IntApp at Bank of America Conference: Strategic Focus on AI and Growth

On Wednesday, 04 June 2025, IntApp Inc (NASDAQ:INTA) presented at the Bank of America Global Technology Conference 2025. The company provided a strategic overview of its vertical software business, emphasizing its AI initiatives and financial performance. While showcasing its resilience in the financial and professional services sectors, IntApp also highlighted its disciplined approach to balancing growth and profitability.

Key Takeaways

• IntApp specializes in cloud solutions for financial and professional services, leveraging AI to meet industry-specific needs.
• The company is focusing on its top 2,000 clients, which represent over 70% of its Serviceable Available Market.
• Strategic partnerships, particularly with Microsoft, are key to IntApp’s growth and innovation.
• IntApp is optimistic about future growth, driven by AI advancements and a resilient demand environment.

Financial Results

• Revenue Growth and Long-Term Model: IntApp has shown strong diligence in financial performance, with a near-term long-term model indicating confidence in achieving financial goals.
• Margins: The company is experiencing significant margin expansion, reflecting effective financial management.
• Strategic Investments: IntApp is reaping good returns on AI investments, encouraging continued investment in this area.

Operational Updates

• Focus on Top Clients: By concentrating on the top 2,000 clients, IntApp has increased its deal pipeline and win rates, with these clients representing over 70% of its Serviceable Available Market.
• AI Innovation: IntApp has launched AI-driven features like Assist SmartTags, Assist Prompt Studio, and Assist Origination to enhance platform capabilities.
• Microsoft Partnership: The strategic partnership with Microsoft includes co-innovation on solutions like Walls for AI and integration with Microsoft 365, enhancing user experience and compliance.
• Customer Event (Amplify): The Amplify event showcased significant product announcements focused on AI-driven features to boost productivity and decision-making.
• Cloud Adoption: The shift of professional and financial services firms to cloud solutions is a major demand driver for IntApp.

Future Outlook

• Demand Environment: IntApp anticipates a resilient demand environment due to the stable nature of its target industries and their diversification.
• Growth Opportunities: The focus on larger clients, AI innovations, and strategic partnerships positions IntApp for future growth.

Q&A Highlights

• Vertical vs. Horizontal AI: IntApp’s vertical AI approach tailors solutions to the specific data, compliance, and workflow needs of its target industries, addressing the limitations of generic AI solutions.
• Data Protection: Solutions like Walls for AI ensure data protection and compliance, mitigating the risks of oversharing sensitive information.
• Competitive Differentiation: IntApp’s industry graph data model is a key differentiator, offering a deep understanding of industry relationships and processes.

For more details, please refer to the full transcript below.

Full transcript - Bank of America Global Technology Conference 2025:

Ikeda, Software Analyst, Bank of America: Ikeda. I am one of the software analysts here at Bank of America. I am absolutely thrilled to have IntApp here today. We have a special guest, Thad Jampol. You are the Chief Product Officer, and you don’t get out on the road all that much.

So happy and thrilled to be able to do this with you. We also have Dave Morton, CFO. Thanks for joining us. Yeah, thanks for having us. Yeah, absolutely.

And so, IntApp, vertical software business for professional services and financial services. I’m a big fan. I think what you guys do out there is great for all the different professional services and financial services organizations out there. But maybe for those in the room that are unfamiliar with NTAP and those on the webcast that are unfamiliar with NTAP, maybe from a high level. Yep.

You know, what is the background of NTAP? You’ve been there for a long time. Tell us about the kind of the origin story there. And what are you guys doing right now? What is the opportunity that you’re addressing?

Thad Jampol, Chief Product Officer, IntApp: Absolutely. And now thank you again for having us. It’s treat to be here. Yeah. For those that don’t know, as you said, Intap is a vertical industry cloud company focused on the financial and professional

And we take a lot of inspiration from companies like Veeva, who build industry clouds for very specific specialized industries. Our end markets are the large partnerships. So it’s the large law firms, large accounting firms, large consulting, large investment banks, private capital firms, and real asset investors. These are the industries that really drive the world’s deals. And it’s a surprisingly large industry, about 3% of the global economy.

But these are partnerships. And so the business model, the operating requirements and the culture are just extremely distinct from other industries. And it’s one of the reasons that we believe this industry has been underserved and overlooked by Silicon Valley historically. And you think about it, these organizations make deep foundational promises of trust and confidentiality to their clients. They hold a lot of the world’s secrets.

And so they’re regulated in a way that no market is. They don’t sell physical products or widgets or SKUs off of a price sheet that they compete based on knowledge, intellectual capital, and these longstanding relationships. And structurally,

Ikeda, Software Analyst, Bank of America: they are mainly made up

Thad Jampol, Chief Product Officer, IntApp: of professionals organized not by the traditional functional department, but by area of expertise. And so we look at this and say, look, these are very, very profound differences. And these industries, because of that, require hyper specialized solutions and software, which is where IntAP comes in. And IntAP offers a very broad operating platform purpose built for this industry. And it’s made up

I talked about the product. So it’s it’s made up of four main product lines. We have a solution that helps firms win new business by managing the complex web of deals and relationships and clients, investors, and intermediaries. We have a solution that helps firms execute and deliver on that work collaboratively and efficiently. We have a solution that it’s a work to cash solution to ensure that these firms get paid for all their work and that they could distribute maximum profits back out to the partners every year.

And then we have a compliance suite that sits underneath everything to help them navigate this sort of complex set of compliance and regulatory obligations that they have. Got it.

Ikeda, Software Analyst, Bank of America: Sounds like you got I mean, I know I know you guys do that. Sounds like you guys have a front office and back office platform for industries that are data driven, trust driven, knowledge driven Absolutely. Which which makes it difficult for horizontal vendors to to be there, not only from a well, let me ask you that question. You know, it I I I remember during the the IPO period, we talked a lot about, you know, Salesforce. Right?

Salesforce can do this. You know, they have a horizontal solution that can do it, but maybe it’s not the best solution or from a feature standpoint and then maybe from a cost standpoint. And so what are some of those things that the platform can do that makes it better, faster, more cost effective than something like a horizontal platform?

Thad Jampol, Chief Product Officer, IntApp: Yeah, absolutely. And not coincidentally, you’re going to see some dovetailing with the difference between AI as from the horizontals versus vertical AI. But the answer is sort of the same. You come back down to starting with the data. And horizontal systems are really built for the manufacturing and retail worlds.

They have very linear processes. And you think about just as an example, a typical transaction. There’s a buyer, there’s a seller, there’s an asset or a SKU, and there’s a bunch of people around that on each side. But in this industry, there’s co investors, there’s referring banks, there’s lending syndicates, there’s diligence teams, there’s advising counsel, there’s opposing counsel. And so all of these different stakeholders are critical to how these firms operate and you need to be able to capture that so that you can reflect it back.

And so I would put data as a big one. I think a second one is compliance. As again, I was talking about this compliance is existential to these organizations. Everything these professionals do is subject to conflicts or confidentiality or regulatory scrutiny or professional and ethical responsibility rules. It’s not a check the box thing.

It’s not an after the fact bolt on. And again, I’m probably jumping the gun here, but in AI, this is one of the big obstacles and encumbrances of this first wave of AI, because it doesn’t really think about the very profound compliance requirements and obligations that there’s a compliance set. Then thirdly is we are so intimate with the way that these workflows and processes happened as part of our industry orientation that, that’s a big one. Understanding how are you augmenting and supporting these hyper busy professionals in the way that they work and within the tools that they work. And again, each of those three, whether it’s the data, the compliance obligations, or sort of the workflows and processes, we just feel like we have a big advantage being so close to this market.

Ikeda, Software Analyst, Bank of America: I know I’ve probably told John, your CEO, this before, but I’m still waiting for the equity research CRM tool from you guys. I know that you guys do a lot of investment banking Yeah. In a kind of deal deal management with the deal cloud. But, when are guys going to come out with the research product? Maybe a question for Dave.

You know, how do we think about the demand environment? Maybe split between broadly professional services and financial services. What does it look like today? How are thinking about it for

Thad Jampol, Chief Product Officer, IntApp: the future? Yeah. I mean, I

Dave Morton, CFO, IntApp: think our bigger context and some of the moves we made earlier this year with our go to market and looking at where some of the bigger opportunities were coming. You know, before, we kind of weighted everything the same. Whereas what we talked about at our Investor Day, we saw over 70% of our Sam Tam coming from the top 2,000 plus clients. And so that’s where we kind of started over indexing on that go to market motion. And as a result, we’ve continued to see bigger pipe, win rates, a lot of strong deals come through that whole ecosystem, not only for this year, but then, you know, looking at this quarter is what we talked about not only, couple month and a half ago on our earnings call, but then even into FY ’20 ’6.

We are really excited about those opportunities. We’ll be excited to talk to you all here at the end of the quarter as well as what that implies for specifically for FY ’20 ’6. So we believe everything that we’ve done as well as the rate of pace of innovation that dad and his organization has brought on, we feel that we’re positioned really nicely for how this company is continuing to deliver.

Ikeda, Software Analyst, Bank of America: Okay. I’m gonna start macro and kind of bring it in slowly down You know, vertical AI. But just starting macro, the demand environment within the Mhmm. Categories that you’re operating in, professional services, financial services, has been proven to be pretty resilient, kind of IPO time through the COVID ups and downs, the recessionary fears.

And even in today, you guys have been pretty darn good. What is it specifically about the professional service and financial services end market that really creates this nice end market, right?

Thad Jampol, Chief Product Officer, IntApp: So I think it’s a few things. I think first, we’re very fortunate to have an incredibly stable end market. And even in sort of the down markets and as it fluctuates, you’re gonna pay your lawyers, you’re gonna pay your tax professionals, you’re gonna pay your auditors. And when you think about the private capital partners, you know, they’re getting paid at 2% out of their management fees, but it’s from a fund that has a five, seven, nine year lifespan. So it’s just, it’s long enough where they can weather whatever ups and downs there are there.

I think secondly, there’s just an inherent diversification in our markets. So a lot of these firms are made up of sub businesses of different practices or different service lines or different asset classes and strategies. And so we have seen in the past a shift in go to market and investment. So in a down market, you’ll see accounting firms maybe move from advisory stronger into the audit side. You’ll see firms move from some of the cyclical transaction work into more countercyclical litigation, restructuring, bankruptcy work.

Even the private equity private capital firms, they’re inherently diversified because they have portfolios of different assets underneath that. So there’s diversification. And then lastly, I’d call out and perhaps counter intuitively, and we’ve seen this going through the two thousand and eight, two thousand and nine financial crisis and COVID that firms, when you take the foot off the pedal a little bit and the go, go, go, deal, deal, deal side, they have a moment to go enhance their operation, to go make some investments that they’ve wanted to do for a while. And they’ll spend in the areas that they deem strategic, even while they’re reducing and cutting some of the ancillary areas. And we’ve been very fortunate to be deemed within those strategic categories.

And we’ve done some of our biggest deals in the depths of financial crisis or COVID.

Ikeda, Software Analyst, Bank of America: Let’s move to AI. Okay. We’ll start a macro on AI.

Thad Jampol, Chief Product Officer, IntApp: Correct. Tell

Ikeda, Software Analyst, Bank of America: me a little bit about why vertical AI is maybe differentiated from horizontal broad AI.

Thad Jampol, Chief Product Officer, IntApp: Yeah. So I touched on some of this earlier, but we talk to our customers a lot. But there’s two particularly moments that I think are really illustrative. So in the beginning of the year, we have a CIO advisory board that we host in Redmond together with Microsoft. And we invite a few dozen of the most influential innovative CIOs and we talk there.

And then follow that we have an event we call the ambassador event where we invite some of our biggest power users. And when we had these sessions last year, 2024, there was a lot of optimism on the first wave of this generative AI as we were talking about mostly from the horizontals because they were early out of the gates. They were piloting, they were trialing it. When we got together this year, the tenor was very different, that they felt that while a lot of this technology had cool aspects to it that had potential, it ultimately didn’t deliver the outcomes they were looking for. And I do think it comes down to those three things.

At least this is what I’ve been told is that it’s not using the firm’s data. Like these models are so powerful and they’re incredibly innovative and we’re excited about them, but at their core, they’re inherently generic. They’re raw technology trained from information across the broad internet. And that is part of its power, but the broad Internet doesn’t understand the precision of the deals and the transactions and litigations that these professionals work on every day. And so it just it didn’t use their data.

Secondly, a lot of the general counsel’s office and compliance offices just put the brakes on these when they started panicking about the oversharing risks that these co pilots and models might introduce into these firms that have, they have MNPI, they have PII, they have trade secrets, they have comp information all over the place. And a lot of these first wave of innovations didn’t really consider the implications of that. And then thirdly, and I think this is probably the biggest one is the professionals never really adopted en masse the tools that came in. And so I think this is because these initial waves of generative AI are they’re separate panes of frames that sit on the side of your screen. They’re blank with a blinking cursor.

We joke that it feels like MS DOS. They just sit there and they ask you to type in something inspirational or something really important and you get natural language back out. But it puts this incredible cognitive burden on these very, very busy professionals. And it’s asking them to context shift away from the other applications and working on the deals and working with their clients and fighting their competitors and developing prospects to jump over to this other screen that’s blank, enter something, get the results, find a way back into your application or your workflow. So those areas, I think people were very suspect of.

They’ve shifted their focus now much more practically into more vertical AI to your point. And they’re really focusing on grounding the data within the firm’s proprietary information, having a compliance confidentiality first offering and ensuring that the AI is manifested directly within the workflows and the processes processes and the productivity tools that the professionals are using every day. Is

Ikeda, Software Analyst, Bank of America: the thought process here within your industries Mhmm. A blinking cursor chat GPT screen. How can I help you is not how can I help you? Because the cognitive burden that you’re placing. How do you bridge that from with what the offerings that you have there were something where I’m afraid to put something in here because I don’t know what’s going to happen with the sensitive data and compliance and everything.

How do you make that easier, more digestible for So

Thad Jampol, Chief Product Officer, IntApp: I’ll answer that in two ways. Starting with the end of that, which is the, how do you have confidence, trust that all this AI is going to be compliant and work with what you’re doing? So the first thing to do is to ensure that all of your information is protected. And it sounds fairly straightforward to do, but all of these innovations from Microsoft and the productivity tools, are incredible, all the Teams and the OneDrive and all the m three sixty five, they’re so collaborative. They make it so easy to unintentionally do something that reveals or shares sensitive information.

You need the counter to that. And that’s an area that Microsoft and Intap have worked together on. It’s in our mutual interest. And so we have a confidentiality solution that we call Walls for AI, and we launched it on stage last oh, one of our big shows, and we had the head of copilot on stage with us. And it really looks at the overall sort of data landscape and identifies where sensitive information is.

Is it protected? Is it not protected? And then the walls product is a centralized place that can enforce the right confidentiality policies across all the different systems. So that’s sort of the first part of your question. The second part of your question is how do we bridge this gap from the blinking cursor?

And this is where it gets really exciting. So if you look across a lot of our applications, I’ll pick a few out of the air. You look at time. We have a time product that helps essentially lawyers track their time and ensure that they get the bill out of this. We use AI to capture it and we could embed right there in the application.

We can tell you all the time that you worked. We can tell you what your time sheet is. You can now talk to it. It will build out a narrative. The AI will figure out if that narrative is actually a good narrative.

And if it conflicts or violates any commitments you’ve made to clients, it’ll tell you, then it will suggest changes to it. It’s right there in the application. You don’t need to go anywhere else in our conflicts of interest products. So a lot of these firms before bringing on a new piece of work, you have to go through a fairly rigorous process to ensure that you’re not representing somewhere the opposite side of a deal or a litigation or something like that. And we have AI embedded right there that will say based upon the way this firm operates and what we’ve seen from other organizations where risks, here are the areas that you might want to double click on and spend some additional time because we think there might be something at risk here.

Or within deal cloud, within our product that allows you to go win more business, we can embed right there capabilities, allowing you to go see all of these exciting opportunities that you might invest in based upon your historical investment. So the list goes on and on. The point to take away here is that it’s embedded directly within these applications in context at the moment that you need it.

Ikeda, Software Analyst, Bank of America: So it sounds like you guys are doing all the right things with AI. I’m gonna put my more balanced hat on for a And so what’s the catalyst for your customers to adopt this stuff? What are they waiting for? Are they still waiting? I mean, how do we think about what gets them to start really buying this

Thad Jampol, Chief Product Officer, IntApp: So surprisingly, or maybe not surprisingly, a lot of people here probably work at a firm within this industry that these industries have been a little slower in the core of digitalization and the digital transformation. And a lot of the trends that we’ve seen of moving to the cloud and other industries are still happening right now in this market. We’re working with a ton of organizations and helping them move their older on premises in house built tools over to our modern cloud and SaaS solutions. And that is a big demand generator for us. But then on top of that, what really gets them excited is that that is an enabler of generative AI because you have to be in the cloud really in order to take advantage of this.

And they like we are huge believers and very bullish on the potential transformative opportunities of generative AI and the way you operate and compete. And so we’re seeing this opportunity and this demand generation for both the cloud and then the generative AI on top of that. And then compliance is the third one, again, very existential to this industry and they want to get it right. And they also see the yin and the yang between having the right compliance and confidentiality underpinnings, allowing you to bring in all of this generative AI and be able to take advantage of it in a safe and trusted way.

Ikeda, Software Analyst, Bank of America: Throughout your answers, Tad, you mentioned Microsoft, you mentioned Seattle. Yeah. I know you guys have a big partnership with them. We do. But maybe for those in the audience and those in the webcast that aren’t unfamiliar with your partnership with Microsoft, Tell us about it.

How deep is it? And where’s that going in the future? Sure.

Thad Jampol, Chief Product Officer, IntApp: Yeah. So it’s about three years in right now. And I would There are many pieces to it, but I would call out really two big pieces. The one that gets our clients most excited is the co innovation side of this. And we, every year that has gone by, we’ve gotten closer and closer to the engineering teams.

We’re talking to them regularly. We’re co innovating in a number of areas. I talked about walls for AI. That’s a very important one. We really are looking to make sure that all of our innovations, again, this blinking cursor point, meet professionals where they are today.

And they’re not just requiring this big context shift. One of the places where a lot of professionals are in our industry is in M 365 and the office suite. So we have a lot of initiatives together with Microsoft to be able to natively plug right into teams or right into copilot. So we have a lot of progress there and we share a lot of it in our big Redmond meeting and that’s really exciting. We’re also really excited about the go to market and the co selling together with So Microsoft has these Microsoft Azure minimum commitment agreement, spend agreements, they’re called MAC agreements.

And what’s really, really great because we are in the top tier of their partnership is that custom firms will get dollar for dollar credit against their committed Microsoft spend buying Intept products. And so we actually just had a really, really big account who was kind of on the fence between buying deal on buying deal cloud say, oh, I could use the max spend because your product is in the Azure marketplace. It’s essentially free for me if you’ve got that dangling out there. So in certain situations, it’s been a real catalyst and an accelerant of deals. And all of these firms and all of them industries that we serve are very heavy Microsoft users.

Ikeda, Software Analyst, Bank of America: Okay. Okay. Tell me about Amplify. Kind of a big event that you guys had, lots of big announcements. Yeah.

Yeah. I it, but I’d love to hear, you know, kind of your view and and some of

Thad Jampol, Chief Product Officer, IntApp: the big announcements. We’re really really excited by that. So Amplify is the name of our big annual customer event. It’s very heavily product oriented. We share a lot of r and d, a lot of our innovation.

We make a number of big product and SKU announcements there. It’s held in New York. Last Amplify in 2024, we announced our Intap Assist brand, which is our generative AI brand. And we launched our Assist for DealCloud SKU. We’re really, really excited about the uptake that’s had in the market.

And then we followed that up with a number of other assists in our product line SKUs. This Amplify, which we just had in February, we doubled down on AI and we made a number of, I think really, really exciting announcements that went over really, really well with our market. And just to give you a few examples, we announced Assist SmartTags. Assist SmartTags uses AI to analyze all the conversations and call notes and meeting transcripts that happen throughout the day within these organizations. And then to be able to identify the interesting nuggets of intelligence and then bring them to the relevant stakeholders instantly there.

And so this is critical because you think about how many of these conversations happen every day. These are relationship based businesses. So the number of calls and meetings, I mean, it’s hundreds or thousands every day. And then the insights, the competitive intelligence, the opportunities that get buried in this unstructured data, these call notes that just sit in the system and never see the light of day, it’s incredible. And so what SmartDags is able to do is go in there and find it and bring it to the right professionals so that they can be smarter in front of their prospects.

They can find more opportunities and they can have that extra advantage against their competitors. So that’s SmartTags. We announced Assist Prompt Studio. Prompt Studio allows you to get very granular in the configuration of prompts and how generative AI is surfaced within the application. A great example that I just heard is there’s a firm, this was a sort of a well known middle market private equity firm, and they really wanted to focus on the reciprocity of their advisors, meaning they’re spending a lot of fees with their advisors and they want to make sure their advisors are bringing them leads back.

And so they configured the prompt. I just checked it earlier and they’re able to say, show me right on the advisors page. When I load it up in deal cloud, I want to know our total amount of fees that we spent with this advisor. I want to know how many sell side leads they brought me. I want know how many of those leads converted opportunities.

And I want to know how many of those opportunities we actually worked. And then I want the AI to summarize the health of our relationship with this advisor. It’s a great example of what prompt studio can do. We’ve also seen firms who will want their growth equity partners to really see different information highlighted about companies. So cap tables, growth rate CAGRs, they’ll want to see the private credit team.

They’re going be more interested in EBITDA and free cash flows and, know, debt service credit ratios, those types of things. So that’s Prompt Studio. We announced Assist Origination. This was a big one for us. Assist origination uses AI to go find and source the best new opportunities for a fund or a firm.

And, you know, there’s $3,700,000,000,000 of dry powder that these firms have to go commit and deploy. We think the winners are going to be the ones who are most able to go directly source the best new platform acquisition or add on acquisition faster than their peers. And the magic of this is the data. And we bring together all of this private company information from across the internet that we use Delphi, a company we acquired a few years ago to do. We combine that with a lot of firmographic data feeds that firms use through third party subscriptions and then firms proprietary data itself within deal cloud.

Have I met with this company? Have I done workups for models? Have I made bids? And it’s all surfaced directly in deal cloud. So it’s just right out of the bat integrated with all your your workflows, your pipeline, your Monday morning meetings, your investor committee preparation.

So you get this incredible force multiplication effect of coverage, sourcing BD teams of 25, 30 being able to do the work of 40 or 45. And then we had a time for AI, I talked about that. We had walls for AI, I talked about that. It was, there was just a lot of AI top to bottom. We introduced about a half dozen additional monetized AI skews.

Ikeda, Software Analyst, Bank of America: Wow. Just listening to that, would love to have assist smart tags for equity research.

Ikeda, Software Analyst, Bank of America: So if

Thad Jampol, Chief Product Officer, IntApp: you could

Ikeda, Software Analyst, Bank of America: do that, would love that. Throw that in there with equity research CRM, then thanks.

Thad Jampol, Chief Product Officer, IntApp: I didn’t know this was a pipeline generation event.

Ikeda, Software Analyst, Bank of America: That all sounds great. And so how are you guys differentiated? Or how are you going to keep this differentiated from the competition? Because I think about two things. One, clearly professional services, financial services, good growth.

I mean, guys show great growth in your SaaS. SaaS numbers, Cloudera, I mean, good numbers there. And so I always fear that people will, the horizontal vendors might recognize this and come after you. And so then it becomes product, right? Product will win.

And so talk to me a little bit about why your product is differentiated today and how is it going to continue to be differentiated?

Thad Jampol, Chief Product Officer, IntApp: Well, it’s a great book end question. I opened with sort of the company and you had asked about some of the company’s beginnings. And when we started the company, we bootstrapped it and we got into law firms very quickly. The law firm that was doing our patent work looked at our product and said, we should have this. And we hired their CIO as our first seller, and they brought us into a lot of this this very insular self referencing community.

And what was so serendipitous for us is that we were middleware at that time. We were integration. And we didn’t see just one application area that we really understood the whole application landscape. And we understood more importantly, the data model. And so that was the formative start of really building what we call the industry graph data model.

We think this is one of our big innovations and one of our long term durable technology moats. And it really is, reflects the way that these industries and professionals work. And we can capture that information that AI so desperately needs. I use that example of sort of a transaction. That’s an example of that.

And because of this industry graph data model, you could answer these big strategic questions, which are not new, by the way. They’ve been out there for a while, but no one’s really been able to really do this. It’s sort of like, you know, what business and what segments have I been most commercially successful so I could do more of that? Or who in my network has more influence or referred work to me so I could spend more time with them? Where are the best deals for my fund?

What is the likelihood of transaction? And what is my best path of introduction? So I have a first mover advantage or where are the best follow on work or cross sell opportunities so I can develop my clients. And all of that is based upon having this incredible industry graph data model, which I don’t think one of these horizontals can do anytime soon. Got it.

Maybe the last question, Garen, David, I didn’t forget about you.

Ikeda, Software Analyst, Bank of America: No worries. I wanted you guys are clearly in a in a an attractive growth category. And so as the CFO, how how do you think about balancing growth versus profitability? I mean, you guys show great margin expansion, but does that continue forever? Mean, do you invest more?

How do

Thad Jampol, Chief Product Officer, IntApp: you think about it? Yeah. I mean, we’ve shown really

Dave Morton, CFO, IntApp: good diligence and judiciousness. I think it goes back to the culture of being bootstrapped. And so, you know, this wasn’t a company that was born out of, you know, endless funding and then all of a sudden had to get profitable here in the in the twenty twenties. And so, you know, we are very thoughtful, and we’ll continue to apply economics towards that in his organization, you know, to con keep that competitive mode out there. We’ll continue to drive productivity within our sales and marketing and an absolute reductions in g and a.

We’ve done things with our services model. There could be some room to go there. But all things being considered, yeah, we really like of how we framed up on ’25. We like our long term model. We think it’s within, you know, near reach than not.

Almost time for another Investor Day, might you say. And so, yeah, we’re just really excited about those opportunities. And when you think about some of the returns that we’re getting both on the AI products we’re doing, it’s hard to say why we wouldn’t continue to invest while also contributing to the bottom line. Got it. Yep.

I like that near comment.

Ikeda, Software Analyst, Bank of America: And so we’ll leave it at that. Thank you guys so much. Fun conversation. Thanks so much for coming. Thank you.

Appreciate your support. Thank

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