Harvey is a legal AI platform built by Counsel AI Corporation, founded in 2022 by Winston Weinberg, a former securities and antitrust litigator at O'Melveny & Myers, and Gabriel Pereyra, previously a research scientist at Google DeepMind and Meta. It sells exclusively to legal and professional-services organizations rather than to individual practitioners.
The platform ships four core products. Assistant handles chat, drafting and document analysis. Vault stores and bulk-analyzes document sets, supporting up to 10,000 files per project with prebuilt review workflows for M&A, leases and credit agreements. Knowledge provides cited research grounded in licensed legal databases — LexisNexis, Wolters Kluwer, SCC Online and several jurisdiction-specific publishers — alongside web search, EDGAR, EUR-Lex and a firm's own document management system. Workflow Agents is a no-code builder for multi-step processes where the agent plans, adapts based on intermediate results and can solicit human input mid-execution.
Traction is unusually strong for enterprise legal software. As of its March 2026 round — $200M at an $11B valuation, co-led by Sequoia and GIC, bringing total funding above $1B — Harvey reported more than 100,000 lawyers across 1,300 organizations, including a majority of the AmLaw 100, over 500 in-house teams and 50 asset managers, with more than 25,000 custom agents in production.
The honest caveat is cost and access. Harvey publishes no pricing, offers no trial, and sells through a long enterprise cycle with seat minimums. We found no credible per-seat figure — the numbers circulating on third-party comparison sites contradict each other and trace to no primary source, so we do not repeat them here. What is clear is that the commercial model targets firms with real budget and change-management capacity, which makes Harvey a poor fit for solo practitioners and small firms. The value score reflects that access barrier rather than any weakness in the product itself.
Key Benefits
- Legal-native depth: Purpose-built for legal tasks rather than a general assistant with a legal prompt, with practice-area workflows built by domain experts.
- Long-horizon agents: Workflows decompose into steps, adapt to intermediate findings and escalate to a human when judgment is needed.
- Cited research: Knowledge grounds answers in licensed databases and identifiable primary sources, which matters when work product must be defensible.
- Bulk document work: Vault makes multi-thousand-document review tractable — the highest-leverage use case for most firms.
- Hands-on onboarding: Harvey's legal engineers build custom agents with customers, reducing the usual enterprise-AI adoption gap.
Use Cases
- M&A due diligence — Load a data room into Vault, run prebuilt diligence workflows across thousands of contracts, and surface change-of-control, assignment and indemnity issues in a consolidated report.
- Contract drafting and review — Draft from firm precedent, redline against a playbook, and flag deviations from standard positions.
- Regulatory and tax research — Ask jurisdiction-specific questions against connected sources and receive cited answers with links to the underlying authority.
- Litigation document review — Classify and summarize large production sets, then extract facts and timelines for case teams.
