Robert Ambrogi Blog
Last week, Relativity announced that Chris Brown, its chief product officer since 2018, had been named the company’s president, effective July 13. In the new role, Brown continues to lead Relativity’s product organization while adding marketing and technology partnerships to his scope — a change that coincides with the departure of Chief Marketing Officer Cristina Rossman after more than six years with the company.
The appointment comes amid a series of notable moves for the legal data intelligence company, including its June acquisition of Gavel, the document automation company founded by Dorna Moini, and its rollout of governed MCP integrations that allow AI assistants such as Claude to orchestrate matters and workflows within RelativityOne.
On Tuesday, a day after Brown officially stepped into the role, I sat down with him to talk about all of this — the thinking behind combining product and marketing under one leader, the rationale for the Gavel acquisition, why Relativity is opening itself up to general-purpose AI assistants, the adoption trajectory of its aiR products, and the lessons he carried over from a decade spent building consumer travel products at Orbitz.
Below is a transcript of that conversation, which I have edited for length, style and consistency. Ellipses indicate omitted text, and brackets indicate words added or substituted for clarity.
Ambrogi: I want to talk about the product side, but first, in terms of the announcement that your position will also be absorbing the marketing and the technology partnerships side, what’s the rationale for that? With Cristina leaving, do you just leave that CMO position empty for now, or do you see filling it again at some point?
Brown: I think we’ll definitely have another senior executive in the marketing area, for certain. Right now, it’s really about taking all the great marketing work that we’re doing combined with the product work. Ultimately, from my vantage point, we can shrink the distance between awareness or lead generation through to not just converting to licensing the product, but actually using it. So we’re just really trying to shrink the distance between all those motions. …
Ambrogi: I wanted to ask you about the acquisition of Gavel. Could you explain what you see as the rationale for that acquisition and how it fits into Relativity’s strategy?
Brown: Number one, one of the things that we’ve known we’ve wanted to do … was we want to continue to extend what we call our system of action to where users and lawyers want to work. As Relativity has matured over the last number of years, [as] RelativityOne has matured, we understand that it intakes a lot of data and helps you make sense of it. What may not jump to mind is, within Relativity and RelativityOne and within [our] AI, we’re also helping lawyers produce a lot of work products that go out of Relativity, downstream into other systems.
More and more of those work products being created are actually Word documents. So from one vantage point, what I liked about Gavel was that they had built a lot of expertise around basically building an agentic solution inside of Word — whether it was doing document automation, but also Q&A and other types of complicated things, like redlining and collaboration amongst different users live in a document. Ultimately, I’ve always felt that Relativity needs to not just export to Word — it needs to be able to be opened and edited in Word, with those changes synced back into Relativity. The value and virtue in that is that all that information that you’re editing or managing around the case stays consistent with what the actual case is. …
The second thing is the way that Gavel went to market — being very product-led and growth oriented. … They’ve really built a foundation down market, addressing lawyers with their capabilities. We liked the muscle they had built, both in their go-to-market approach and their technology chops. So, for me, they’re just a really good fit if we apply them more in the legal data intelligence zone.
What we’re working on with them now is how we take all the stuff that they’ve been building and integrate it into Relativity and legal data, while also looking at their current business, which is a little bit more on the transactional side, and just trying to understand that business more, learn the value of that, and see what kind of opportunities that might create in the future for our joint customers as well. …
Ambrogi: Is that an indication that you plan to continue to expand in that direction? With Phil’s talk about system of action, is that somewhere you continue to want to develop and build?
Brown: Yeah, it is. Maybe to reverse the way we’re talking about it: Customers are asking for it; customers are doing it. It’s not as if we’re [simply] saying we want to extend our system of action. They are literally, today, taking some of our documents generated [in the platform], exporting them out, and then manipulating them, changing them, reviewing them. We want to help enable that workflow, as opposed to it be[ing] a point where we stop and they have to continue. …
Ambrogi: Somewhere else that Relativity has been expanding of late is into adding governed MCP integrations with Claude and elsewhere. Could talk about the rationale for that. What’s the advantage for your customers in terms of enabling those kinds of integrations?
Brown: With our AI platform for legal data intelligence, we are trying to meet multiple personas across the multiple [surfaces] where they may work, or may desire to work, in the future. Traditionally, that’s been, support[ing] contract reviewers and other folks working directly in RelativityOne. … We want to meet in the surfaces they work — which is, make RelativityOne easy enough for them to use, [and] provide them a surface like Word, where they can also work with Relativity in a way that they’re familiar with. Equally, there [are] going to be more folks who want to use something like Relativity, or at least orchestrate it, through a surface that’s emerging, like Claude.
So … we want to use … our MCP integration to enable certain amounts of skills or capabilities to be serviceable through another interface that folks might begin to leverage more in the future — basically, one of these frontier AI … chat solutions. Claude is a good example, where we’ve enabled a number of skills. People who are using Claude can now orchestrate a bunch of the setup of matters [in] RelativityOne. But then, still, for the more consequential decision-making on the matters, they can run [aiR and RelativityOne] on them. You’re not necessarily doing that in Claude. …
And it’s not just Claude — there’ll be others of those coming, because there’s a market [where] some people use Claude, some people use Copilot, some people use Google, some people use something else. … The main thing that’s important to us is that [with] the data and the AI that makes judgment on it, we can help deliver the best possible results for customers. …
Ambrogi: When you talk about this as a governed MCP integration, what does that “governed” part of it mean? What can a user do within a matter via the AI assistant, and what can’t they do?
Brown: Right now, you’re able to basically set up a matter, set up a workspace, set up users and permissions, access things like billing data and usage data and stuff that you [need] to run your matters, and automate a number of them. So that’s a way for them to orchestrate. But what we’re not allowing them to do is just export tons of data directly out of RelativityOne, or to take consequential decisions and run them past loosely held AI. It’s still managed and auditable in our platform. So it’s giv[ing] them [the] power of orchestration while still having all the defensibility of running it in RelativityOne. …
Ambrogi: I know you have talked over the years about extending Relativity beyond the classic litigation and investigations use cases. With Gavel, with the MCP, are these all steps toward getting more into contracts, transactions, that whole side of the game?
Brown: The way we describe [it] is legal data intelligence, and the number of use cases in that market … continue[s] to expand. So we have definitely been focused on expanding across multiple LDI use cases and deeper in those use cases. … We just launched our Relativity FOIA product this year — that was another example of adding another deliberate use case, for information requests in the public sector. …
The same thing goes for contracts. … I like to think of [contracts] as a data type, because contracts exist in all kinds of forms and all kinds of places, and we want to make sure that they’re understandable wherever they show up in Relativity, in any use case. So I think of it in that sense — particularly when it’s post-signature [versus] pre-signature, when it’s different use cases around management or creation of the contracts, or redlining and all those things. Those [are] areas that we’ve traditionally not spent a lot of time in, but they are close to what we do, and I think naturally, as we expand, we might touch some of those things. …
Ambrogi: At Relativity Fest last year, one of the themes of your presentation was about the degree of adoption of aiR for Review. Here we are, almost a year later, another RelFest coming up not too far down the road. Where is aiR adoption at this point? Can you share any information on the progress of that, or how many review workflows are running through aiR at this point?
Brown: I’m trying to think of how much to share here versus other places. I’ll give you some adjectives without numbers, and then maybe I’ll throw a number at you … . It is absolutely growing gangbusters. If I just looked at this month — I’ll abstract this to any month over the last 12 months — almost every month, it’s growing multiple, like double-digit percentage[s] month over month, growing absolutely exponentially year over year. Depending on the number, we’re talking about, like, 10 to 20x year over year [on] a bunch of these different [measures]. …
The way we look at it is both depth and breadth. Depth, for aiR for Review specifically, would be the amount of documents running through it. The breadth would be the amount of workspaces or matters [it’s] being run on within a firm, and the amount of people climbing those curves. It’s a really staggering amount of adoption. … It’s actually tied to very explicit ROI we can show customers. [At RelFest in London] we spoke through the quantity of high-value results that were being delivered by AI and just the amount of ROI people are seeing, which we publish much of … on the website – really, in aggregate, hundreds of millions of dollars of savings by using AI.
Still, there’s so much more room for further adoption. So while we’re seeing massive success, we still see a lot of opportunity for more people to get in and use the workflows. We’re seeing really strong interest in the public sector. We just released, two weeks ago, our aiR Assist product, which is now more [about] having a conversation with the data, asking questions of the evidence. That thing is also skyrocketing week over week, but it’s only been a couple of weeks since it’s gone [generally available].
So, in general, the products are getting adopted really fast. But if you’re asking me, in my new title as president, am I satisfied? No, I still [would] like to see us do a lot more.
Ambrogi: You spent a decade at Orbitz working on building consumer-facing travel products. I’m curious what you brought from that consumer background to what you are doing now. Were there lessons you learned there that have proved invaluable to you at Relativity?
Brown: Oh, yeah. Number one, when you operate a large consumer brand … you certainly understand how important user experience is. Even very first off, coming into Relativity in my earliest days, that was one of the first major overhauls, to upgrade the user experience. …
Another thing you learn from a large brand like that is a little bit of the funnel — which is going from awareness, to interest, to on your site, to interested in your product, to maybe buying it, to then buying and having a good experience, and following up, and all those sorts of things. And I think, again, in a B2B business like Relativity finds itself in, there’s a lot we can do across our general funnel to make sure that all those pieces are working well together as well. …
The last one would just be feedback loops. With software development right now, or with anything with a high degree of feedback from customers, if you can connect the feedback directly to the R&D engine, and scale that, it’s really important. Particularly [at] Relativity, where there [are] so many different users of the platform, in different segments, with different needs, it’s really essential [that] we can connect that feedback directly into the R&D process. …
Ambrogi: I know our time is just about up, but real quick, here’s my Oprah question for you: In your eight years as CPO at Relativity, what’s the product decision that you are proudest of?
Brown: The shortest answer I’m going to give you … is just AI. … It’s a product, it’s a movement, it’s a commitment for us. It is a lot of different parts of the generative AI stack, but it’s really a commitment to all of legal data intelligence. We believe we can do it better with [aiR] applied in all these areas. And I think the product, when you speak with customers who have used it, continues to blow them away. …
It’s also a product that actually sparks creativity from our customers and from our channel partners, where it energizes them and creates ideas that they have — that we didn’t have — that they can take [to] the business. So I think, personally — and probably beyond just my time at Relativity — [aiR] as a product is probably the product I’m most proud of in my whole career. I think it’s jreally hit the mark, and we’re just getting started.