Everlaw

Everlaw is a litigation and investigations platform combining AI-assisted document review, analytics, legal holds, FOIA handling and trial preparation in one evidentiary system of record, with an open platform that lets external AI tools connect to case evidence.

Everlaw is a discovery and litigation platform that positions itself as a single evidentiary system of record. Instead of scattering case data across separate review tools, drafting assistants and storage buckets, teams work from one source of hard evidence, whether they stay inside Everlaw or connect outside AI applications and custom-built solutions to it. The platform combines processing, review, analytics, legal holds, FOIA and public records handling, and trial preparation in one environment. The AI layer is aimed squarely at the document-heavy phase of a matter. Coding Suggestions perform first-pass review, with Everlaw publishing benchmark work claiming that its generative review beat human performance on real litigation data and delivered roughly 36 percent better effectiveness in first-pass review. Clustering and predictive coding produce heat maps and near-instant insight across large collections, and the analytics suite helps teams find key facts quickly when the data set is complex. Legal holds preserve data at the source, automate custodian tracking and keep a full audit trail. Separate modules address public records backlogs and testimony, designations and exhibit work ahead of trial. The audience is legal rather than general purpose: litigation teams at law firms, in-house counsel running discovery, government agencies handling FOIA requests, and investigations groups. The open platform stance matters here, because many organizations already draft in tools such as Harvey, Legora, Copilot or the major model providers, and Everlaw lets those tools reach the evidence rather than forcing a single drafting environment. Against standalone review platforms, Everlaw's differentiator is the combination of AI review, analytics, holds and trial prep in one record with security and data-sprawl controls built in. The tradeoffs are practical: pricing is quote-based through sales, so budgeting requires a demo conversation, and the depth of configuration suits teams with dedicated litigation technology staff more than occasional users.