By Phil Shellhaas, Executive Vice President of Legal Solutions

Perspective from a litigation support professional who delivers services in RelativityOne—and is watching GenAI arrive like every other “revolution” before it.

I’ve been doing litigation support for 25+ years, which means I’ve had the unique privilege of watching our industry evolve from bankers’ boxes and redwelds, to scanning rooms that never slept, to eDiscovery platforms that could finally breathe at scale, to text analytics, and now to the era where everyone asks: “So… can GenAI just do it?”

Quick disclosure on perspective: In my current role at Trustpoint.One, my team and I deliver services using RelativityOne, so my understanding of that platform (and where it sings, and where it needs adult supervision) is hands-on. I do not have direct, day-to-day experience using Harvey or similar attorney drafting copilots—because I’m not in the practice support business. So consider this an opinion piece grounded in what I know first-hand (RelativityOne) and what I can verify publicly about Harvey’s positioning and integrations.

If you work with Harvey (or comparable attorney copilots) every day—especially in real client workflows—I’d genuinely love your perspective. Send me your practical wins, your “it sounded great until we tried to operationalize it” lessons, and anything I’ve missed. If there’s a nuance here that deserves an update, I’m happy to incorporate it in a future revision.

The most common version of that question I hear from law firms and corporate legal departments sounds like this: “Is Harvey basically the same thing as Relativity aiR?” Or its cousin: “If I buy one, do I still need the other?” Let’s unpack that—with facts first, and opinions earned the old-fashioned way: by doing the work.

The short answer (today): they’re not the same tool, and they’re not “plugged into each other”

As of April 2026, I haven’t seen anything public that suggests there’s an official plug-in, connector, or “one-click” integration between Harvey and RelativityOne. I’ve looked for the usual tells—press releases, product documentation, partner pages, and industry announcements—and the signal is consistent: they’re not formally connected out of the box.

Before we compare features: these tools live in different parts of the legal universe

If you remember nothing else, remember this: Harvey is primarily built for attorney knowledge work (research, drafting, synthesis, “make this sound like I didn’t write it at 1:47 a.m.”). Relativity aiR is primarily built for eDiscovery work inside RelativityOne (review, privilege, case strategy against the record, workflows, auditability). And—this is the part people skip—RelativityOne is a platform. Getting great results usually requires experienced humans who know how to design workflows, tune processes, and keep things defensible.

Same broader era (GenAI), different job descriptions. In car terms, Harvey is the upgraded navigation + co‑driver that helps you plan the route and draft the road-trip playlist. Relativity aiR is the engine diagnostics + pit crew that keeps a document review running, defensible, and fast when the data volume tries to eat your weekend.

• No “we’re thrilled to announce…” from either side: Harvey’s public comms don’t point to RelativityOne, and Relativity’s AI announcements focus on its own aiR capabilities and its Microsoft partnership—with no Harvey callout. See Relativity’s Legalweek 2024 aiR announcement and Microsoft’s Relativity/Azure customer story. 2,1
• Ecosystem clues line up: Harvey’s public positioning and integrations cluster around the lawyer productivity stack (for example Microsoft 365), while Relativity’s aiR is positioned as a suite of AI capabilities native to RelativityOne for legal data intelligence and review workflows. 4,5
• Microsoft & OpenAI: Relativity chose Microsoft’s Azure OpenAI Service to power its generative AI features. In a Microsoft customer story, Relativity’s team describes partnering with Microsoft to develop its new AI capabilities and keep customer data protected within RelativityOne’s boundaries. 1
• Relativity’s broader ecosystem: Relativity has a longstanding partner ecosystem of eDiscovery service providers and service partners like Trustpoint.One, and many of them are extending RelativityOne’s AI with their own packaged workflows which we deploy on a daily basis for our clients. That’s not “Harvey integrated into Relativity”—it’s the Relativity universe building on Relativity.
• Why you don’t hear “Harvey” in eDiscovery chatter: When you skim eDiscovery-focused outlets and conference buzz, the AI conversation is usually about review acceleration, privilege workflows, or platform-native features inside review tools. Harvey shows up more often as a lawyer’s day-to-day drafting/research copilot. Different arena, different scoreboard.
• Why do attorneys seem to confuse the two: I believe that as attorneys are simply trying to get a handle on all the technology that is available to them, they are naturally merging two known entities who have had extensive publicity in the legal tech news arena.  On a daily basis while delivering services around the Relativity One ecosystem, we encounter some attorneys who dont want to know how the sausage is made and others who have their own spice blend and prefer making it themselves.  That is part of the current delivery model options available to them.  For the subset that does not want to know, they could naturally merge the two distinct platforms and think they do the same things and solve the same problems.  Obviously, that is not the case.

Billboard version: Harvey and Relativity don’t “compete” so much as they do different kinds of legal work. Harvey tends to shine when you’re improving drafts, doing research, and moving attorney work product forward. Relativity shines when you’re managing, searching, reviewing, and producing large volumes of documents in a defensible way.

Integration reality check: where each one “plugs in” today

When someone asks whether Harvey and Relativity aiR are interchangeable, what they’re usually really asking is: “Where does the data live, and how many clicks does it take to get value?” Here’s the plain-English map—and a reminder from the trenches: tools don’t deliver outcomes, workflows do. The best results I see in RelativityOne come from pairing the platform with people who know how to run it.

• Harvey ↔ RelativityOne: No official, out-of-the-box connector announced (as of April 2026). If you’re using both, you’re typically using them side by side, not as one blended workflow.
• Harvey’s neighborhood: Harvey has leaned into the “lawyer productivity stack”—including integrations with Microsoft 365 (Word/Teams/SharePoint/OneDrive) and business-of-law systems like Aderant (announced December 2025). That tells you exactly who Harvey expects to be sitting in the driver’s seat: practicing lawyers and firm ops teams. 5,6
• Relativity aiR’s neighborhood: Relativity’s generative AI features are designed to be native inside RelativityOne, powered by Azure OpenAI. The point isn’t to send your review data on a field trip; it’s to keep the AI where the evidence already lives, with Relativity-style permissions, logging, and workflows, typically led by experienced professionals who guide the process. 1,4
• Could someone build a bridge? RelativityOne does support certain kinds of custom/external AI connector patterns (via APIs) in specific areas. In theory, a third-party model could be wired in. In practice, that’s custom development—and it’s very different from “these products are integrated.”

What each tool is actually good at (a.k.a. the part procurement wishes we’d write first)

Harvey shines when the input is legal knowledge work

• Drafting and redlining support: first drafts, rewrites, clause alternatives, tone changes, and “make this persuasive without sounding like a robot.”
• Research and synthesis: summarizing authorities or internal knowledge, building outlines, and turning a pile of notes into something a partner will sign.
• Reusable work product: memos, client updates, deposition prep packets—anything where the output is a document a human lawyer owns.
• Everyday attorney workflows: especially when it can live where lawyers already live (Word/Teams/SharePoint), instead of forcing a context switch.

Relativity aiR shines when the input is litigation data at scale

• Document review acceleration: using AI inside the review platform where tagging, QC, sampling, and validation already exist.
• Privilege workflows: helping teams identify and manage privilege consistently—where mistakes are expensive and “oops” is not a legal strategy.
• Case strategy against the record: summarizing themes and issues across what’s been collected/processed/reviewed, with the ability to tie back to actual documents.
• Defensible process: permissions, logging, repeatability, and the reality that eDiscovery is as much about proving what you did as it is about doing it.

Important nuance from someone who lives in RelativityOne: aiR can accelerate parts of review and privilege, but it doesn’t eliminate the need for case strategy, review protocol design, QC, sampling, and defensibility checks. In other words, it’s a multiplier—not a replacement for experienced litigation support and review leadership.

Does one replace the other?

In my opinion: no—and trying to force that conclusion is how you end up with the wrong tool, the wrong workflow, and the world’s most expensive demo. I say that with a clear bias: I have hands-on experience delivering work in RelativityOne, and not hands-on experience operating Harvey day to day. If you do work with Harvey daily, I welcome corrections, nuance, and real-world examples—consider this an open invite. But even from my vantage point, the roles are clear. Harvey and Relativity aiR can both use large language models under the hood, yet they’re optimized for different moments in the lifecycle. One is built to help lawyers create and refine work product; the other is built to help legal teams find, review, categorize, and defend decisions across massive data sets—and it typically performs best when it’s paired with professionals who know the platform.

• Use Harvey when your goal is better/faster attorney thinking and writing: drafting, research, summarization, client-facing narratives, internal memos.
• Use Relativity aiR when your goal is better/faster eDiscovery execution: review throughput, privilege workflows, issue organization, case insights within the evidence corpus.
• Use both when the matter is big enough that you have (1) a serious review in Relativity and (2) serious attorney work product to produce—briefs, witness outlines, strategy memos, status reports. In that world, they’re complementary: aiR helps you understand the universe of documents; Harvey helps you turn understanding into writing.
• One more truth: for complex matters, what you’re really buying is RelativityOne + aiR + experienced delivery (whether internal or a service provider). The platform is the foundation; the people and process are the architecture.

The practical gotchas (because reality always joins the meeting)

• Defensibility isn’t optional: In eDiscovery, it’s not enough to be right—you need to be able to show your work. Platform-native workflows (permissions, logging, repeatability) matter.
• Hallucinations are equal-opportunity: If you ask any GenAI tool to “just answer,” it may do exactly that—confidently. The fix is not panic; it’s workflow: require citations, verify against the record, and treat outputs as drafts, not gospel.
• Data gravity is a thing: Moving large evidence sets out of an eDiscovery platform just to talk to them is rarely fun, cheap, or fast. (Also: security teams tend to have feelings about this.)
• Scope creep loves AI: The fastest way to disappoint everyone is to buy an AI tool for one job and then demand it replace three adjacent jobs. Pick the workflow first; pick the tool second.
• Enablement beats purchase orders: Budget time for playbooks, prompt/usage guidelines, reviewer training, and stakeholder alignment. In my experience, that’s where most “the tool didn’t work” stories actually start.

Bottom line

Harvey and Relativity aiR answer the “Are they different, and does one replace the other?” question like this:

1. They’re different tools: Harvey is aimed at lawyer knowledge work; Relativity aiR is aimed at eDiscovery workflows inside RelativityOne.
2. They don’t replace each other: not in any clean, responsible way—especially not without custom integration and careful governance.
3. They can complement each other: aiR helps you wrangle the evidence; Harvey helps you turn that into written advocacy and client-ready guidance.

After 25+ years in this business, my recommendation is boring—but effective: buy tools for the job you actually have, then invest in the people and process to use them well. If the job is drafting and research, Harvey (and tools like it) can earn its keep—though I’m judging that from the outside, not from daily hands-on use. If the job is review and defensibility at scale, Relativity aiR is built for that world—and from first-hand experience, RelativityOne alone isn’t a magic wand; it gets exponentially better when experienced professionals design the workflow, run QC, and keep you out of trouble. And if you’re lucky, you’ll get to use both—because it means your matter is big enough to be interesting, and someone else is paying the hosting bill.

Post-publication note: this space changes fast. If you’re deep in Harvey deployments (or have built strong Harvey + M365 workflows in the wild) and you see something that should be refined here, reach out—I’m happy to update this as the market (and the integrations) evolve.

References

1. Microsoft Customer Stories. How Relativity built AI for legal data intelligence with a foundation of trust on Azure. Published January 15, 2026.
2. Press Release: Relativity Announces Expansions to Relativity aiR, its Suite of Generative AI Solutions, at Legalweek 2024. Published January 29, 2024.
3. Relativity Documentation (RelativityOne Help). aiR for Privilege. Last modified March 30, 2026.
4. Artificial Intelligence for e-Discovery & Legal Intelligence (Relativity aiR product suite). Accessed April 2026.
5. Harvey Accelerates Enterprise AI with Agent‑Powered Platform and Microsoft 365 Copilot. Published March 4, 2026.
6. Aderant and Harvey Announce Market Defining Partnership Connecting Industry Leading Business-of-Law Solutions with AI-Powered Legal Work. Published December 15, 2025.
7. Aderant and Harvey Announce Strategic Partnership. Published December 15, 2025.