Harvey
Harvey helps law firms automate legal work with domain-specific AI.
Harvey is an application-layer AI platform built by legal practitioners that streamlines contract analysis, legal research, document review, and complex multi-step workflows for law firms and corporate legal teams. Unlike general-purpose AI tools, Harvey is trained on domain-specific legal data and embeds awareness of professional responsibility standards. The platform combines conversational AI, legal research capabilities, secure document management, and a no-code Workflow Builder that lets teams encode proprietary expertise into reusable processes. Clients like A&O Shearman report 2–3 hours saved per week on routine tasks and 30% faster contract review cycles.
Problem solved
Legal professionals spend excessive time on manual contract review, document analysis, legal research, and routine workflows that require specialized expertise but not creative judgment.
Target customer
Law firms (especially large corporate practices), in-house legal teams at enterprises, and professional services firms managing high volumes of contracts and legal documents.
Founders
W
Winston Weinberg
CEO & Co-Founder
Former securities and antitrust litigator at O'Melveny & Myers; BA from Kenyon College, JD from USC Gould School of Law.
G
Gabriel Pereyra
President & Co-Founder
Former research scientist at Google DeepMind, Google Brain, and Meta AI; directs Harvey's research and technical roadmap.
Funding history
Seed
$5M
November 2022
Led by OpenAI Startup Fund
· Jeff Dean, Elad Gil, Sarah Guo (Conviction)
Series A
$23M
April 2023
Led by Sequoia Capital
· Unknown
Series B
$80M
December 2023
Led by Elad Gil, Kleiner Perkins
· Sequoia, OpenAI Startup Fund
Series C
$100M
July 2024
Led by GV (Google Ventures)
· Kleiner Perkins, Sequoia, Elad Gil, OpenAI, SV Angel
Series D
$300M
February 2025
Led by Sequoia, Kleiner Perkins
· GV, Elad Gil, Conviction, OpenAI, Coatue, LexisNexis
Series F
$160M
December 2025
Led by Andreessen Horowitz
· EQT, WndrCo, Sequoia, Kleiner Perkins, Conviction, Elad Gil
Series G
$200M
March 2026
Led by GIC, Sequoia
· Andreessen Horowitz, Coatue, Conviction, Elad Gil, Evantic, Kleiner Perkins
Total raised:
$1.04B
Pricing
Not publicly available. Based on market intelligence, estimated at $1,200–$2,000+ per seat per month for enterprise deployments.
Notable customers
A&O Shearman (4,000 staff across 43 jurisdictions, 2,000 lawyers using ContractMatrix daily)
Integrations
Document management systems, legal research databases, secure cloud repositories; specific integrations not publicly detailed.
Tech stack
Bootstrap Icons (Font scripts)
HTTP/3
Google Analytics (Analytics)
Sentry (Issue trackers)
Google Workspace (Email)
jsDelivr (CDN)
cdnjs (CDN)
Cloudflare (CDN)
Website
Competitors
LexisNexis AI-Assisted Research
Traditional legal research focus; less emphasis on contract automation and custom workflow building.
Westlaw AI
Broad legal database platform; less domain-specialized for contract and document automation workflows.
Kira Systems
Focused primarily on document review and due diligence; lacks conversational AI and legal research capabilities.
Why this matters: Harvey represents a rare convergence of domain expertise and AI capability in legal tech. With $1B+ raised and a $11B valuation by March 2026, it demonstrates institutional confidence in AI for high-stakes professional services. The platform's no-code Workflow Builder and enterprise traction (2,000+ daily users at A&O Shearman) signal a shift from generic AI to specialized, deployable tools that directly impact billable hour productivity and compliance.
Best for: Large law firms and enterprise legal departments managing high volumes of contracts, complex due diligence, and multi-step legal workflows who want to reduce manual review time and standardize processes.
Use cases
Contract Review at Scale
A corporate law firm uploads thousands of NDAs, employment agreements, or lease documents. Harvey automatically extracts key data (dates, parties, termination clauses, dollar amounts) and presents them in a sortable Review Table. Lawyers sort by jurisdiction or effective date without opening each document, cutting review time by 30% while catching critical terms.
Custom Workflow Automation
An in-house legal team builds a proprietary workflow using Workflow Builder that combines document triage, legal analysis, and compliance checks. The no-code interface lets non-technical Innovation leaders encode firm-specific precedent and logic. The workflow scales across 50+ routine matters monthly without additional headcount.
Legal Research with Citations
A litigator asks Harvey a complex question about antitrust liability in a specific jurisdiction. Harvey returns a conversational answer grounded in relevant case law and statutes, with full citations and links. The lawyer saves 2–3 hours compared to manual case research while maintaining confidence in the legal foundation.
Secure Document Vault & Analysis
A firm maintains a Vault of privileged client documents and internal precedents. Harvey indexes and analyzes the repository, allowing lawyers to ask questions across the entire corpus with confidence in confidentiality and privilege protections.
Alternatives
OpenAI GPT-4 / Claude (General LLMs)
General-purpose models lack legal domain training, professional responsibility awareness, and are not designed for document-scale analysis or structured legal workflows.
Relativity Assisted Review
Strong for e-discovery and litigation document review; weaker on contract automation, legal research, and multi-agent workflow orchestration.
Thomson Reuters Practical Law
Comprehensive legal content and templates; less AI-driven automation for document analysis and custom workflow building.
FAQ
What does Harvey do? +
Harvey is a domain-specific AI platform built for legal teams that automates contract analysis, legal research, document review, and complex multi-step workflows. It combines a conversational assistant, legal research tool, secure document repository, and a no-code Workflow Builder to help law firms and in-house teams save time on routine work while maintaining legal standards and professional responsibility.
How much does Harvey cost? +
Pricing is not publicly disclosed. Based on market intelligence, enterprise deployments typically range from $1,200–$2,000+ per seat per month. Contact Harvey directly for custom pricing based on firm size, usage, and feature requirements.
What are alternatives to Harvey? +
Kira Systems (document-focused due diligence), Relativity Assisted Review (e-discovery and litigation review), Thomson Reuters Practical Law (legal content and templates), and general LLMs like GPT-4 or Claude (though these lack legal domain expertise and structured workflow capabilities).
Who uses Harvey? +
Large law firms and enterprise legal departments managing high-volume contract work, due diligence, and complex workflows. Notable public customer: A&O Shearman, which deploys Harvey across 4,000 staff in 43 jurisdictions with 2,000 lawyers using the platform daily.
How does Harvey compare to general LLMs like ChatGPT? +
Harvey is trained on legal-specific data and embedded with professional responsibility standards, making it safer and more accurate for legal tasks. General LLMs lack domain expertise, cannot analyze documents at scale, and are not designed for legal workflows. Harvey's Workflow Builder also enables firms to encode proprietary expertise—something general chatbots cannot do.
What results do firms report? +
A&O Shearman reports 2–3 hours saved per week on routine tasks and 30% faster contract review cycles. Individual lawyers report saving 10+ hours per week. Adoption is high, with 2,000+ users at A&O alone.
Tags
legal tech
contract analysis
AI
document review
legal research
workflow automation
enterprise SaaS