Harvey

Definition

Harvey is an AI platform built specifically for legal professionals, providing tools for legal research, document review, contract analysis, and drafting that are trained and tuned on legal-domain tasks rather than general-purpose chat. It is aimed at law firms and in-house legal departments rather than consumers, and it emphasizes citing traceable source material behind every answer so a lawyer can verify the underlying reasoning.

Overview

Harvey positions itself as legal-domain AI infrastructure rather than a single point tool, offering a set of workflows that map onto tasks lawyers already perform: researching case law and statutes, reviewing due-diligence documents, analyzing contracts against a specific standard, and drafting first versions of legal documents. Because legal work carries high stakes for accuracy, the platform emphasizes citation and traceability, tying its outputs back to identifiable source documents rather than presenting unsupported conclusions. Mechanically, this means Harvey's research and drafting outputs are built to reference the specific case, statute, or clause behind an answer, so a lawyer can verify the underlying source rather than trusting the summary at face value. The company has partnered directly with large law firms to refine its models and workflows against real legal work, reflecting an industry-wide pattern in legal AI where close collaboration with domain experts is treated as necessary, given how costly a hallucinated citation or a missed clause can be in practice. This differs from general-purpose AI assistants in that Harvey is built around legal-specific data formats, citation conventions, and the confidentiality requirements law firms need for client work, including safeguards intended to keep client documents from training models shared across other customers. It also differs from narrower tools like a single contract-review product by spanning research, review, analysis, and drafting under one platform. Adoption inside law firms tends to be gradual and workflow-specific, often starting with lower-risk tasks like initial research summarization before expanding into higher-stakes work like contract drafting, as firms build confidence in output quality and develop internal review practices around it. Firms typically use it for summarizing and researching case law, reviewing large due-diligence sets during a transaction, drafting memos, contracts, or briefs, and checking contract language against a firm's or client's standards. Harvey does not replace a lawyer's judgment; it is designed to speed up research and drafting that a lawyer then reviews and finalizes. It competes with legal research incumbents that have added AI features to existing products as well as newer AI-native entrants targeting the same law firm and corporate legal market, with citation reliability as a key point of comparison. For a firm evaluating legal AI vendors broadly, the comparison against Harvey often turns less on any single feature and more on how deeply a platform's citation practices, confidentiality guarantees, and workflow coverage match the specific mix of research, review, and drafting work that firm actually does day to day. It is also useful to keep in mind that legal AI adoption inside a firm is often shaped as much by partner-level trust and malpractice-risk tolerance as by any measurable difference in a tool's underlying accuracy.

Key Features

• Built specifically for legal workflows rather than general-purpose chat
• Supports legal research with citations traceable back to source material
• Assists with due diligence document review across large document sets
• Analyzes contracts against a firm's or client's specific standards
• Developed in close partnership with large law firms on real legal work
• Includes confidentiality safeguards suited to client-facing legal work

Use Cases

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Frequently Asked Questions

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