Harvey

What

Harvey is an AI platform for legal and professional services. It is designed for law firms, in-house legal teams, and related professional service organizations that need help with legal research, document analysis, drafting, due diligence, contract review, and complex workflows.

The platform appears to be positioned as a unified legal work environment rather than a single-purpose assistant. Its product suite combines an AI assistant, document storage and bulk analysis, domain-specific research, workflow agents, and an ecosystem layer intended to make Harvey available within existing work environments.

Features

• AI legal assistant — Lets users ask questions, analyze documents, and draft faster with domain-specific AI tailored to legal work.
• Vault for legal documents — Provides secure storage, organization, and bulk analysis of legal documents to support matter-based work and review at scale.
• Knowledge research tools — Supports research across legal, regulatory, and tax domains, which is useful for cross-disciplinary questions and more complex advisory work.
• Workflow Agents — Offers pre-built agents and the option to build custom agents for firm-specific processes, helping standardize repeatable legal tasks.
• Ecosystem access layer — Makes Harvey available where teams already work and grounds answers in trusted sources, which can improve adoption and traceability.
• Collaboration spaces — Supports shared work across legal teams and organizations in secure spaces, which is relevant for multi-party legal and professional service matters.

Helpful Tips

• Assess workflow fit by matter type — Products like this tend to deliver the most value when mapped to high-volume, document-heavy use cases such as due diligence, contract review, and internal research.
• Validate source-grounding requirements — Since legal teams depend on defensible outputs, confirm which source repositories and citation behaviors are available for your target workflows.
• Start with standardizable processes — Workflow agents are usually most effective when applied first to repeatable tasks with clear review rules and known inputs.
• Plan change management and training — Harvey Academy suggests training is part of adoption; legal teams should pair product rollout with role-specific guidance and governance.
• Review collaboration boundaries carefully — If cross-organization workspaces are important, evaluate how matters, permissions, and document-sharing controls align with your operating model.

OpenClaw Skills

Within the OpenClaw ecosystem, Harvey could likely support legal AI skills focused on intake triage, matter research, clause review, due diligence summarization, and drafting workflows. The source page does not confirm a native OpenClaw integration, so this should be treated as a likely orchestration use case rather than a confirmed product capability.

A practical OpenClaw setup could include agents that route legal requests, collect supporting documents, trigger Harvey-based analysis, and return structured outputs to lawyers or legal operations teams. In law firms and in-house departments, that combination could help shift routine work into governed, repeatable AI workflows while preserving expert review for higher-risk legal judgment.