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Harvey AI
AI for legal work, built specifically for law firms and legal departments.
In short
Legal-domain AI built for law firms rather than adapted from a general assistant. Handles legal research, document drafting, contract review, and due diligence in the contexts a lawyer actually works in, not the contexts a general AI was trained on.
Built for: Compliance/Audit Professionals · Enterprise Operations
| Tier | Model | Key inclusions | Limits |
|---|---|---|---|
| Firm / department licence | Enterprise pricing, custom | Data controls, professional liability alignment, admin oversight | Contract-based |
Pricing, version numbers, context-window sizes, and compliance certifications change frequently. Where stated they are accurate as of the as_of date and should be confirmed with the vendor before any procurement or compliance decision. Where they could not be stated confidently they are omitted rather than guessed.
The governance question this raises
The legal professional responsibility question is the same regardless of tool: a lawyer cannot delegate judgment to an AI, and outputs must be reviewed before they touch client work. What changes is which tasks can be accelerated. The professional liability point is that if Harvey produces a flawed contract clause and a lawyer submits it without review, the lawyer's error, not the vendor's. On the data side, privilege must be maintained for client matter inputs, which requires a confirmed data path under the firm's privilege policy, not just the vendor's standard terms.
No compliance certifications are listed here. Certification status is vendor-specific and time-specific, so it is stated only where verified rather than assumed. Check the vendor’s trust centre and confirm it covers the specific tier you are buying.
API and SDKs: Available for firm-scale deployment.
Strengths
Drawbacks
Consider instead: CoCounsel (Casetext), Microsoft Copilot, ChatGPT
Legal-domain AI built for law firms rather than adapted from a general assistant. Handles legal research, document drafting, contract review, and due diligence in the contexts a lawyer actually works in, not the contexts a general AI was trained on.
Built on frontier models (primarily OpenAI and Anthropic) with legal-domain fine-tuning and retrieval.
Legal-grade data terms. Client matter data is not used to train models. Verify the DPA for your jurisdiction.
The closest comparable tools are CoCounsel (Casetext), Microsoft Copilot, ChatGPT. Which fits depends on where the work already lives and what the organization's data terms require.
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