Harvey AI 2026: Enterprise Legal AI for Law Firms
Last updated: 2026-07-01
Harvey is enterprise legal AI by Counsel AI for law firms and in-house teams. It drafts, reviews, and researches contracts and case law. Read our 2026 review.
Harvey is an enterprise legal AI platform built by Counsel AI Corporation for law firms and in-house legal teams. It drafts, reviews, and researches across contracts and case law. Harvey is sold through enterprise plans, with no public free tier.
About Harvey
Harvey is a generative AI platform purpose-built for law firms and in-house legal teams. Founded in summer 2022 by Winston Weinberg (O'Melveny & Myers litigator) and Gabriel Pereyra (Google DeepMind researcher), Harvey now serves 142,000+ legal professionals across 60 of the AmLaw 100 and Fortune 500 companies. The platform uses proprietary domain-specific training on Azure OpenAI to deliver contract analysis, legal research, document drafting, and workflow automation with source-cited answers. Harvey's four core products address the full legal lifecycle. Assistant handles document analysis and drafting with real-time legal research. Vault securely bulk-analyzes thousands of documents simultaneously for due diligence and M&A. Knowledge researches complex regulatory and tax questions with citations tied to case filings and statutes. Workflow Agents execute multi-step legal work end-to-end, from contract review to risk scoring. The platform processes 1.3 million documents daily and handles 200,000+ queries per day across 1,500 countries. Key use cases are contract analysis (80x faster than manual review), due diligence (document discovery and risk assessment), litigation support (document clustering and privilege review), and regulatory compliance (automated policy checking). Best for in-house counsel at Fortune 500s and AmLaw 100 firms managing high-volume, high-stakes legal work. Solo practitioners and small firms cannot access it: minimum annual commitment starts at $50K with seat minimums of 25-50 users. Harvey launched mobile apps in September 2025 with voice-to-prompt and document scanning. The platform integrates with Microsoft Word, Outlook, and SharePoint natively. MCP (Model Context Protocol) support allows external AI assistants like Claude to embed Harvey's legal Q&A and document analysis into their own workflows. Raised $1.22B in funding; valued at $11 billion in March 2026 Series G led by GIC and Sequoia. Compliance: SOC 2 Type II (2026 audit), ISO 27001, ISO 42001 (AI management), GDPR and CCPA certified, EU-US Data Privacy Framework compliant. Zero-training guarantee on customer data. Regional data residency in EU, US, or Australia. Customers report 92% monthly active usage and save 20+ hours per month on average. No public pricing, enterprise sales only.
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Pricing
Enterprise-only, custom pricing. Estimated $50K-$300K+ per year. $1,000-$1,200 per user per month reported for large deployments. Minimum seat count 25-50. Implementation and training fees add 30-60% overhead. Annual renewal contracts typically include 10-25% uplift.
Feature Comparison by Tier
| Feature | Enterprise |
|---|---|
| Document Review Speed | 80x faster than manual |
| Daily Document Processing | 1.3 million documents |
| Citation Verification | Sentence-level citations to case law |
| Workflow Agents | Custom multi-step automation |
| Bulk Vault Capacity | 10,000 documents per project |
| Mobile Apps | iOS, Android with voice dictation |
| MCP Integration | Native Model Context Protocol support |
| Office Integration | Word, Outlook, SharePoint native |
Key Features
- Contract Analysis at Scale: Processes 1.3 million documents daily. Document review 80 times faster than manual with risk scoring, obligation extraction, and redline suggestions.
- Citation-Backed Legal Research: Answers grounded in statutes, case law, and regulatory sources. Every claim is sentence-level cited so lawyers can verify and trace reasoning without fact-checking burden.
- Workflow Agents for Complex Work: Pre-built and custom agents execute multi-step legal work end-to-end. Handles contract negotiation loops, due diligence workflows, and compliance reviews autonomously.
- Mobile Voice Dictation: iOS and Android apps launched September 2025 with hands-free voice-to-prompt. Document scanning and query history sync across devices for continuous work.
- Vault for Bulk Document Analysis: Securely upload and organize legal documents. Analyze up to 10,000 documents per vault simultaneously for discovery, M&A due diligence, and litigation support.
- MCP Integration Standard: Embeds Harvey's legal Q&A and vault analysis into external AI agents via Model Context Protocol. Claude and other MCP clients can invoke Harvey natively.
Pros
- Reduces legal document review time by 80 percent. Handles 1.3 million files daily across 142,000+ users; 92% monthly active usage shows sustained value.
- Citations ground every research answer in actual case law, statutes, and regulatory sources. Eliminates hallucinations and malpractice risk from fabricated citations.
- Entrenched in AmLaw 100: 60 of the top 100 law firms and Fortune 500 in-house teams use Harvey. Network effects and contractual lock-in create defensible moat.
- Enterprise-grade security with SOC 2 Type II (2026), ISO 27001, ISO 42001 certifications. Zero-training guarantee on customer data. Regional data residency in EU, US, or Australia.
- Mobile and voice launched September 2025. MCP support allows embedding into other AI agents. Deep Microsoft Office integration reduces context switching.
Cons
- Price: $1,000-$1,200 per user per month with $50K-$300K+ annual minimums. Out of reach for solo practitioners and firms under 25 lawyers. Implementation fees add 30-60% overhead.
- Steep learning curve. Vault has hard 10,000-document cap per project, which fails in large litigation. Power users report frequent small glitches and weak dashboarding.
- Hallucinations still occur: citations can be fabricated or incorrect if underlying models fail. Requires active fact-checking and legal judgment, not fire-and-forget.
- Enterprise-only sales motion. No free trial, no self-serve, no public pricing. Locks out market segments below Fortune 500 and AmLaw 100.
Product Information
- Cloud
- Yes
- Self-Hosted
- No
- On-Premise
- No
- Languages
- English, Spanish, French, German, Chinese
- Training
- Implementation onboarding, Product documentation, Customer success webinars, Video tutorials, Professional services for custom agents
Frequently Asked Questions
What is Harvey?
Harvey is an enterprise AI platform purpose-built for law firms and in-house legal teams, made by Counsel AI Corporation. It handles document review 80 times faster than manual review, contract drafting, due diligence, and legal research with source citations. Harvey is used by 60 of the AmLaw 100 firms as of 2026.
How much does Harvey cost?
Harvey is sold exclusively through enterprise contracts and does not publish pricing publicly. There is no free tier, no self-serve trial, and no monthly subscription available to individuals. Organizations must contact Harvey's sales team for a custom quote, which typically involves per-seat or volume-based licensing arrangements.
Is Harvey free to use?
No. Harvey has no free tier, no free trial, and no self-serve access. It is an enterprise product sold to law firms and legal departments through negotiated contracts. Individual lawyers or solo practitioners cannot purchase Harvey directly.
Who is Harvey best for?
Harvey is best for large law firms, Big Law associates, and in-house legal teams at mid-to-large corporations who handle high volumes of contracts, due diligence, or regulatory filings. It is not suited for solo practitioners, small firms on tight budgets, or non-legal professionals.
What can Harvey do?
Harvey can draft and redline contracts, perform M&A due diligence on hundreds of documents simultaneously, research case law with cited sources, summarize deposition transcripts, and run custom workflow agents for repetitive legal tasks. It integrates with firm document management systems including iManage and NetDocuments.
How does Harvey handle confidentiality?
Harvey uses private, isolated model instances for each enterprise customer, so one firm's data is never used to train another firm's model. All data is encrypted in transit and at rest. Harvey supports SOC 2 Type II compliance and signs data processing agreements to satisfy law firm and corporate requirements.
What are the main alternatives to Harvey?
The closest alternatives in enterprise legal AI are Ironclad AI for contract lifecycle management, Lexis+ AI and Westlaw AI for legal research, and Luminance for due diligence. For teams wanting more flexibility at lower price points, Clio Duo and Smokeball serve smaller firms effectively.
Is Harvey built on GPT?
Harvey is built on top of large language models from OpenAI and Anthropic, customized through fine-tuning and reinforcement learning on legal data. Harvey does not publicly disclose exactly which models power each feature. Its legal-specific fine-tuning is what differentiates it from using generic GPT-4 or Claude directly.