E-discovery (electronic discovery) is the process of identifying, preserving, collecting, reviewing, and producing electronically stored information in response to litigation, investigations, or regulatory demands.
Last reviewed: 2026/05/19
AI-assisted discovery uses artificial intelligence to manage collection, processing, review, and production of electronically stored information in litigation — dramatically reducing per-document review costs through technology-assisted review, predictive coding, and generative AI overlays.
Legal PracticeDocument production is the process of delivering to opposing parties in litigation or investigation the set of documents that are responsive to discovery requests, non-privileged, and within the scope of the applicable discovery order or agreement.
CapabilityA legal hold (also called a litigation hold or preservation notice) is a formal directive issued to individuals within an organization requiring them to preserve all potentially relevant documents and data when litigation or investigation is reasonably anticipated.
CapabilityPrivilege review is the process of examining documents in an e-discovery collection to identify and withhold materials protected by attorney-client privilege, work product doctrine, or other applicable privileges before production to opposing parties.
Cloud eDiscovery with AI predictive coding and document summarization.
Case management with AIFields for personal injury and plaintiff practice.
AI document analysis purpose-built for personal injury case preparation.
Enterprise AI for portfolio-level contract analysis and institutional memory.
Move from this definition to role-based legal AI shortlists and the selection criteria that matter for each type of legal team.
Specialist firm workflows: deep practice area expertise, premium client service, selective tool adoption.
Am Law 200 and global firm workflows: accuracy at scale, security compliance, and matter-level auditability.
Legal department workflows: contract lifecycle, regulatory tracking, outside counsel management, and risk.
Last reviewed: 2026/05/19. Definitions are written by the LawyerAI Editorial team. Commercial relationships are disclosed and do not determine editorial scores or conclusions. See our Sponsorship & Affiliate Disclosure.
E-discovery (electronic discovery) is the process of identifying, preserving, collecting, reviewing, and producing electronically stored information in response to litigation, investigations, or regulatory demands.
Electronic discovery governs how digital information — emails, documents, databases, instant messages, cloud storage — is handled in the litigation and regulatory context. The Federal Rules of Civil Procedure impose specific obligations around e-discovery, and failures in the process carry significant consequences: spoliation sanctions, adverse inference instructions, cost-shifting, or in severe cases, dismissal.
For litigators, e-discovery competence is a professional responsibility issue. Courts expect lawyers to understand the technical dimensions of how their clients store data, what preservation measures are required when litigation is reasonably anticipated, and how to negotiate discovery protocols with opposing counsel. Ignorance of e-discovery mechanics is not a defense to a spoliation motion.
The volume and variety of data in modern e-discovery has made technology assistance standard rather than optional. A corporate data breach case may require processing communications from dozens of custodians across multiple platforms — email, Slack, Teams, CRM systems — collected over several years. Without specialized e-discovery software, managing and reviewing that data at proportionate cost is not feasible.
Understanding the EDRM (Electronic Discovery Reference Model) framework — which defines stages from information governance through production — helps lawyers structure their e-discovery workflows and explain their methodology to courts.
E-discovery platforms manage the entire collection-to-production workflow. Everlaw and Relativity AI are among the most widely deployed platforms, providing document ingestion, processing, review workflows, and production tools in integrated environments. Both have added AI capabilities for document classification, conceptual search, and review prioritization.
Smaller and mid-market platforms like Filevine offer e-discovery functionality integrated with case management tools, reducing the need for separate vendor relationships for firms handling moderate-volume matters.
AI features in e-discovery platforms typically include near-duplicate detection (grouping similar documents for consistent review), email threading (organizing email chains chronologically), and predictive coding (training a relevance model on reviewed examples). More recent additions include generative AI for document summarization and issue spotting.
For a comparison of two major platforms, see Everlaw vs. Filevine.
The right platform depends on matter volume, the firm's existing infrastructure, and the complexity of the collection types involved.