Enterprise, custom per-seat annual contracts, from Custom pricing (contact sales)
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Last updated
July 18, 2026
Founded
2022
Headquarters
San Francisco, California, USA
Web AppAPIAI
Overview
Harvey is an enterprise AI platform built specifically for legal and professional services work, covering legal research, contract analysis, drafting, due diligence and litigation support. It was founded in 2022 by former litigator Winston Weinberg and machine learning researcher Gabriel Pereyra, and is headquartered in San Francisco.
Rather than a general chatbot adapted for law, Harvey is built around workflows and evaluation standards specific to legal work, including citation accuracy and document-heavy analysis, and is used by roughly half of the Am Law 100 largest US law firms.
Key Features
Harvey's Assistant module handles open-ended legal question answering and drafting, while Vault provides secure storage and bulk analysis of large legal document sets. Knowledge supports research across complex legal, regulatory and tax questions spanning multiple jurisdictions.
Workflow Agents automate multi-step processes such as due diligence review using pre-built or custom agents, Contract Intelligence extracts key terms and clauses from agreements, and a Command Center gives firm leadership usage analytics and benchmarking. Shared Spaces allow secure collaboration between legal teams across different organizations.
Pricing
Harvey does not publish pricing publicly; every deployment is quoted individually based on firm size, seat count and licensed modules, sold through an enterprise sales process rather than self-serve signup.
Market intelligence estimates put per-seat pricing around 1,000 to 1,200 dollars per month, translating to roughly 12,000 to 16,800 dollars per seat annually, with a typical minimum of 25 to 50-plus seats resulting in annual contracts from about 30,000 dollars up to several hundred thousand dollars for the largest firms.
Key Features
Assistant — General-purpose legal AI for answering questions, analyzing documents and drafting content, tuned specifically for legal domain accuracy.
Vault — Secure repository for storing, organizing and bulk-analyzing large volumes of legal documents in one centralized workspace.
Knowledge — Research tool for investigating complex legal, regulatory and tax questions across multiple practice areas and jurisdictions.
Workflow Agents — Pre-built or custom AI agents that automate multi-step legal processes such as due diligence review and compliance checks.
Contract Intelligence — Extracts key terms and clauses from agreements to speed up negotiation and review, and helps strengthen negotiating positions.
Command Center — Gives firm and legal department leadership usage analytics, benchmarking and insight to guide AI adoption across the organization.
Ecosystem Integrations — Embeds Harvey's capabilities into existing tools legal teams already use, pulling context from multiple firm systems.
Shared Spaces — Enables secure collaboration between legal teams at different organizations within protected, access-controlled environments.
Pros & Cons
Pros
Built by a litigator and an AI researcher specifically for legal accuracy and citation-grade work, not a repurposed general chatbot
Adopted by roughly half of the Am Law 100, indicating strong validation among the largest, most risk-averse law firms
Deep, high-profile funding and model access relationship with OpenAI and other frontier AI labs
Broad module coverage spanning research, drafting, document review and workflow automation in one platform
Enterprise-grade security and compliance features suited to confidential legal work
Cons
No public pricing, and typical deployments require a minimum of 25 to 50-plus seats, putting it out of reach for solo practitioners and small firms
Enterprise sales cycles reportedly run six months or longer before a contract is signed
Reported per-seat costs of 12,000 dollars or more annually make it a significant budget commitment
Requires firm-specific onboarding and integration work to get full value from Workflow Agents and Contract Intelligence
As with any generative AI legal tool, output still requires attorney review to catch potential inaccuracies
Harvey is used by law firms and legal departments for legal research, contract analysis, document drafting, due diligence and litigation support using domain-specific AI.
How much does Harvey AI cost
Harvey does not publish pricing publicly. Third-party estimates place per-seat costs around 1,000 to 1,200 dollars per month, with typical annual contracts starting around 30,000 dollars for a minimum seat count of 25 to 50-plus users.
Who founded Harvey
Harvey was founded in 2022 by Winston Weinberg, a former litigator at O'Melveny and Myers, and Gabriel Pereyra, a former research scientist at Google DeepMind and Meta.
Is Harvey backed by OpenAI
Yes, the OpenAI Startup Fund led Harvey's first funding round in 2022, and OpenAI has participated in subsequent funding rounds alongside investors like Sequoia Capital and Kleiner Perkins.
What is Harvey's valuation
Harvey was valued at approximately 11 billion dollars following a 200 million dollar funding round in March 2026, up from a 1.5 billion dollar valuation roughly a year and a half earlier.
Which law firms use Harvey
Harvey reports serving more than 1,000 clients globally, including roughly half of the Am Law 100, the ranking of the 100 largest US law firms by revenue.