Enterprise-grade AI legal assistant built for law firms and corporate legal departments, offering contract analysis, legal research, litigation support, document drafting, and compliance automation with enterprise-grade security.
An AI legal assistant that helps lawyers and legal teams analyze contracts, conduct legal research, review documents, draft legal content, and automate compliance workflows using AI models specifically trained for the legal profession.
Harvey stands as the preeminent enterprise AI platform purpose-built for the legal profession, combining proprietary language models fine-tuned on extensive legal corpora with the power of foundation models from OpenAI and Anthropic. Founded in 2022 by Winston Weinberg, a former antitrust attorney at O'Melveny & Myers, and Gabriel Pereyra, a former Google DeepMind research scientist, Harvey has rapidly become the AI platform of choice for elite law firms and corporate legal departments worldwide.
The platform delivers a comprehensive suite of legal AI capabilities spanning contract intelligence, legal research automation, litigation support, document drafting, regulatory compliance monitoring, and due diligence acceleration. Harvey's contract intelligence engine can analyze hundreds of agreements in hours rather than weeks, extracting key provisions such as change-of-control clauses, assignment restrictions, indemnification terms, and IP ownership — then flagging deviations from a firm's preferred playbook. Its legal research module searches across case law, statutes, regulations, and secondary sources while providing verified citations to minimize hallucination risks.
Harvey has achieved remarkable enterprise traction, with adoption by over 60 AmLaw 200 firms including marquee clients such as Allen & Overy (now A&O Shearman) and PwC. The platform reportedly handles millions of queries per month across its client base. Its 2026 strategic partnership expansion with Intapp — the dominant platform for conflicts checking and new business intake at large law firms — integrates real-time privilege protection and ethical wall enforcement directly into AI-assisted workflows, addressing one of the profession's most critical barriers to AI adoption.
Backed by over $200 million in venture capital from Sequoia Capital, Google Ventures, Kleiner Perkins, and OpenAI's Startup Fund at a reported $1.5 billion valuation, Harvey operates on a multi-model architecture that routes different legal tasks to the most appropriate AI model. The platform runs on Microsoft Azure infrastructure with SOC 2 Type II certification, ISO 27001 compliance, GDPR adherence, end-to-end encryption, and a contractual guarantee that no client data is used for model training — meeting the stringent security requirements of the world's largest law firms.
Harvey is positioned as a premium enterprise solution with annual contracts starting at approximately $1,000 to $1,200 per lawyer per month, reflecting its comprehensive feature set, dedicated customer success management, and firm-specific customization capabilities. While this pricing model limits accessibility for smaller firms and solo practitioners, it has proven compelling for large organizations seeking to reduce associate hours on routine tasks, accelerate time-sensitive matters, and maintain competitive advantage in an increasingly AI-augmented legal market.
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Harvey is the leading AI platform for the legal profession, combining proprietary legal AI models with enterprise-grade security to serve 60+ AmLaw 200 firms. Its comprehensive capabilities span contract analysis, legal research, litigation support, and compliance automation, with a standout Intapp integration for privilege protection. The platform excels at accelerating high-volume legal workflows but comes at a premium price point that limits accessibility to large firms and corporate legal departments. Attorneys consistently praise the accuracy of its legal research and the time savings on due diligence, though all outputs require professional review.
Proprietary language models fine-tuned on millions of legal documents from OpenAI and Anthropic foundation models, delivering domain-specific legal reasoning with minimized hallucination risk and verified citation generation for case law, statutes, and regulations.
Use Case:
Analyzing complex merger agreement provisions across hundreds of contracts to identify change-of-control clauses, assignment restrictions, and indemnification terms that deviate from the firm's standard playbook.
AI-powered analysis that extracts key provisions, identifies risks, compares terms against firm playbooks, and flags deviations across large contract portfolios — reducing weeks of manual review to hours of AI-assisted analysis.
Use Case:
Processing hundreds of vendor contracts during M&A due diligence to extract pricing terms, liability caps, termination provisions, and IP assignment clauses, then generating a structured risk summary for the deal team.
Enterprise-scale document review, case law research, motion drafting, and e-discovery support that accelerates litigation workflows from initial case assessment through trial preparation with AI-assisted analysis at every stage.
Use Case:
Reviewing millions of emails and documents in a complex commercial litigation matter for relevance and privilege, then generating case summaries and identifying key evidence to support motion practice.
Automated case law and statutory research with verified citations, precedent analysis, and jurisdictional comparison that reduces research time while maintaining professional accuracy standards and minimizing hallucinated references.
Use Case:
Conducting comprehensive legal research on novel antitrust issues, identifying relevant precedents across federal circuits, distinguishing unfavorable cases, and generating a research memorandum with verified citations.
AI-powered legal writing that generates drafts of contracts, memoranda, briefs, client letters, and corporate filings based on firm-specific templates, style guides, and precedent documents, learning from the firm's own work product.
Use Case:
Drafting complex commercial loan agreements based on firm precedents, automatically incorporating jurisdiction-specific provisions and flagging areas requiring attorney judgment on deal-specific customization.
Real-time attorney-client privilege screening and ethical wall enforcement through deep integration with Intapp's conflicts and new business intake platform, ensuring AI-assisted workflows respect professional responsibility requirements.
Use Case:
Automatically screening document review outputs against Intapp ethical walls before surfacing results to attorneys, preventing privileged information from one client matter from leaking into work for a competing client.
$1,000–$1,200/lawyer/month (annual contract)
Starting ~$1,000/user/month (annual contract)
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In 2026 Harvey is leading with a major expansion of its Intapp partnership, embedding real-time privilege protection and ethical wall enforcement directly into AI-assisted legal workflows. The platform has continued its multi-model evolution with updated foundation models from both OpenAI and Anthropic, enhanced its enterprise workflow automation capabilities to support end-to-end matter lifecycle management, and expanded its international footprint with improved capabilities for non-US jurisdictions. Harvey has also deepened its penetration into corporate legal departments and Big Four advisory firms, moving beyond its traditional law firm base.
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