Everlaw Cloud E-Discovery and Litigation API

Everlaw cloud e-discovery and litigation support REST API for law firms, corporate legal departments, and government agencies to manage the entire e-discovery lifecycle from data collection through production. Enables AI agents to manage case and matter setup for litigation workflow automation, handle data upload and processing pipeline for legal document ingestion automation, access predictive coding and AI-assisted review for legal document review efficiency automation, retrieve document coding and tagging for legal review workflow automation, manage search and concept clustering for legal document analysis automation, handle document production and TIFF conversion for litigation production automation, access storybuilder and chronological case construction for trial preparation automation, retrieve team collaboration and reviewer assignment for legal team coordination automation, manage deposition transcript management for witness preparation automation, and integrate Everlaw with law firm practice management and case management systems for end-to-end litigation workflow management.

Evaluated Mar 07, 2026 (0d ago) vcurrent
Homepage ↗ Developer Tools everlaw e-discovery litigation document-review cloud-ediscovery legal-tech
⚙ Agent Friendliness
55
/ 100
Can an agent use this?
🔒 Security
74
/ 100
Is it safe for agents?
⚡ Reliability
68
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
18
Documentation
70
Error Messages
68
Auth Simplicity
67
Rate Limits
65

🔒 Security

TLS Enforcement
92
Auth Strength
70
Scope Granularity
70
Dep. Hygiene
67
Secret Handling
70

E-discovery. SOC2, ISO27001, FedRAMP. OAuth2. US/EU. Litigation documents and privileged legal data.

⚡ Reliability

Uptime/SLA
70
Version Stability
70
Breaking Changes
65
Error Recovery
67
AF Security Reliability

Best When

A law firm, corporate legal department, or government agency wanting AI agents to automate e-discovery case setup, document processing, AI-assisted review, and litigation production within Everlaw's cloud platform.

Avoid When

WORK PRODUCT DOCTRINE PROTECTION FOR AI REVIEW CONFIGURATION: Automated AI review model configuration (training sets, seed documents, relevance criteria) in Everlaw constitutes attorney work product; AI model training data and review configuration are discoverable under some court interpretations; consult litigation counsel on protective order for AI-assisted review methodology before automated deployment. CROSS-BORDER DATA COLLECTION FOR EU CUSTODIANS: Automated data collection from European employee custodians via Everlaw integration must comply with GDPR and EU data transfer requirements; automated collection without GDPR-compliant transfer mechanism creates GDPR violation; GDPR Standard Contractual Clauses required for EU-US data transfer in litigation context. PREDICTIVE CODING VALIDATION DISCLOSURE: Automated predictive coding via Everlaw for large document set review must implement defensible validation testing; courts increasingly require disclosure of predictive coding methodology and validation metrics; automated deployment without documented validation protocol creates defensibility challenge.

Use Cases

  • Processing litigation document sets from e-discovery workflow automation agents
  • Managing document review from AI-assisted litigation review agents
  • Building case timelines from trial preparation automation agents
  • Coordinating review teams from litigation project management agents

Not For

  • Contract lifecycle management (use Ironclad or Conga)
  • Legal hold and data preservation (standalone — use DISCO or Onna)
  • Regulatory compliance filing

Interface

REST API
Yes
GraphQL
No
gRPC
No
MCP Server
No
SDK
No
Webhooks
Yes

Authentication

Methods: oauth apikey
OAuth: Yes Scopes: Yes

Everlaw uses OAuth 2.0 with scopes and API key for integrations. REST API with JSON. Oakland, California HQ. Founded 2011 by AJ Shankar and Erin Wayne. Private (~$200M raised, Andreessen Horowitz, Georgian). Focused on cloud e-discovery for law firms, corporate legal departments, and government. Predictive coding, storybuilder, deposition management. FedRAMP authorized for government use. SOC2 Type II, ISO 27001. Competes with DISCO, Relativity, and Reveal for cloud e-discovery.

Pricing

Model: usage
Free tier: No
Requires CC: No

Oakland CA. Private (~$200M raised). Founded 2011. Per-GB and per-reviewer pricing. Unlimited reviewer plans. FedRAMP for government.

Agent Metadata

Pagination
cursor
Idempotent
Full
Retry Guidance
Documented

Known Gotchas

  • PROCESSING JOB ASYNC STATUS POLLING: Everlaw document processing for uploaded data sets is asynchronous; automated ingestion workflows must poll processing job status or use webhook notification rather than assuming synchronous completion; large volume uploads (millions of documents) may have processing times measured in hours; design automated workflows with processing completion gate
  • PREDICTIVE CODING MODEL VALIDATION DEFENSIBILITY: Automated predictive coding deployment via Everlaw requires documented validation protocol (elusion testing, precision/recall measurement) to be defensible in court; automated AI-assisted review without validation testing creates adverse inference motion exposure if opposing counsel challenges methodology; document validation metrics as part of automated review protocol
  • STORYBUILDER TIMELINE EXPORT FORMAT: Everlaw storybuilder exports litigation timelines in specific format; automated case chronology generation via Storybuilder API produces timeline artifacts in Everlaw-specific format; automated export to trial presentation software requires format conversion; verify target trial presentation system compatibility before automated timeline export workflow
  • MATTER PERMISSION SCOPING FOR OUTSIDE COUNSEL: Everlaw matter permissions control outside counsel and client access to review data; automated privilege log and review data exports must respect matter-level access controls; automated analytics pulling across matter boundaries requires matter-level permission verification to prevent inadvertent cross-matter data exposure
  • REVIEW ASSIGNMENT LOAD BALANCING FOR TEAM COORDINATION: Automated document review assignment via Everlaw must implement equitable load balancing based on reviewer speed and document complexity; automated assignment without reviewer capacity modeling creates reviewer overallocation during peak review periods and deadline risk
  • FEDRAMP INSTANCE vs COMMERCIAL INSTANCE ROUTING: Everlaw has FedRAMP authorized government instance separate from commercial instance; automated government client workflows must route to FedRAMP instance; cross-instance document sharing between government and commercial Everlaw instances is not permitted; verify government client instance routing before automated deployment

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Scores are editorial opinions as of 2026-03-07.

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