it, you can lose the opportunity to a competitor. So there is a real race in this area. And a lot of our focus has been on that combo.
In the time business, we do a lot around compliant time because there's a strong program from the corporate clients to all these firms that if you don't bill exactly as you agreed in your engagement letter, which, by the way, are individually negotiated with every single client, it's a very interesting industry.
They will not pay the bill, and you'll get into a dispute around the bill, and then you end up writing it off, and it's a major source of profit loss to these firms, and a lot of our technology is about the hard ROI that comes from avoiding that kind of situation.
We have great relationships with the professional indemnity and malpractice insurers around our whole compliance issue, which saves them hard money on their insurance agreements.
And then on the revenue side, we're doing a lot about helping the firm capitalize on the intellectual property and intellectual capital that's embedded in the brains of all of these professionals around the world who work in these firms. If they can just unlock that, they probably can win any deal in the world, but the hardest thing they've had is how do they get them all organized?
And so this moment of AI is such a huge opportunity for them, not just on the efficiency side, but on unlocking the untapped potential of the knowledge and expertise by connecting people across the firm with the right expertise to the right opportunities, to the right client engagements to win the business in the first place, or to bring follow-on business for additional practice areas or service lines to the firms later.
It's a really exciting opportunity for this AI moment because there's so much you can do inside these firms to take advantage of the potential of this generation. And I think we're just really well positioned to be the people who apply this technology to help folks succeed.
And I think the key we see is, right, your technology-enabled as opposed to displacement because, again, it's such a relationship business, particularly at the senior level. And as AM Brief said, it helps drive more efficiency in their go-to-market, win more business, and you become more embedded as opposed to disruption risk. It's actually pretty phenomenal.
And I think the firms take a lot of most of these firms. There is still a professional identity that the people who are running the organization have. They really feel it's important to think about the client, to think about the client relationships, to think about the client obligations, to think about their expertise as professionals and a collective group of professionals with that expertise.
How do they capitalize on the intellectual property and knowledge and experience that they've already assembled in their human platform across the world? And this AI moment is such a moment for them to unlock and release that. And so what we're really focused on is being the platform that enables that for the firm as a whole.
You can think of it as the firm AI system that helps release the potential of all the expertise across the firm overall.
And that really wins. When you talk to the managing partners and the CEOs of these firms, they nod when you talk that way. So it's been a really fun project.
Particularly when you think about their go-to-market relative to, and again, there's all different types of law, right? But in interpretation at the federal level versus state and local, those judges are at a much different evolution than where a lot of this private practice sits, and they can leverage cases to help drive the outcome for them. And that's just, there's a lot there. We're up on time. I mean, it's super effective. Anything within that? I mean, again, it's great to have both of you, but.
No, we really appreciate everybody's time, and we're happy to talk to folks. Thank you for spending time with us.
Thank you, Yes.