Transcript: Datasite MCP for Blueflame AI

Doug Cullen (00:00)

Good morning, good afternoon, and good evening. Thanks to everyone for joining us for the fourth and final webinar in our series. Welcome to the Datasite MCP for Blueflame webinar. I'm joined here by Raj Bakhru and Alice Esmerian. We're going to walk you through several different components of Blueflame, including the Blueflame AI Assistant within Diligence, and we're excited to have you here. My name is Doug Cullen. I'm Chief Strategy Officer here at Datasite, as well as head of corporate development and head of partnerships.

Today, we're going to talk with you a little bit about how Datasite and Blueflame AI work together to bring governed AI workflows directly into deal execution. Our web series has focused on the transformations that are available now with AI technology and how they are really changing the way deals get done. As we focused on in previous webinars, we're going to dive right into the Blueflame experience and showcase the Blueflame AI Assistant in the Diligence application itself. Before we get to those exciting things, I just have a few housekeeping items that I want to cover.

Okay. First of all, we want to hear from you. You'll see a Q&A panel, so please ask questions throughout the webinar, and we will do our best to get to those questions after the fact. If we don't get to them, we'll still follow up with some FAQs to make sure that we address the most important topics. We are also going to put together a survey, so we want to make sure that you respond to that. You'll find additional resources in the console.

These include some of the FAQs from previous sessions, as well as information about some of the things that you're going to see here on the webinar today. Of course, we are recording this, and it will be available on demand. And what webinar would be complete without a good legal disclaimer? All the opinions expressed are our own and not those of Datasite or Blueflame. Welcome. I just wanted to do some quick introductions. Again, we've got Alice Esmerian, product strategist at Blueflame. Why don't you tell us a little bit about how long you've been at Blueflame and what you did previously?

Alice Esmerian (02:25)

Sure. Thanks for having us here today. I'm on the product strategy team at Blueflame. I joined six months ago, so it has definitely been an exciting time with no rest. My background is in investment banking and private equity, where I spent almost eight years. It's very exciting to help bankers and private equity professionals benefit from new AI products in their workflows.

Doug Cullen (02:50)

Awesome. And Raj Bakhru, co-founder of Blueflame, can you give us a little bit of background about Blueflame and maybe some of the things you did before founding the company?

Raj Bakhru (02:59)

Yeah, sure. Thanks. Hi, everyone. Raj Bakhru, co-founder and general manager. My background is actually on the tech side of things. I started my career at Goldman, was later at Highbridge Capital and Kepos Capital, and started a security firm that we sold to a compliance firm. Eventually, I ended up running M&A and corporate strategy as the chief strategy officer of that company. That was a PE-backed company under three different private equity owners. I saw a lot of the pain of the manual workflows that we had in acquiring dozens of firms.

We launched Blueflame because of that. We saw that there was a huge opportunity for AI to step in and make life a lot better for folks in the industry. We knew AI was going to be transformative, and here we are today.

Doug Cullen (03:41)

Awesome. Well, we definitely want to get into showcasing some of the capabilities. We have a lot to unpack on what's going on across dealmaking. AI is becoming central to how deal teams think and operate. Teams increasingly want these AI workflows, but some of these things are not super intuitive out of the box.

So I think we want to showcase that. And then, of course, as we think about it from a dealmaking perspective and an overall strategy perspective, governance, security, and auditability are really critical to everything that we do to ensure that the trusted environment of Datasite is extended into all these different workflows. Raj, from your perspective, what do you think is getting people really excited about some of the things that are impacting deal execution in AI?

Raj Bakhru (04:32)

There are so many things that you can do with the tool in executing either the build of your data rooms, the launch of a process, all of the workflows that happen through the process, and answering questions that are coming in.

And then on the flip side, if you're a buyer dealing with the data room and working within it, asking the tough questions, and running through your analysis and your workflows, whether that is customer retention data or HR analysis, all of that data obviously sits in the data room. It's unstructured data, and the AI has gotten really good at being able to parse through that data, address questions, and find things for you that you might not be able to find on your own, or that would have taken you hours and hours to find. We're going to demo some of that today. Alice is going to show us some of those workflows on both the buy side and the sell side.

Doug Cullen (05:16)

Yeah. We got to know each other about a year ago, met the team at DealMAX, and struck up a great conversation. Ultimately, we bought Blueflame last year. I think we closed in July or something. It's pretty amazing to see some of the things that we've brought to bear already from our perspective. I met the team, saw some of the things you were doing, and I was blown away.

We, of course, had our own organic set of capabilities that we've been bringing into the Datasite platform for six or seven years across the AI landscape. But I was really wowed by some of the buy-side workflows that Blueflame was bringing to bear and had this vision of, "Hey, imagine if we could take some of those capabilities and bring them into a native Datasite experience." This is really what we believe dealmakers wanted: natural-language querying across large data sets. From our standpoint, it just felt super comfortable and very natural. You were co-founder, right?

You weren't necessarily expecting to get your door knocked on by Doug saying, "Hey, man, I really want to buy your company." How did you approach it from your perspective?

Raj Bakhru (06:29)

We knew, obviously, Datasite was the biggest, best, and most credible data room out there. We've used it in prior lives, and we knew that we wanted to be embedded with that content. It's where all of the really interesting stuff in a deal lives. We knew our clients wanted that. They wanted to be able to access that data.

We knew the only way to do that really well was if we were tightly coupled together, able to replicate the permissions and the security that live within Datasite all the way down to the details: what gets watermarked and what is allowed to be downloaded. There is a lot of intricacy in the security and permissions of a data room. There was really no way to bridge that gap unless we were tightly coupled together. We knew that the value would be tremendous, so we figured out a way to make it happen, and I'm glad we did. It's been a fun journey building together.

Doug Cullen (07:15)

Yeah, it has been absolutely awesome. So I guess the fun question that we get to showcase today is: what can AI actually do within this secure data room environment? Before we go into that, I think it's important to set some context about what's going on within this because we've got a few different layers. You've got the Blueflame AI Assistant, which we'll get into, and then you've got MCP. Can you give us a little bit of a 101, Raj, in terms of what's working here?

How are these things interoperating? How are some of these capabilities technologically possible?

Raj Bakhru (08:00)

Yeah. A big piece of what we've enabled with the data rooms is broad-scale, deep, high-fidelity search. When content comes into the data room, we really want to understand what a chart says. We need to understand how the legend corresponds to the bars in that chart. We need to understand logos on pages, charts, graphs, and org charts. All of this is complex, but it is really important in understanding the context of the deal and all of the highly visual materials that exist in a data room.

So a lot of what we brought into Datasite was high-fidelity parsing and search algorithms to work through that massive set of data. That means we can now leverage that search either directly in the data room or directly in the Blueflame platform against that data room. We're going to show you both experiences today. Within the Datasite data room, there is now a sidebar, sometimes called Sidecar, where you have the ability to chat with the data room, and that chat is leveraging Blueflame behind the scenes to ask questions against the data room content. It's leveraging all of that high-fidelity search that we built against the data room.

So this is not like some of the agentic tools you see out there, where the tool tries to search file names and read just a few files to answer a question. This is actually looking through every bit of information in the data room to find nuggets of information that might be buried in files you would not otherwise find. You have the ability to do that directly in the data room with the sidebar chat. You also have the ability to go into the Blueflame platform and do everything from creating a data room to managing the data room to asking questions against the data room.

There are a number of different ways you can leverage that on both the buy side and the sell side, which we'll demo today.

Doug Cullen (09:44)

And because we've been processing content for a long time at Datasite, one of the things I was really impressed by was this next level of processing and extraction capabilities that Blueflame helped bring into our environment. How is Blueflame able to go into things like charts and graphs, pictures, and org charts and really make that information come to life?

Raj Bakhru (10:11)

Yeah. We're leveraging vision models against a lot of that content to pull out all of the details that live within it.

Over the past two years, AI models have gotten much better at being able to read that content. But there are still cases where we have to optimize. Certain models do better against bar charts, and certain ones do better against pie charts, and so on. So it is very intricate data science work that happens behind the scenes to enable all of this. The result for someone interacting with the platform is that when you ask your questions against the platform, it shows you all of the places where it is finding relevant search results, and then it goes ahead and answers the question based on all of those results.

What we've seen happen over the past six to 12 months is that the quality of those answers has become extremely rich, extremely high confidence, and frankly really good at finding the right answers by leveraging a combination of agentic search and high-quality semantic search.

Doug Cullen (11:10)

Awesome. Thanks so much for that. I think now let's just get into it. I love this showcase in a Diligence project. I think Alice is going to share her screen here.

Why don't we just dive right in? If you don't mind, walk us through what you can expect now as a Diligence user when you have the Blueflame AI Assistant available in the Diligence project.

Alice Esmerian (11:38)

Yeah. We're going to cover a few workflows here. There are obviously many more that can be done. Feel free to drop any workflow suggestions or workflow questions you have into the question panel. But just to get started here on my screen, everyone will recognize the Datasite environment. In case you haven't enabled Blueflame AI within your data room yet, you can simply do that by clicking this button at the top right here.

When you do that, you'll be able to open more information and, if needed, get in touch with your Datasite rep so they can help you add Datasite AI to your VDR. If you created a new project, you'll automatically have the option to have that. Now I'm moving on to what it looks like once it's enabled. I want to start by showing you how you can leverage it to make sure that when you start your VDR, all your content is organized and cleaned the right way. Here, I simply ask the Blueflame AI agent, "Can you help me run through my index, the folder names, and the document names?"

I want it to be very clean so that when I let buyers into my data room, everything seems very neat and they have an amazing first impression. Here, the model has the ability to look at the existing names, but also the real content behind every document, to inform how it should actually be labeled. That really helps me get useful feedback, such as, "Here, you're not necessarily using the right date because the date of the document is actually different," or, "You're not using a standard naming convention for all your contracts," or, "The date looks different." So it comes back with many different levels of feedback for me that are very helpful in quickly pointing out the issues.

As a banker, that is typically a process that you would do manually, scrubbing everything, and that's time-consuming. Now you really have this level of feedback from a single prompt, which is pretty amazing. Another workflow that I really like is the risk audit capability that we've built with the help of Blueflame and Datasite working jointly. Here, I'm asking the model to look at potential risks and create a risk report. As a banker, you are typically heads down in your deal, and there are some oversights that may happen that buyers will be very focused on, and you may not necessarily have prepared a sufficient level of defense.

So here, you really get this third pair of eyes, an extra person taking a look at the entire content of your documents and screening every single document that you might have uploaded without actually reading every single line. It will give you a risk snapshot for both strategic and financial buyers if you want it to, and it will look at very different aspects of your deal. It will scrutinize everything it can, including add-backs, change-of-control clauses that have different types of risk around them, and customer concentration across different verticals.

So it is really going to rerun a lot of the analysis and data available so that you can come prepared, get your defense where it is needed, and then open your VDR. Although it might look like a lot of content, you can then get that into a simple table with risk, buyer type, and defense. I'll copy and paste that into an email. I think that's a lot of work that has been done very quickly thanks to Blueflame AI being able to go through all your content and retrieve information for you.

Doug Cullen (15:09)

And Raj, from your perspective, how is this able to do such a high-quality job looking at all of this content? I mean, we have a very large corpus of information potentially here, as well as across Datasite. I always feel that Blueflame has this innate ability to really understand things from a dealmaker perspective, and I don't think that's accidental. It feels like it has been by design.

Raj Bakhru (15:33)

Yeah, that's always been what we've been going after. The vision has always been: how can we build for the prompt-first dealmaker?

Someone who wants to come into the platform naturally and go there first to get their work done. What you saw Alice do here could obviously save you hours of time, and you didn't need to custom-create a really difficult prompt to get to that. I chuckled briefly when Alice said thank you to the agent and then had her prompt there. It was very natural language. It is able to ascertain what the user is going for, what the investment professional or the dealmaker is going for, because we designed it to do exactly that.

What we've seen happen over the past six to 12 months is that the agents themselves, the agent harnesses, have become tenacious, which is what we like to call it, in the way that they search for information. In that last example Alice showed you, there was a lot of information that it had to dig through to generate that table of potential issues. That's exactly what you want it to do. I don't know how long that prompt took. It might have been a few minutes of work to go do all of that, but that's exactly what you want. You want it to spend a lot of time working through all the information.

The agent harnesses have become really good. I mean, we've designed this agent harness to be really good at reading through the VDR, understanding all the content, and finding all those potential issues really well just from the natural-language query.

Doug Cullen (16:52)

And effectively, I'm asking almost a pretty basic question, but underneath that, it's firing off dozens of additional questions in order to orient its way through the data room, find the answer, and pull it out. I love that sort of resilience that it must have in the models themselves.

Raj Bakhru (17:11)

Yeah, from a technical perspective, it's leveraging subagents.

It can kick off dozens of subagents in parallel to read through content, ask multiple questions at a time, and aggregate tables of information. Again, it is tenacious and resilient. It will always work really hard to find the right answer for you.

Alice Esmerian (17:29)

I think what's great on top of that is that this is all done within your Datasite instance, so you don't need to drop any document outside of Datasite. Everything remains safely stored within Datasite, and that additional level of security is very important.

Doug Cullen (17:44)

Yeah. I mean, we really have taken a lot of time thinking about the guardrails. We are the trusted place where deals are made, right? So we wanted the ability to take advantage of these capabilities, but in a super guardrailed environment. Can you talk a little bit more about that, Raj? How difficult is that? What would be some other approaches? If you wanted to take things out of the data room, obviously that would create a bunch of risk and exposure points.

Doing this within the four walls of Datasite is a pretty important thing for our dealmakers around the world.

Raj Bakhru (18:20)

Yeah, and it has a lot of value, right? The download-upload process itself is clunky. It's also error-prone, right? Sometimes you just have old copies of information. You haven't brought in the latest copy. You start asking questions, you realize that you have bad data, and you ask poor questions because you're working off the wrong data.

This is all directly built in. It's native. It's fast. You can just go directly and ask questions against it. The permissions are obviously really important, so that was baked in from the get-go. No one is getting access to anything that they don't otherwise have access to. The agent is only working through what you have the ability to see, and if you have the ability to download, any watermarks are preserved. We even provide what I think of as guardrail citation: the ability to understand where a specific figure or data point is coming from, and to go back to that source document to verify as needed or to call it out in any of your follow-ups.

So we think the guardrails were paramount. That's table stakes. We had to make sure that it got that perfect. And then, obviously, on top of that, we wanted to build a lot of the value-added functionality.

Doug Cullen (19:25)

That makes a ton of sense, and it's just so powerful to have these capabilities in the platform itself. This is kind of what I always felt search should be, right? The technology just was never there to allow for this type of interrogation, natural-language querying, and ultimately getting these incredible answers right within the Datasite data room.

Raj Bakhru (19:49)

Yeah, and it's not easy. I will say that even with a download and upload into any of the LLM tools that are out there, you're not going to get the same level of tenacity with the agent or the same level of high-fidelity search through the charts, graphs, and logos. So replicating a lot of what Alice just did through the core LLM tools that are out there is not necessarily doable. You'll hit token limits, and you'll hit a number of other issues in terms of the fidelity of content that's coming in and the ability to search through it.

Doug Cullen (20:19)

Yeah, because if it's just the LLM, it is limited to the context window that it has. With the Blueflame agent experience, you're not really limited or bound by those traditional constraints. You're really able to look at 5,000 to 500,000 pages' worth of information in a data room.

Raj Bakhru (20:40)

Exactly. If you were to leverage some of the project tools that are out there, there are limits on the number of files you can have in there and the size of those files. It doesn't directly index all of those files. So we can obviously work against much larger or more complex data rooms much better.

Doug Cullen (20:55)

Awesome. So I think we're going to shift gears a little bit and maybe showcase the Blueflame platform itself. Part of the connectivity here is that you've seen the Blueflame agent sitting within Datasite, the AI Assistant, and now we have this other incredible experience in the Blueflame platform itself, which is leveraging the MCP capability. It's awesome to see what other customers get if they've invested in Blueflame and have it as an enterprise platform, which we recommend for everyone, of course. You get an even more enriched experience.

Alice Esmerian (21:32)

Yeah, absolutely.

We've always had this connectivity into Datasite, where our clients were able to query Datasite content from their Blueflame instance. Now, the addition that we're releasing with this MCP connection into Blueflame is the opportunity to push content into Datasite. In the example we're seeing on the screen, I'm starting fresh and just want to start a new project without ever leaving Blueflame. So I'm going to ask Blueflame, "Can you help me set up a new Datasite project?" It knows that it's going to need a bit of context to help me as best as it can.

It immediately asks me: what is the industry of your deal? What type of deal is it? What is the size? Where is it going to be hosted? That is obviously very important for our customers. By providing this high-level context, it automatically returns a sell-side data room index that is tailored to my particular deal because, as you can see here, it came back with some IT-specific sections and things that you'd expect to see in an IT services data room. So that is great, and I can push it to Datasite. But I want to take advantage of the fact that all my Datasite data rooms are actually flowing into Blueflame.

So I push it a little further and say, "Actually, can you look at this other deal where I really liked our index and inform from that what should be the final index for that new Pegasus deal?" The model does that immediately. It looks at everything in that other VDR, comes back with a plan, and then, once we iterate together, finalizes a very detailed index that has all my main sections and folders. Everything is prepared from a single push of a button to be accessible. Then it also provides the link so that I can open my Pegasus sell-side data room within Datasite to see that it actually created all of that, which is pretty insane.

As a banker, it would take a lot of time to move a clunky Excel spreadsheet into Datasite to have your index populated. You obviously need to think about how you want to orchestrate that. Here, you can leverage all your firm context from all your data rooms and build something very tailored, all from a single natural-language prompt.

Raj Bakhru (23:42)

Yeah, it's amazing how fast you can do things now.

Doug Cullen (23:45)

I mean, it's not just that, in and of itself, getting access to a data room via Blueflame or MCP and setting it up is super powerful.

Then you take it to a whole other level by doing a comparison against another deal. You'll be able to dynamically operate in this Blueflame environment, taking advantage of your previous work and best practices, and ultimately easing that setup for the project itself. You can do it in minutes, as opposed to the days it probably would have taken back in the day.

Alice Esmerian (24:19)

Yeah, definitely. Another thing that is quite time-consuming when it comes to setting up a data room is inviting parties. You're receiving names and email addresses in different spreadsheets, emails, and unstructured formats, and you need to manually push that into Datasite.

Now, the way it works with the MCP is that you can drop a spreadsheet, and the model is going to identify the roles, names, and email addresses of the individuals. Here, you can see on the screen that I pushed an email list, it identified the right people, created the roles, and then had the invitations ready to go to their inboxes. Obviously, it is done for me to go into Datasite and make sure that they have all the access permissions and that I can keep control of that. We're not pushing that all the way to the other end quite yet because we feel that it's super important to make sure that the permissions are still set up manually at this point. But at least you can invite them and locate each individual role from a single prompt again.

So that's very helpful. I'm also conscious that, having been in the bankers' shoes, you don't always receive a nice spreadsheet with everything in an organized way. You receive several emails in the same day saying, "Hey, can you add Raj? Can you add Doug?" What I love with Blueflame is that because it's connected to your email system, you can actually pull the data from your emails without having to sit here, and then push it into Datasite without ever leaving Blueflame. So that's another way to leverage the fact that all your systems are working jointly within Blueflame AI.

Doug Cullen (25:53)

And your CRM, right? One of the big value points for Blueflame is connectivity to all the primary systems of record. You could be a banker who has a CRM connected, and you're connected by Office 365. How is that working, Raj, to enable Blueflame itself to have access to all these critical business systems?

Raj Bakhru (26:12)

Because we're connected to all those systems, and we have proprietary integrations in all the major CRMs, in Office 365, and obviously Datasite and Grata, you have the ability to have the agent correlate data across them.

So again, you can pull information from one and push it to another. You can do some pretty cool things there, such as asking, "Who do I have in my CRM as potential buyers for this project who have not been set up in Datasite yet?" And you can reconcile a list across the two as well. Obviously, Office 365 comes with email and calendar access, and you can automate quite a number of things by leveraging the data room with the Office 365 integration. You can create your process letters and auto-send your process letters. You can point people to specific files in the data room with links. There are so many things you can do by pairing these systems together with the agent.

Doug Cullen (27:03)

It's how I think people have always wanted it to work. You just had to go to these different places to do the different things, and now you're able to almost sit in this beautiful environment and allow the orchestration to be at your fingertips.

Raj Bakhru (27:17)

Yeah. There was another webcast we did where Alice created a whole CIM through prompting, right? A 55-page CIM created through prompting, and now you can upload that into your data room directly through the MCP connection.

Alice Esmerian (27:29)

Yeah. And I feel that another way to really benefit from this integration is around the process that comes when you prepare your data room. As a banker, you work with your client to make sure that they're populating the right information and that you're going to have everything covered. Here on the screen, we're looking at a data request list, or DRL, where you're going to have all the requests you submitted to your clients. You never know if the process is really tracking what has been uploaded and what information is there or not there.

It changes for every single process, so it's quite manual. Here, I just uploaded it. The agent is going to read through all 241 items that I requested from my client. It's going to crunch the entire data room to see what's in there or not and come back with very detailed feedback. It's going to produce the materials I requested for me to run through these conclusions, which include the detailed DRL with annotations, sources, and page numbers for each of the different information requests, as well as a summary in PowerPoint that I can share with my client and tell them, "Here is what I need from you."

Those sets of documents are produced by Blueflame. You can see here the DRL tracker, as well as the PowerPoint. Sorry, it's just loading for a little second. The DRL tracker is in XLS, as well as the PowerPoint. On top of that, what I'm asking Blueflame is that it put it into an email that I can send to my clients so that I don't even need to move back, download the files, put them into Outlook or whatever app you use, draft the email, and send it out. It's already sitting in my draft folder, and I can just push it to my client so they can easily navigate where they need to prepare and submit more.

So that's really a great way for me to leverage AI and save time while keeping all the traceability and auditability of everything you're doing within Blueflame.

Doug Cullen (29:26)

Yeah, incredible value for the advisors and the clients, right? Ultimately, having the banker or other trusted advisor run a process for you, part of the difficulty, as you know from running strategy, is trying to navigate who needs to get access to it and what files need to be provided. Of course, there are always going to be gaps, but being able to really focus on the missing pieces as opposed to all of the pieces is crucial for customers and really allows you to have that optimal conversation, kind of trusted advisor to the underlying corporation.

Alice Esmerian (29:58)

Yeah, definitely. And we've covered a lot of sell-side workflows today, but this is obviously something that is going to benefit our buy-side clients. We just released within Blueflame what we're calling Spaces, which is a way to, on top of getting access to your data room within Blueflame, create a space around it where you can put your SharePoint data and really any content that is flowing around a particular deal or around a particular industry that you're focusing on, where you can work in this closed vault. You can invite team members you want to collaborate with and leverage both the content of the data room and all the analysis that your team is working on.

Here you can see my project's homepage. I love the fact that I have an activity thread and I can track who has been doing what on that project. Here, I've been working quite solo, but team members will see everything everyone is doing if they decide to share it. You can add people here, and you can see that I have everything concentrated, with my chats around that particular project and notes that I take. Those can be notes from a call one team member is having with a CEO, while another team member is talking to an expert and another one to the CDD provider.

So you can just share all of that and then query your data room content with this additional layer of context to really optimize your work around the deal.

Doug Cullen (31:26)

Yeah. And just to take a step back, because I think this is so profound and we've gotten a ton of questions around this, what we are covering on the Datasite side of things with the Blueflame AI Assistant was really highly oriented toward the sell side and many of the things Alice was showing there, again, for sell-side advisors. We're jumping to the other side of the coin here because now you're really thinking about most of the interaction that happens around the deal is not necessarily on the sell side.

It's really around the buy-side and all the interested parties. So as a Blueflame customer, yes, I get access to the Datasite data room, which is a super crucial part of it. But now I have my own space to operate. We've got this project, and I can add so many different contextual components. I can invite my team members, I can invite my advisors, I can invite experts from third parties, and so on into this space. I'm tracking it and really working through the diligence from my point of view, which I think is just going to transform how buy-side deals are done.

Alice Esmerian (32:31)

Yeah, absolutely. I think buy-side people love the data room space, but they also love having their things working in their own instance. They're creating a lot of analysis on top of the data room. They might want to leverage previous deal material as well to inform the decisions they're making and the risks they're identifying. Here, it's really the opportunity to work side by side. You open a note on one side, and you open a chat or a document on another, and everyone works with this shared context that is powered by Blueflame.

Raj Bakhru (33:00)

I think what's really nice for the buy side is that it's a place to collaborate, right? The data room has historically been a place to share information. This is a place where I can go to my colleagues and work with my colleagues. As Alice has shown here, you could take your call notes. Everyone on your team can see that same set of call notes, and that all feeds into the same context that's being used in the chats in the space.

So everyone is working off the same set of information. You no longer have these little silos of knowing what's going on or digging around SharePoint files or whatever it may be to find the internal context on a deal.

Doug Cullen (33:34)

Right, because you may be taking this to investment committee, or IC. I think that's one of the great use cases within Blueflame: taking all of this context and all of this information to that next level to present to investment committee.

Raj Bakhru (33:49)

Exactly. And getting to that ready draft of information, Blueflame already has all of the context of how our firm likes to build PowerPoint decks.

This is the branding guidance around what we do for Excel models and PowerPoint decks. So it just makes building that material so much faster and easier when it's already coming into the format and the style that you like.

Doug Cullen (34:13)

So we're going to go to the next portion of this, or we're going immediately into some Q&A. All right, I am going to read from the questions here. We probably don't have time for everything here, but I think the most important question is: Alice, how do I get the Blueflame AI Assistant on my Datasite project?

Alice Esmerian (34:37)

So for any Datasite project, you'll always have this button that I showed at the beginning of the webinar. It is the Datasite AI button on the top right of your screen. Once you click on it, you can get more information around exactly how it works and what it's able to do, and you can also activate it or get in touch with anyone at Datasite, who will be able to help you very quickly and enable it. That's for existing projects. When it comes to new projects, it's something that you should immediately discuss with the person at Datasite helping you set up a new VDR.

Raj Bakhru (35:10)

And I think what's worth noting is that you don't need to be a Blueflame subscriber to leverage the Blueflame AI Assistant within Datasite. That can be something you do on a per-VDR basis if you so desire. There are lots of reasons to become a Blueflame subscriber, as we showed, but you don't need to be one to leverage that.

Doug Cullen (35:25)

Yeah, awesome. And then I guess, maybe this is the paranoid side of me, Raj, but how do we ensure that redacted and/or permissioned content data isn't accessed improperly? That's part of the trust of Datasite, right?

Raj Bakhru (35:39)

You're using Datasite because Datasite puts a premium on making sure that that's always right. That's part of why we paired together. We wanted to build tightly together to make sure that we're never showing information to folks who are not permissioned for that information. We're never allowing people to download things that can't be downloaded. We're always redacting information the same way. Translation still applies the same way, and watermarking still applies the same way it always does. So we took all of it into account to make sure that we were putting out something that was safe and adhered to all of the expectations that everyone has of Datasite.

Doug Cullen (36:19)

This wasn't necessarily entirely new to Blueflame, right? We basically have to do the same thing from a Blueflame standpoint by respecting SharePoint permissions and content availability and visibility. This is almost core DNA for Blueflame.

Raj Bakhru (36:34)

A lot of our team comes from cybersecurity, privacy, and compliance backgrounds. That is a big piece of why we knew Blueflame, a big piece of what we knew we needed to deliver as part of Blueflame in this space, right? The sensitivity of the content is extreme, just as high as it gets.

We wanted to make sure that we were protecting that.

Doug Cullen (36:55)

And then the question here, which I think is super important, is around audit trail. How do I know what has been asked? How do I know what has been presented? We want to make sure that we maintain this crucial set of information around the deal so that there are no dark spots in the room, if you will.

Raj Bakhru (37:15)

Yep. Again, no different. We wanted to make sure that we were doing things consistently with how the data room has handled things historically. All of the queries are archived. We have the ability to surface that, and all of the file accesses still go through the same auditing, so the audit trails still apply.

Doug Cullen (37:32)

Yeah. Needless to say, kind of table stakes, right? We couldn't do this any other way. We wanted to make sure that we extended all of that monumentally important governance, compliance, and auditability, just like everything that happens on Datasite. That is paramount for deal success.

Raj Bakhru (37:51)

Exactly.

Doug Cullen (37:53)

Okay. Alice, talk to me a little bit about some of the advantages for sell-side workstreams that may or may not have a deal admin.

Alice Esmerian (38:01)

Well, it's true that today we've covered a lot of workflows that are focused on the person really setting up the data room, so the team that is going to be in place to do that. But there are a lot of sell-side individuals who are going to be added to a data room and do more focused work for VDD reports, or maybe other folks at the bank who are less involved in the day-to-day process but still want to enter the data room and be able to understand what's happening.

So I feel that this ability to question the content with Q&A, understand where documents are, and identify whether there is any information that you might have missed is important. Let's say you're a commercial diligence provider. You're going to look at the commercial contracts, but there may also be other bits of information in an IP folder that you actually might want to be aware of. So that's a very good way of orienting yourself and getting very quickly into a deep level of information for someone who is less involved in the building of the data room.

Doug Cullen (39:00)

Great context. We covered this, but I think it's super important, so I'll read this question aloud, and maybe Raj, you and I can probably tag-team this a bit: what is Datasite MCP only versus when do you need Blueflame AI Assistant, and is the Assistant included in the Datasite license?

Raj Bakhru (39:21)

Yeah. So the Assistant is that first experience that Alice showed today within the data room. There is a chat on the right side. That's the Datasite AI Assistant, the Blueflame AI Assistant within Datasite. That has its own separate commercial terms on the VDR. There is an extra piece to the SOW, or you can upgrade as Alice showed to get access to that. Blueflame clients have access to that by default. It's enabled for them to ask questions there. That said, they also have the ability to ask questions directly in Blueflame, and it's the exact same tooling behind the scenes. It's all going to the same place and running the same queries. Oftentimes, you want to be within Blueflame itself because we have wider integration access. You have the ability to go out to your Office 365 and CRM.

In fact, FactSet or CapIQ, or what have you. So you can do a lot more across the ecosystem directly in Blueflame, but you have the ability to leverage it in either, if you're a subscriber. You don't have to be a subscriber to get access to the Datasite sidebar chat that we are. That is the Blueflame AI Assistant within Datasite.

Doug Cullen (40:27)

Awesome. Yeah. So if you have, and I think Alice covered this as well, but just to reiterate, on net-new projects that you may be engaging Datasite with, it will be an option to add this as a set of capabilities.

And then if you actually have active projects, which we have tens of thousands of before this capability really was available, we can add it to those projects as well. So any active deal that you have, you can do so either directly within the app itself or, of course, you can always contact either a service professional or a person in the sales organization, and we can turn it on for you. Okay, we have one more question, and this I think is great as well. Maybe Raj can talk about it: what LLMs are being used to create this magic?

Raj Bakhru (41:18)

Yeah, great question. That changes potentially all the time. As everyone knows, models are constantly leapfrogging each other. We leverage all of the best-of-breed models and open-source models. We'll leverage whatever we need to leverage that can be secured the right way. Our data science team is constantly benchmarking models to understand who is doing the best at what actually matters. Some will do better at certain types of questions or certain types of content, and we will get specific about what we point to for particular circumstances. As we go out to certain integrations, like CRM or Office 365 in particular, we might be using different models for that.

That may be different from what we leverage for asking a question against data room content or for running the agent harness itself. Sorry, I can't tell you the exact single LLM because there is no exact single LLM. It is multi-model by nature, and that is intentional. The models that we're using for different things change all the time.

Doug Cullen (42:20)

Part of the benefit to the user is that you don't really ever have to think about it, right? It shouldn't be your job to decide. We have plenty of people who benchmark the models, test the questions, and figure out what's best for which types of questions. I'm asking one question. And really, the Blueflame agent is routing that, if you will, to a variety of different places to get the absolute best response possible.

Raj Bakhru (42:46)

Exactly, and that is more than a full-time job for a lot of people to figure out.

Doug Cullen (42:52)

Yeah, we're testing the models, we're doing performance benchmarking all the time. It's a crucial thing, and we certainly take it super seriously here. Okay, well, I think with that, we'll have to wrap up. Thank you both for such an amazing discussion.

This shift is amazing. Things are happening so quickly. I love your notion of a prompt-first dealmaker. I think this is just changing the way deals are going to get done. We showed a lot of sell-side use cases. We showed the Blueflame AI Assistant within the Diligence project. Then we jumped out to the enterprise Blueflame experience. Again, you really got that same type of admin flow, and we got a little peek into the future, I think, on what we believe buy-side diligence is going to look like.

We've got this MCP availability, the enabled content, and all of this is coming together because of our partnership, right? You can't do this type of groundbreaking innovation without being super connected across our strategic teams and our technical teams. I really believe the best is yet to come.

Raj Bakhru (44:04)

Yeah, it's getting better every day. It's been exciting to watch, and it's been fun to build.

Doug Cullen (44:09)

Thank you to all the people around the world who were able to join us today.

Thank you, Raj. Thank you, Alice. As a reminder, this is recorded, so please look for that on-demand replay and forward this to your friends and colleagues. We'll probably be back with future series, but this is a wrap for our MCP, or Datasite MCP, series. Once again, I want to thank everyone for tuning in. Thank you to my esteemed guests, and really enjoy and take advantage of this next level of dealmaking. We think the best is yet to come. Thanks, everyone.

Alice Esmerian (44:48)

Thank you.