How to Use Harvey AI for Legal Research and Contract Review
Harvey is a legal-domain AI platform used by law firms and corporate legal departments. It answers research questions, drafts and reviews contracts, and works with your own document sets.
Quick answer: Harvey is an enterprise product, sold to firms and legal teams, not a self-serve app with a free tier. It is trained and tuned for legal work and runs inside a controlled environment with your firm’s data.
The honest framing: Harvey is a serious tool for a specific buyer. If you are an individual or small firm looking for a $20 subscription, this is not the product.
What does Harvey do?
Its core workflows are legal research, document review, contract analysis, and drafting. You can ask it to summarize a merger agreement, flag unusual clauses against your playbook, or draft a first-pass memo. It also supports uploads of your own documents so answers are grounded in your files rather than general training data.
How does a contract review workflow look?
- Upload the contract, or point Harvey at a repository.
- Ask for a summary and a list of clauses that deviate from standard positions.
- Review the flagged items and drill into the source passages.
- Export a memo for the partner or client.
Harvey cites the passages it used, which is the feature that matters. Uncited legal AI is unusable, because you cannot verify a claim you cannot see the basis for.
How does it compare to general chatbots?
| Factor | Harvey | General LLM |
|---|---|---|
| Grounding | Your uploaded documents | Training data + whatever you paste |
| Citation | Points to source passages | Often unverifiable |
| Data handling | Enterprise controls | Consumer terms |
| Buyer | Firms and legal departments | Anyone |
The difference is not raw model quality. The same underlying models are available to a general chatbot. The difference is grounding, provenance, and the contractual terms a firm can actually accept.
What does it cost?
Harvey does not publish public pricing. It is quoted per firm, typically on an annual contract with seat-based tiers. Expect it in the enterprise budget line, not the tool-expense line. If you need a number, you need a sales conversation.
Where does it fall short?
- It is not a substitute for a lawyer’s judgment. It speeds review; it does not assume responsibility.
- Coverage of unusual jurisdictions may be thinner than a specialist’s knowledge.
- Output still needs verification against primary sources.
- Small firms may find the pricing model and minimums out of reach.
How should a firm adopt it?
Start with one workflow — contract summarization or first-pass review — on a small set of matters. Have a senior associate check every output for a month. Track time saved honestly, not by optimism. Roll out wider only after the accuracy is proven on your own document types, which vary far more between firms than vendors imply.
Who this suits: firms and in-house teams with high document volume and the budget for a managed platform. Who should skip it: solo practitioners and small firms — general LLMs with careful prompting and mandatory verification cover a surprising share of the same ground for far less.
Quick Summary
- Harvey is an enterprise AI platform for legal research, review, and drafting.
- It grounds answers in your uploaded documents and cites source passages.
- Pricing is quoted per firm; no public or free tier.
- Verification remains mandatory — it assists, it does not advise.
- Pilot one workflow on real matters before a firm-wide rollout.
