Datasite's CEO on what deal data shows and where AI agents fit in M&A

• Wiley says deals usually start on Datasite about a year before they become public, and that first-quarter M&A starts on the platform were up 22% year over year, 42% in the Americas.
• He puts the current deal success rate at about 34%, down two points, based on outcome data that clients provide.
• Sell-side teams can use agents to find diligence hotspots, such as change of control provisions in HR contracts, before a sophisticated buyer finds them.
• Wiley argues that uploading data room content to a file store for LLMs gives up the controls on confidentiality and compliance that permissioning and audit trails provide.
• He expects sophisticated firms to work from their own Claude or ChatGPT environments through an MCP server, and most others to want AI inside the data room.
• In private equity, he says, value now has to be created while you own a company rather than at the purchase.

A deal usually shows up in a data room about a year before anybody hears about it in public. That is Rusty Wiley's claim, and as CEO of Datasite he uses it to explain why the exhaust from a data room is worth something. By his count, M&A starts on the platform were up 22% year over year in the first quarter, with the Americas up 42%. Healthcare is sort of on fire, he says, industrials are doing quite well, and in software deals are taking longer with what's going on with AI (around 7:05).

“Now you can just have an agent go read all of them and come back and tell you, by the way, from that secure environment, here are 12 HR contracts that have a change of control provision that you need to analyze because the buyer is going to do the same thing on the other side if they're sophisticated, and they'll find these things along the way.”

Rusty Wiley, CEO, Datasite

Asit Sharma, senior analyst at The Motley Fool, does the interviewing, so this is a CEO describing his own company, and the platform figures are his. He says Datasite hosts about 55,000 deals a year and around 3.5 billion pages, with about 200,000 active users a month. He stresses that the first mission is to protect the data in the data room and that trend data is anonymised. Deal success rates, he says, are about 34% right now and down two points, based on outcomes that companies using the product provide.

“As opposed to just taking all of the content and uploading it into a file store and then allowing LLMs to effectively work against that, you don't have strong controls on protecting confidentiality or supporting compliance, particularly in regulated industries.”

Rusty Wiley, CEO, Datasite

For sellers, Wiley describes benchmarks across 48 sub-industries. Datasite could tell you how many similar deals are actively preparing, how long preparation typically takes before launch, and how long diligence lasts. A long preparation period, he says, usually indicates it takes more work to prepare the asset. A very short diligence period often means a bilateral market: one seller, one buyer, reaching agreement fairly early. He says this insight goes through the seller's banking partner, and that Datasite is not trying to disintermediate or sit in the middle.

“There was an old saying that you can make your money at the time you acquired the company, not the time you sold the company, right? Which is pretty common in private equity. I think that's changed, that you've got to create the value while you own the company.”

Rusty Wiley, CEO, Datasite

The diligence point most readers will recognise is preparation. Data rooms can hold 5 million pages, Wiley says, and today you find problems a document at a time. His example is change of control provisions in HR contracts: an agent can read all of them inside the secure environment and come back with the dozen that need analysis (around 17:18). The reason to do it as a seller, he says, is that a sophisticated buyer is going to do the same thing on the other side. Escalating commercial contracts are another of his examples.

“The risk for everyone right now, and it's very obvious, is what happens with the labs and the LLMs, and being able to the best of your ability anticipate how you make that an asset within your business and within your platform or within your software as opposed to it becoming a competitor to your platform.”

Rusty Wiley, CEO, Datasite

On the buy side, his example is mid-market private equity, which gets many teasers and CIMs. Wiley says clients on BlueFlame, the agentic AI company Datasite acquired, use it to read the inbound emails, summarise the CIM, check it against what the firm has been interested in before, draft an investment committee memo and build an LBO model. The bigger gain, in his account, comes when clients connect it to their internal systems: previous deals, messaging, calendars, email, and why they did or did not pursue companies in the past.

The security argument is the one to take into any vendor conversation. Wiley says everything on Datasite is permissioned down to the paragraph and audit ready, with the agentic tools layered on top. Taking all the content, uploading it into a file store and letting LLMs work against it leaves you without strong controls on confidentiality or compliance, particularly in regulated industries, he says. Datasite's route is an MCP server, which he calls a fancy name for collecting your APIs and putting them in one place. He says an announcement on working with Anthropic, OpenAI and Copilot through it was coming, and that it went from decision to operational in four weeks.

He sees two kinds of users. Hyper-sophisticated buyers and sellers will build their own environments in Claude or ChatGPT and reach the data room from there. An enormous number of people in the ecosystem, he says, just want to do a transaction. They want to be in the data room they are familiar with and ask a question about contracts or HR agreements from a side panel.

How Datasite got here is a short history of the category. Wiley joined Merrill, a 40-year-old financial printer, about 12 years ago, sold every other business in about two years and kept the data room. He says the team migrated the entire customer base to a new platform in 12 months. Under CapVest it bought Firmex in Canada and Ansarada in Australia, then Grata, an AI private company database with about 20 million profiles, Sourcescrub, and BlueFlame, a team of about 50 focused on M&A agentic workflows.

His view of the risk applies to every software vendor in this market: whether the labs and LLMs become an asset inside your platform or a competitor to it. The bigger risk, he says, is losing pace, and just bolting on some AI to defend the existing business. On private equity he makes a broader point. There was an old saying that you make your money when you buy the company, and he thinks that has changed: you have to create the value while you own it.

If you plan to run AI over a data room, ask whether permissions and audit trails follow the documents into the model, and whether your deal data feeds anonymised benchmarks. Wiley's change of control example is an easy first test for any sell-side team.

0:00 Hello Fools. I'm Asit Sharma, senior analyst and lead advisor at The Motley Fool, and my guest today is Rusty Wiley, CEO of Datasite, a leading global software-as-a-service platform that helps enterprise businesses conduct M&A and other deal-making activity. Prior to joining Datasite, Rusty held many senior roles at IBM and served as Big Blue's general manager of banking and financial services. He holds a Bachelor of Science degree in Business Administration and Management from East Carolina University and a Master of Business Administration from Duke University's Fuqua School of Business. Rusty Wiley, welcome to The Motley Fool. >> Thank you. It's great to be here. >> So, I wanted to start with Datasite's history.

0:45 As some people may remember Datasite from a different name in its previous incarnation, and I think this will flow well into your involvement with the company. So, maybe if you can give us a little bit of background on Datasite, we can begin there. >> Yeah, I'd love to. It's now been 12 years ago when I actually got the call from Bain and from Davidson Kempner to have a look at this company at the time was called Merrill. And went and met with them and moved fairly quickly. At the time, I just finished the tour in Shanghai with IBM running banking capital markets for IBM. And you know, the company at that time was a collection of about a dozen different regulated printing businesses. So, if you think about what the heart and soul of Merrill was, and by the way, the company was 40 years old at the time, so already an established company, was financial printing, which is really the process for going public as a company.

1:39 And printing many volumes of S-1s for the purposes of making your announcement of going public. So, I joined there. We also had a compliance business and a number of other things inside Datasite, inside of Merrill, I mean, but there was a business called Datasite that caught my eye. And keeping in mind the the time frame, this is when almost all applications were hosted in data centers inside firewalls, and this was a platform that was converting paper data rooms for doing deals into digital data rooms. Interesting, but the interesting part, even more so than that, was they were hosting the most confidential content a company has at that time outside the firewall and sharing it with different members of the ecosystem.

2:25 Those that were selling a company, those that were buying a company, and those were advising in the process. So, I looked at it and said, "This is a really interesting impactful ecosystem. Let's focus on this business." And so, the short of it was we sold every other business in about 2 years and we're left then with the Datasite business that began fairly modest at the time as a part of the portfolio. And then it was the the next stage of the of Merrill's history, which was really to build a new technology platform, or effectively to incubate a new company inside of what was then Merrill. So, we built a brand new technology organization, we built a brand new technology platform, we brought in an entirely new go-to-market team. But the one thing we kept, which is really kind of core to the company, was a service culture. And one of the things that's very important in our industry is not just to provide a technology platform, but to provide expertise and in some cases help when needed for customers who are trying to execute complex transactions. So, we built that new technology platform.

3:25 And the short of it is we did something fairly miraculous. We migrated the entire customer base from old to new in 12 months. and became the leading platform for doing M&A transactions, or the leading VDR for doing M&A transactions. So, that was kind of, if you will, the first four or five years of the company. at that point, we were acquired by CapVest, a private equity firm out of the UK. there is a funny story I'll share another time about how that happened during COVID, by the way. but they acquired us and really, their focus is about doing inorganic moves in companies to build great companies, not only through what you do, organically, but through acquisition. So, we then made a couple of important acquisitions in the business. We bought Firmex out of Canada, which is a leading VDR provider in Canada. And then we bought off, the Australian Exchange, and Serrado, who is a leading, leading ANZ, but also a leader in Asia in the VDR category. So, that was, the phase of really beginning to aggregate the size of that business and

4:27 the size of, the number of deals that were on our platform. And so, you you you take that stage. And by the way, if you roll that forward now, we host about 55,000 deals a year on the Datasite platform alone. So, it's a it's a very at scale platform serving M&A. But, back to the story, we finished aggregating and building this large content repository. And then what became very clear to us was the tools for, driving productivity around M&A processes were very fragmented and very limited. Often, Excel or Word documents or just PDFs or PowerPoints. So, we started building capabilities before AI really was, im- really was as impactful. And we built an AI tool to categorize content in a data room. We built an AI tool to redact content that might be sensitive from an HR or financial perspective. we did full document translation. So, we kept building things around the data room that would make people more productive in organizing and presenting content for doing due diligence.

5:27 so that was kind of, you know, phase 1B, if you will. And then we really began discussions about the volume of content on the platform and how we could use the content to help our customers in M&A. to give you some context, we have about 3 and 1/2 billion pages of content on Datasite today. all of that is, in that 55,000 M&A transactions plus some other content work that gets done on our platform. So, we knew a big part of successful M&A was the ability to source companies. And so we went out and we looked and we really wanted to stay on a technology forward platform, not a human based information gathering platform. So, we acquired a company by the name of Grata.

6:10 Grata was an AI powered is an AI powered private company platform hosting now about 20 million private company profiles. So, a very large set of profiles in the Grata platform. We made two other acquisitions around that. We acquired Source Grub, which was a competitor of theirs that had much more detail around things like conference attendance, which is a leading indicator if you're sourcing companies of a company might be getting close or interested in selling themselves. So, if you think about it, the basic building block is this large content secure content platform. The next building block is this platform of Grata for private companies, but also for proprietary data. One of the things that we have and and I will be very clear on this. We our first and foremost mission is to protect the data in the data room, not exposing any confidential content, not exposing any names or participants.

7:05 But there is a lot of exhaust that occurs from a data room that you've got 3 billion pages of content and about 200,000 active users a month working on M&A transactions. So, we can collect things as an example like trend data. What's happening in M&A? How long are M&A processes taking? How many M&A transactions have started? I'll give you an example of that. In the first quarter M&A starts, which means people come to our platform and that usually is about a year before anybody hears about it in the public domain are up 22% on a year over year basis. Interestingly enough, inside that data the Americas is up 42%. So, we collect a lot of information. We know what's happening with industries as an example, healthcare is sort of on fire right now from a new start in the M&A space.

7:51 industrial is doing quite well and software within TMT as you would expect, the duration of deals is now taking longer, right? With what's going on with AI. So, what we began to do or what we're doing now is put more and more interesting proprietary content into that Grata platform for the purposes of helping people on the buy side of the world as well as the sell side of the world do M&A, finding the right buyers, finding the right companies, hitting the right timing. And then, about a year ago, a little over a year and a half ago, Agented AI really caught fire. And we were rapidly building workflow into the core data site content platform for doing everything from managing tasks to doing outreach to potential buyers. and we reached the realization pretty quickly that that workflow, not only the research, but workflow was going to move into the agented space.

8:43 and we knew we wanted to participate in that and not really just be that secure compliant content platform. So, we went and bought a very small company, an 18-month-old at the time, called BlueFlame, which is a new member of our portfolio. BlueFlame was a relatively small team, about 50 people. Their focus was purely on M&A agented workflows. and so, we acquired them and then we have invested it very heavily in that business and scaling that as well as scaling the Grata business. So, now what we have assembled over I'd say 12 years, but most of the assembly is actually happening in the last 24 months, is an AI native M&A platform for the purpose of serving the sell side of the world plus the buy side of the world. So, we're pretty excited about where we are. I can tell you that it changes every week and every day in terms of what you can actually accomplish with this platform at this stage, but we feel like we're very well positioned to help our customers going forward.

9:44 >> Some of that might have been more That might have been more than you wanted in a question. >> No, not at all. So, many questions. I I I'm trying to pick my spots where to begin, but let me jump into the middle of your introduction. So, a question cropped up. So, suppose that I am potentially not on either side of the platform, but I would love to have data that gives me some leading indicators on where commerce is going. For example, the layperson like me sees in mid-2027 that M&A activity is up, let's say 15% cuz I'm seeing the close of the transactions. >> Mhm. >> So, do you offer subscriptions to businesses that just want this sort of macro insight data that starts to give you a leading indicator of what might be happening 6 months or 12 months from today? I was just curious.

10:33 >> So, we don't have a specific offering for that. Actually, what we do is we publish a lot of these insights quarterly as a part of what we do for marketing for the industry. So, you'll see that we a lot of things I have talked about are available in a quarterly push my marketing team, and I'll be glad to connect you to that post our post our discussion. the insights have become a little more customized for a client are really available when you're a client of Datasite, whether you're coming in through Grata or whether you're coming in through coming in through the Datasite platform. And And largely because it's becomes tailored to what you're trying to accomplish. So, if you are trying to do a roll-up of companies in the mid-tech space and you're using the Grata platform to search for companies that might be good candidates for your roll-up strategy, and we can augment that with insights that can prioritize certain targets or reach outs ahead of others. It really becomes more personalized to the user on the platform as opposed to just pushing out generic content. But, the generics that I talked about in terms of trends, deal duration, hot industries, cool

11:36 industries, those types of things we do share every quarter and we're happy to share those with you. >> Thanks much. Let's jump into this most recent phase of your business. I wondered if you could describe to us the Agented workflows, what they achieve either on the buy side or the sell side, and what are some of the limitations that you've encountered? In other words, how hard is it potentially to have agent behavior perform as expected, especially when you're dealing with proprietary data that has to be very carefully managed? >> Yeah, and your your last point is a key point I'd like to make and it's kind of where we're positioning the company as a as a partner to our clients and that when we do Agented AI around data sites, so again, think of that content platform is at the base of the foundation, all of that content is permissioned, meaning I know that you have the ability to look at this file and this paragraph, but not the paragraph above that, right?

12:32 So, everything in the platform is completely permissioned. It's also audit ready, so you can audit every movement of content within the platform. So, what we're doing, and I'm going to get to your other question is, we're layering the Agented capabilities on top of that, whether it is you're coming in through an MCP server from your cloud environment or from your chat environment, or whether you're coming in through Blue Flame, which is our our our focus M&A Agented platform. So, we protect it in that as opposed to just taking all of the content and uploading it into a file store and then allowing LLMs to to effectively work against that, you have really, you don't have strong controls on protecting confidentiality or supporting compliance, particularly in regulated industries.

13:17 So, we do that, but to answer your other question is, every 30 days I'll give you a different answer to what you just asked me, which is what is possible and what is the quality of what can be done. So, as an example, what our clients on BlueFlame are doing today is in in private equity as an example on the on the buy side, you will get many many teasers, you will get many many SIMs for companies that are attempting to sell themselves or bankers that are trying to get you interested in a particular company. That's a volume, particularly for mid-market private equity. And so, what they do is they'll use BlueFlame to read all of those inbound emails, to read the SIMs, to read the teasers, to summarize the SIM and put it into your inbox so you've got a really concise summary of the company, of the profile, and even looking at your history of things you're interested in, and letting you know where this falls into, you know, sort of the sweet spot of of your targets. The other thing it will do is, let's say that it's a company that does have some interest for you, it will prepare an investment committee memo on your behalf with all

14:22 of the content from that from that particular SIM and put it in front of investment committee. more advanced things you can do in BlueFlame and on the buy side, you can actually build models, you can build an LBO model for an acquisition. and then, obviously, you can do a lot of research analysis in terms of comparing the company, benchmarking the company, history and perspective of leaders in the company. It's pretty unlimited in terms of what you can do, but the power of a BlueFlame really expands when our our clients connect it to their data. So, if you think about using just using Claude or just using chat in and of itself, you do get access to all of the content that the LLMs and the lab LLMs can access, right? Which is it is enormous, by the way. And you get access to the inference engine, you get access to the ability to present content. But through BlueFlame, what our clients are doing is they're connecting it to all of their internal systems. So, they provide access to previous deals they've worked on. They provide access

15:24 to their messaging platform. They provide access to their calendar, to their emails, to their share files, to all that abundance of knowledge in the organization in terms of things they've worked on, how they've approached them, how they've analyzed them, why would why they haven't pursued companies in the past, why they got why they were successful or why they were unsuccessful. All of that knowledge and insight is pulsing through their internal systems. So, the power of taking a secure platform like Datasite and an Agented AI platform like BlueFlame supported by Grotto proprietary data and your own company data is the what you can do is is is largely unlimited in terms of buy-side analysis. And what it does for private equity is it puts you in the lead for being ready to negotiate and pursue an asset often ahead of when your competitor competing bidders are prepared to do that, right?

16:17 And so, that's just an example of how you can light up the combination of the content and the BlueFlame and Grotto platform on the on the buy-side. Sell-side is Think of sell-side is just the opposite of buy-side in a way. If if I wanted to do a really simplify it, what do you need to do when you're going to to to help a client if you're an investment bank sell an asset? Well, you got to go deep into understanding that business. You got to go deep into understanding their peers and competitors. You got to go deep into understanding their multi-year financials and their operating model, right? And then you've got to work to prepare the content whether it is the teaser or whether it is the CIM to begin to activate interest in that particular asset. But more importantly, where it's now going is being able to analyze the data room. So, as you stand up a data room, and by the way, we have data rooms that have 5 million pages in them. They can be enormously large. So, you can use the AI tools to organize that content, to put it into in into into the index, to get rid of duplication, all the things you'd like to be able to do, just sort of basic organization and prep.

17:18 But some of the new things that are being worked on right now are, okay, how do I look at this company that's getting ready to come to market and understand where the hot spots are going to be in the process of doing diligence? As an example, how do I Where am I am I going to run into challenges around you know, change of control language and HR agreements? I'm going to run into issues around escalating commercial contracts. A million things that can be in there. And today, the way you have to do that to prepare, you essentially will go a document at a time, document at a time to try to figure out, do I have I'll take the easy one, change of control provisions in HR contracts. Now you can just have an agent go read all of them and come back and tell you, by the way, from that secure environment, here are 12 Here are 12 HR contracts that have a change of control provision that you need to analyze because the buyer is going to do the same thing on the other side if they're sophisticated, and they'll find these things along the way. So it's it's it's two sides of the same coin, and we have a luxury of being able to help the buyers pursue an asset that they want to

18:22 acquire and help the sellers make sure that they have the company in the position the company in the best possible light when they go to market. >> Right, and that that last bit is something I'm curious about. If I'm representing a company that's putting itself up for sale, will I have access to trend data to understand where the hot spots of demand are? So this company may be excelling in a space where there's a higher multiple that we could ask for because I have, you know, access to maybe aggregated data or I have a just better way to present. And this is the magic. You have a an asset, you're trying to present it. How do you get that in front of the buyer in a way that will click for the buyer, the buy what the buyer wants? So does it help me leverage that in in any way?

19:12 >> Yeah, and and again, it's I'm going to I will say this over and over again just be careful. It is anonymized data. We are we're not exposing individual deals or or individuals. yes is the answer on a couple of fronts. If I if you're getting ready to take an asset to market in a given theater cuz we actually track 48 different sub-industries on the platform. we could tell you as an example, there are this many deals that are actively preparing that are similar to the company you're taking to market. We could also tell you through the data, here's how long it takes typically to get ready before you launch your deal. That usually is an indicator that it takes more work to prepare the asset for an attractive sale. We can tell you how long you stay in that diligence period because that will tell you by the way often is it a a bilateral market because it's a very short period of time, it's usually one seller, one buyer and they reach a good agreement fairly early.

20:06 We we even collect and this is provided by companies that use the product. We collect outcome. So I can tell you the success rate of deals. As an example, I can tell you success rate of deals right now is about 34% and it's down two points year-over-year. so we can provide that kind of insight, but the way we do it is we do it through your your banking partner. So we're not we are not in any way trying to position Datasite to disintermediate or sit in the middle. What we do is we arm our customers if the investment bank takes advantage of the content we have to provide that kind of insight. same thing in terms of being able to identify the best buyers for an asset. We have a lot of information on the platform that would suggest here a group of individuals or buyers you should consider for this particular type of asset. so yeah, that's that's how that's how we support our customers.

20:56 >> Good point. Want to shift Thank you. I want to shift to a big picture question. So you come in, you take a look at this company and very perceptively understand that the offset print business is going away, Focus on a what looks to be a great property with a lot of demand ahead of it because M&A activity should increase. And you do a really nice job over a several year period with this idea of building internal systems, making the product better, internal growth. You have the private equity phase and you guys have been I think pretty good at the acquisition piece. So, the inorganic part you mentioned. Number one, how do you make the two work in tandem? What is the culture like over there between incentivizing internal engineers to create and be this innovative company and then going out and acquiring other pieces to make the platform better, that the platform more robust? How do you integrate cultures?

21:52 How do you integrate systems? And then part two of this question, what does the future look like for you guys? How will you keep growing going forward? >> Yeah. great questions. I I think the history of the company is important and I didn't really touch on this. So, the way we went from a distant second to the leader in the category of video VDR or the content platform was we had a just a a culture of investing in innovation in the business. So, I'll give you good examples of that. The year of COVID, we invested in the platform. We didn't we didn't reduce investment in the platform and most of our all of our competitors had basically pulled back. 2 years ago when there was virtually no financing to be had for M&A, we invested in the platform that year. So, we have a culture of growing organically through investing in the product in the platform. Now, what happens when you acquire, as you point out, two additional businesses? How do you how do you manage the I I I'll call it the the the the the inevitable friction of

22:56 we were building everything ourselves. We're really good at it, right? Why would why would you go buy someone else? Why wouldn't we just build this ourselves? In our world, we were able to position it and and to a great extent compartmentalize it. and and it made a lot of sense to our teams. So, our organization, Datasite, it has been and is exceptional at building, you know, highly scalable transaction platform, building in security, building in permissioning, building in compliance, doing all things you have to do to make the platform extremely resilient, and make sure that of all things you protect confidentiality, right? we knew we needed to move into the intelligence space quickly if we're going to add value to our customers on both the buying and selling of assets.

23:43 We didn't have that DNA in the building. We didn't have the expertise, not just the the building engineers and product people. We just didn't have deep expertise in terms of how to do that. And so, the message to the company as we went and acquired Gradall because it gave us a really good head start. Not only in having private company data on the platform, but it also created the container to which we could also deliver this proprietary information that I've been talking about that comes off of the of the core transaction platform. So, the company understood that. >> [clears throat] >> Excuse me. And then when you went to the next wave of it, if you thought it was a Excuse me, a big [clears throat] step to go from a transaction platform to an intelligence platform, now go from a transaction platform to a cutting-edge frontier model-based agentic M&A platform. So, they were all very different in terms of the subject matter content and also sort of the pace of engineering and innovation inside those firms. So, we're able to marry them all together. Now, having said that, it's gone quite well. we we literally have

24:46 the Blue Flame team focused on building out the agentic space. We have the Gradall team building proprietary and private company content, and we continue to focus on from and making the content platform, which by the way really think of it as a system of record. They decided it's a system of record for every doing M&A transactions. but what's happening now is you ask, you know, what's going on next? Well, now we need to have all these pieces operate more closely together as an integrated platform. So, we need to embed the Aigentic technology throughout the platform. We need the content to be formatted and structured in a way that it's Aigentic, that it's vectorized, so it's very easy for AI models to work with that. We need to make sure we can weave in the gas or the exhaust from the transaction platform into Grata. So, now we're beginning to evolve our model to where we're integrating sort of the best of each team into these core functions as we build out one integrated platform.

25:41 And it's it's it's working quite well. I mean, I think the the thing most companies have to deal with is getting clarity of purpose in the context of rapidly changing technology. So, our purpose is very clear on our M&A platform, resilience, scalability, security, compliance, auditability, moving into being an AI native content platform. And our purpose inside the the Grata team is very clear in terms of continuing to build, you know, unique and private private content and BlueFlame on the other. another place that it kind of tests your ability to work together is we're getting ready to make an announcement about how we'll be working with Entropic and how we'll be working with OpenAI as well as with Copilot through this MCP technology server.

26:32 So, if you think about how that all works, you've got this transaction platform that has all this secure permission content. You want to be able to connect to the LLMs and and the labs via this MCP server. Fancy name for collecting your APIs and putting it in one place, so it makes it easy to access the content. That forces you to have to work across all of those streams of engineering and product to be able to bring that together. And so those are muscles we're growing. I I think most companies if if they say it's easy, it's not an issue, they're not they're not pushing the the envelope enough. But for us, I think because we've been able to take sort of the transaction skills along with the Blue Flame skills or the Blue Flame skills along with the Grotto skills and marry them into producing business function and commercial function, it's working.

27:20 And ultimately, our success for our clients is that becomes one seamless AI native platform supporting the buy side of the world and also supporting the sell side of the world. >> So a question in my mind as I listen to you, Rusty, how does a CEO who is busy enough with ensuring that his company is functioning across all the important areas, compliance is just one of many you mentioned, is growing to meet its internal targets, is scouting out acquisitions, how does that CEO roll up his or her sleeves enough to understand enough about AI to move forward and say, "Yeah, this is what we need. We need to have a multi-context protocol server that our customers can query against that still contains all of our constraints." How do you get the knowledge that you need to have about artificial intelligence and generative AI and keep up in order to make the decisions like these crucial acquisitions?

28:19 >> I think it's I think it's two things. First of all, you you have to begin, and this sounds really simple, with what problem are you trying to solve for your clients? What is it that they're trying to actually accomplish? And what you can see is with the build-out of these environments in cloud, which have obviously advanced rapidly, with the build-out of chat environments and other environments, is that [clears throat] our clients have a need to be able to not only operate within their enterprise within those environments, but they have to get to the critical project information that they're working against, whether it's on in private equity or whether it's investment banking. So, we start with that. And then, I think what we did, and I give credit to Capstone and the team, we we we really went out and bought companies that have exceptionally talented people in them. So, if you look at the founders for Blue Flame and the founders for Grata, they are cutting-edge intelligent in terms of how you actually, you know, deploy these technologies. So, it's then a matter of once you can define what is the business

29:21 problem you're trying to solve, what's [clears throat] the best way to solve it, you know, using the technology. And that's essentially the way we walk through that entire discussion of, "Okay, we know we've got cloud environments. We know we've got data rooms that they need to access. We know the most secure way to do that and control content is through MCP as a platform. Well, who knows MCP? Well, Blue Flame had already written an MCP platform connector to go to Datasite as a part of our group structure as a company in Datasite. So, we already had that, so you move that skill over and the people who are best and brightest in that do it. I'll give you another example right now is we know that there are going to be sort of hyper-sophisticated companies on the buy side and on the sell side that are going to build out really robust environments and Cloudera or or in Chat or other environments.

30:12 we also know there are an enormous number of people in the ecosystem that are just going to want to do a transaction, and they're going to want to have access to AI capabilities within that secure box that is the Datasite platform. >> you all to do it for us and do it well. >> We want it or we want to be able to literally just be in the data room, and I want to be able to have a prompt. I want to be able to ask a question about contracts like we talked about, or about, you know, HR agreements, or any number of things. And literally, while I'm just in an an I'm familiar with, which is the data room, I have a you know a a side panel that allows me ask all those things. It goes out and it leverages the Blue Flame architecture and and the agents they built to bring back the answers inside the data room. Now, >> [clears throat] >> how do we do that? Well, we knew there was a need for people to be able to access AI powerful AI capabilities in LLMs securely inside of a data room. So, we took our team to build the MCP interface. And Blue Flame has written all of the agents already, and we just deployed them into the actual Datasite platform. So, it's you know,

31:14 I don't want to oversimplify it, but figure out what your customers need and then have the best and brightest people on your team sit down and do whiteboarding, have discussions, and figure out what's the fastest way to get there. I mean, the other thing is it forces pace. So, we [clears throat] did the what I just described in a matter of gate-to-gate 4 weeks to decide to do the MCP server, to have it operational this week in 4 weeks, which is for a company our size pretty good. >> Does that mean that you were at like final beta testing in week three? It's like incredibly compressed time. >> Yeah. Yeah. >> So, I have a question on behalf of members. Are we going to get a chance to see an IPO out of Datasite, or are you guys just making so much money you don't need the the public markets?

32:00 >> You know, I you know, I've got a really standard answer on that is I spend all of my energy on our clients and on our business and figuring out how to grow and scale the business. and I leave to Cap Vest those complicated topics about you know, DEI IPO. I will I will say this. Excuse me, [clears throat] my voice has been kind of up and down as I shared earlier. The world's changed a lot about IPOs and about holding of private companies. And if you look at what's happened with private companies and the duration that private equity holds companies now, and vehicles like continuation vehicles that extend the duration, we're in a situation where we're now at we were at a big inflection point when they acquired us with scale the data room business. We hit another inflection point around building up the private company content. We're at now another incredible inflection point around a genetic AI. So, we think there is a another long run for the business in terms of value and growth.

32:57 And I you know, I don't see anything near term. there are some clear advantages about being a private >> company that you have articulated previously and I know well that you can make decisions quickly and you can pivot quickly and you can take economic hits in short to intermediate term for strategic plays and for me I have enjoyed being in a private company. >> And this brings up a related question that I wanted to ask about the industry in general. I see you all and this is probably just a layperson's perception, so take that for what it's worth, but I see you all as more an exception in the private equity world. What we see is often companies that have value because there's something to be extracted out of them. >> Mhm.

33:40 >> Do you think or do you see a shift towards more of your model where private equity firms have an interest in buying companies and really trying to invest with them, invest alongside them and have more medium-term, long-term results to increase a bigger payout for them once they they exit? >> I do. I mean and I think some of it is how the just how the structure of the industry has changed. you know, when you had a long period of very inexpensive debt to be able to finance the acquisition and have highly leveraged businesses that the expectation was you'd hold it two to three to four years and flip that business was a was a brilliant model, right? And and and private equity or were and are exceptional when that exist today.

34:24 the challenge now is the business cases and return cases are much tighter at acquisition. There was a you know, there was an old saying that you can make your money at the time you acquired the company not the time you sold the company, right? Which is pretty pretty common in private equity. I think that's changed that you've got to create the value while you own the company, which means you have to invest your intellect, you have to do inorganic plays, you have to leverage the balance sheet, you have to do all those things to create the ultimate value of a business is it's it has I think we're I think we're a case example, but I think it's going to be more prevalent in the industry going forward because it's just going to be the importance of strategy and innovation and execution to creating value has never been higher and the uncertainty has never been higher in terms of how do you actually get there.

35:11 >> Mhm. Rusty, we have just a few minutes left. So, I want to ask you two questions. The first is about risks. So, I'd love to know what worries you most about Datasite, where you see the vulnerabilities as you manage the company both day-to-day and and for the longer term, and then flip over to vision. Eventually, what would you like this company to to be? And that could be in terms of maybe a revenue figure, it could be size of market, it it could be something else that's more qualitative, but having given you those outlines and hopefully a few seconds to to think through those. we'll start on the risks. >> I think I think the the the risk for everyone right now, and it's very obvious, is what happens with the labs and the LLMs and being able to the best of your ability anticipate how you make that an asset within your business and within your platform or within your software as opposed to it becoming a competitor to your platform. And so, we're very actively obviously focused on

36:15 that with the things I've described before in terms of incorporating that into our product plus making our product available as a system of record. We have a good plan for that. So, I I think that is sort of an inherent risk to every software business right now. the bigger risk is that do you do you lose your pace? Do you lose the energy? Do you lose the pace with which you understand, process, and act on what's happening in the industry, what's happening with technology? Because I if there's anything I know for sure, we could have taken a path as a business that says, "You know what? It's great. We're growing, you know, 20% a year every year. It's a fantastic business. It's profitable. Let's just bolt on some AI, right? Let's do some AI functions. Let's keep everything as is.

36:59 No big change, no big renovation, no big acquisition. And we would put ourselves in a position of just defending our existing business and not growing. I I think that to me is the energy and the approach that if you lose that, where I'm going to identify it, I'm going to pursue it, I'm going to figure out how to leverage it, I'm figure out how to use it on behalf of our leverage on behalf of our customers. If you lose that, I don't know, you lose that velocity, you're you'll struggle. where we're headed is we're going to be an AI native platform that effectively becomes the operating system of M&A. full stop. I mean, our desire is to not only be the system of record for all transactions as we scale this. and not only that, but to be, you know, one of the key proprietary content sources and build the best due diligence workspace we can build out for our customers within Datasite and be, you know, effectively an M&A operating system powered by AI. So, we have bold bold plans and a lot of industry out there to help.

38:00 >> Well, Rusty Wiley, this has been great. You've packed a lot of information chock-full in 40 odd minutes and and many insights, too, for those who want to follow Datasite, but also the industry in general. And I would say software as a service companies as well. So, I really appreciate your time and your insights, and I look forward to having another conversation at some point in the future. >> I would like to do that as well. Thank you very much.