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AI E-Discovery Software: Relativity, Everlaw, DISCO

By Mark Fulton11 min read
AI E-Discovery Software: Relativity, Everlaw, DISCO

The three AI e-discovery platforms litigation teams actually shortlist are RelativityOne with aiR, Everlaw, and DISCO, and the real difference between them is not model quality. It is the operating model. Relativity gives you the broadest AI product family and the deepest partner ecosystem, at the cost of needing someone whose job is running Relativity. Everlaw ships the most self-service AI stack, with review, search, and drafting assistance in one interface. DISCO sits in between, with Cecilia built around asking questions of the record rather than configuring workflows. None of the three publishes a price, so the pricing model you negotiate matters more than any headline rate you read.

We do not sell, resell, or take affiliate revenue from any of these platforms. What follows compares the AI layers specifically, because that is where the three products have diverged most in the last two years, and it is the part most comparison pages skim.

What does AI actually change in document review?

Less than the marketing suggests, and more than the sceptics allow.

Technology assisted review has been in litigation for over a decade. Predictive coding, clustering, concept search, and email threading were all mature before generative AI arrived. What the current wave changes is not whether a machine can prioritise documents. It is that the machine can now explain itself in language a reviewer can argue with, and can produce work product rather than just a ranking.

That has three practical consequences.

The output changes shape. Older TAR gave you a relevance score. The current tools give you a proposed coding call, a reason, and a citation to the passage that drove it. A second-year associate can audit that in seconds. A relevance score of 0.83 cannot be audited at all.

The burden argument changes. Federal discovery is governed by proportionality, and Rule 26(b)(1) of the Federal Rules of Civil Procedure requires discovery to be proportional to the needs of the case, weighing the amount in controversy, the parties' resources, the importance of the discovery, and whether the burden or expense outweighs the likely benefit. When review cost per document falls, the arithmetic behind a burden objection moves. That is a strategic fact, not just a budget fact, and it cuts both ways.

The certification does not change. Under Rule 26(g), the attorney signing a discovery response certifies, after a reasonable inquiry, that it is complete and correct as of the time it is made and is neither unreasonable nor unduly burdensome. No vendor feature signs that certificate. Whatever the platform does, a human still has to be able to describe the process and defend it. The Sedona Conference's Sedona Principles remain the standard reference for what a reasonable, documented ESI process looks like, and they are worth reading before any AI review protocol goes to a meet and confer.

This is general information about software, not legal advice. Defensibility is a matter for the lawyers on the case, in their jurisdiction, on their record.

How do aiR, Everlaw AI, and Cecilia differ?

Here is what each vendor actually ships, by name, as of September 2026.

Platform Named AI components Centre of gravity
RelativityOne (aiR) aiR for Review, aiR for Privilege, aiR for Case Strategy, aiR for Data Breach Response, aiR Assist A product family. Separate modules for separate legal workflows, including privilege and breach response as distinct products.
Everlaw Deep Dive, Coding Suggestions, Review Assistant, Writing Assistant, Predictive Coding, Clustering One assistant layer spread across the platform, from search through review to drafting the narrative.
DISCO Cecilia Q&A, Cecilia Timelines, Auto Review Question answering over the case record, with automated review as the newer addition.

The shape of those lists is the comparison. Relativity has productised the AI by legal workflow, which is why privilege review and data breach response have their own names. That suits organisations with distinct teams and distinct budgets for each. Everlaw has done the opposite and built one continuous assistant, which is why its list runs past review into a writing assistant. DISCO's list is the shortest, and it is organised around a question rather than a task, which is a genuinely different way to enter a matter.

The scorecard

Four dimensions, scored structurally. These are judgements about what each product is and how it is operated, not benchmark results. Nobody, including us, has run a controlled head to head on your documents, and any page that gives you accuracy percentages for all three is not showing you its method.

Relativity aiR Everlaw AI DISCO Cecilia
AI review capability Broadest. Distinct modules for review, privilege, case strategy, and breach response. Broad and continuous. Review plus search plus drafting, one layer. Focused. Q&A and timelines, with Auto Review the newer piece.
Admin overhead High. The platform is configurable, which means it expects an administrator or a service provider partner. Low. Built for teams to run themselves without a dedicated admin seat. Low to moderate. Self-service in posture, less configurable than Relativity by design.
Pricing model clarity Partly clear. aiR for Review and aiR for Privilege are stated as included in standard RelativityOne pricing and packaging. Case strategy and totals are quote only. Quote only. Quote only.
Ecosystem Deepest. A large partner and service provider market, plus an application marketplace. Moderate. Fewer third parties, more shipped in the box. Moderate. Strong in its own stack, smaller surrounding market.
Best structural fit Large portfolios, repeat litigation, a team or vendor that owns the platform. Mid-market firms and lean in-house teams who want the AI without the ops. Teams whose bottleneck is understanding a record fast rather than configuring a workflow.

The admin overhead row is the one most comparisons leave out, and it is usually the row that decides the contract. Relativity's configurability is a real advantage, and it is also a real staffing commitment. If nobody in your firm owns the platform, you will hire a service provider to own it, and that cost belongs in the comparison even though it never appears on the vendor's quote.

What do the pricing models really cost?

We will not give you numbers, because none of the three vendors publishes any, and our directory records all three as quote only. Figures circulating on comparison sites are either private quotes reported second hand or invented. Treat any per gigabyte rate you read without a named source as unreliable.

What you can compare before you get a quote is the model. Three archetypes dominate this market:

  1. Volume based. You pay for data hosted, usually per gigabyte per month, sometimes with processing and production priced separately. Predictable per matter, unpredictable per year, and it punishes over collection.
  2. Seat or subscription based. You pay per user, with data allowances attached. Predictable per year, and it rewards collecting broadly, which is not always the same as collecting well.
  3. Bundled or all inclusive. A negotiated envelope covering hosting, users, and some or all of the AI features. Simplest to budget against, hardest to compare against a rival quote, because the envelope contents differ.

One verified data point is worth having before you negotiate: Relativity states that aiR for Review and aiR for Privilege are included in the standard pricing and packaging for RelativityOne, with aiR for Case Strategy quoted separately. That is unusual candour in this category, and it sets a question you should ask every vendor on your shortlist.

Ask these five, in writing, and the model becomes visible whatever the headline number says.

  • Is AI review priced inside the platform, per matter, per user, or per document processed?
  • What happens to the bill when a matter's data volume triples mid case?
  • Are privilege review and production billed separately from first pass review?
  • What is the cost of getting our data out, in a load ready format, at the end?
  • Is an administrator, certified consultant, or service provider required for us to actually run this?

That last one is the question that separates the platforms more than any feature list. Our broader legal AI pricing guide covers how to run the rest of the procurement conversation.

Which platform fits which litigation team?

Choose Relativity if you run repeat litigation at volume, already have or can hire platform expertise, and want privilege and breach response handled as first class workflows rather than as review with extra steps. The ecosystem is a genuine moat here. If your regular co-counsel, your service providers, and your clients all already work in Relativity, the switching cost of not choosing it is real.

Choose Everlaw if your team is capable but small, and you want the AI usable on day one without an administrator between the lawyers and the platform. The writing assistant matters more than it sounds: teams that live inside one tool from collection through narrative lose less in handoffs.

Choose DISCO if the hardest part of your matters is understanding what happened, fast, across a record nobody has read yet. Cecilia's Q&A and timeline generation are built for exactly that entry point, and a focused product used well beats a broad one used partially.

Choose none of the three if your firm handles a handful of small matters a year. A full e-discovery platform is a standing cost with a standing operator requirement. Smaller cloud options such as Nextpoint or Reveal, or a service provider running the platform on your behalf, are frequently the better answer. We cover the economics of that decision in our guide to AI for small law firms.

Whichever way it goes, run the pilot on your own documents, with your own reviewers, scored against calls those reviewers already made. Every platform in this category looks excellent in a demo built by the vendor. Our framework for evaluating legal AI sets out how to structure that pilot so it produces a decision rather than an impression.

What does Relativity's acquisition streak signal?

Two verified moves, five years apart, tell a consistent story. Relativity acquired Text IQ in May 2021, a company whose machine learning identified sensitive and privileged data, reported at the time by LawSites. In June 2026 it acquired Gavel, a document automation and contract review product that continues to operate under its own name.

Those two purchases are not in the same category, and that is the signal. Text IQ was capability for the core discovery product. Gavel is a step outside discovery entirely, into drafting and document automation, and into the small and mid-size firm market that RelativityOne has never really served. A company that only wanted a better review engine does not buy a Word add-in with a free tier.

For a buyer, that is worth two things. First, the consolidation wave is not finished, and platform choices made today are being made against moving ownership. We track every verified move in the legal AI acquisitions tracker. Second, an acquiring platform is a platform whose roadmap is partly a purchasing decision made by someone else. That is fine, and it is worth knowing before a three year term.

Frequently asked questions

What is Relativity aiR?

aiR is Relativity's family of generative AI products inside RelativityOne, not a single feature. It currently comprises aiR for Review, aiR for Privilege, aiR for Case Strategy, aiR for Data Breach Response, and aiR Assist. Relativity states that aiR for Review and aiR for Privilege are included in standard RelativityOne pricing and packaging, while case strategy is quoted separately.

Is Everlaw cheaper than Relativity?

Nobody outside a live quote can answer that honestly, because neither vendor publishes rates. What can be said is that Everlaw is positioned for teams that do not want to staff a platform administrator, and that unstaffed operating cost is a real part of total cost that never appears on a quote. Compare the two on total annual spend including the people who run it, not on the licence line.

Does DISCO charge per GB?

DISCO does not publish its pricing, and our directory records it as quote only. Volume based pricing is common across this market, so it is a reasonable thing to ask about, but you should get the answer from DISCO in writing rather than from any comparison page, including this one. Ask specifically what happens to the bill when data volume changes mid matter.

Do small firms need an e-discovery platform?

Often not a full one. A firm with occasional, low volume matters usually does better with a lighter cloud tool or a service provider who runs the platform on the firm's behalf, because a platform is an ongoing cost and an ongoing operating responsibility. The threshold is less about firm size than about frequency: if you are running discovery continuously, owning the platform starts to pay. Browse the full e-discovery category to see the lighter end of the bench.

One more thing on defensibility

Whichever platform you land on, the protective order matters as much as the software. Federal Rule of Evidence 502(d) lets a federal court order that privilege is not waived by a disclosure connected with the litigation before it, and that order binds in other federal and state proceedings. Teams running AI assisted privilege review generally want that order in place early. What form it should take on your matter is a question for your litigation counsel, not for a software directory.

Every tool named here is listed in our e-discovery category, free and verified, with no vendor input on how any of this was written. If your platform is missing, submit it.

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