Automate sales proposal generation
Turn approved content and customer requirements into proposal drafts for your sales team.
An AI tool built only for legal work that researches case law, reviews contracts, and analyzes large document sets for law firms and in-house teams.
Harvey is an AI tool built only for legal work. Law firms and in-house legal teams use it to research case law, review contracts, and analyze large sets of documents. A feature called Vault handles bulk document review for due diligence, and agents can run multi-step legal tasks on their own, like drafting a first contract redline. Teams sign in with single sign-on and get audit logs and role-based access. It is made by Harvey AI, connects with document systems like iManage and NetDocuments, holds SOC 2 Type II, ISO 27001, and ISO 42001 certifications, and states it does not train its models on customer data.
This fits a legal team that already handles heavy contract review or litigation research; large law firms and corporate legal departments are the main users today. A good starting point is a pilot in one practice group, such as M&A or litigation, on the Vault or Contract Intelligence feature. Pricing is not public; planning estimates from legal-tech writers put enterprise deals well above $100,000 a year, with per-seat costs dropping at large scale, so treat any number as a rough estimate and ask Harvey for a live quote based on seat count and use case. The main risk is trust in AI output, since reviewers note Harvey can miss legal nuance, so staff must check citations and analysis before using them with a client; cost and contract complexity can also be a barrier for a smaller legal team.
Potential matches to review against your requirements. Explore matching tools or read a task guide before you choose.
Turn approved content and customer requirements into proposal drafts for your sales team.
Analyze spending, compare suppliers, and identify opportunities to improve purchasing.
The industries and leadership roles this tool is most often matched with.
How one company factor at a time moves the modeled score. The published score is unchanged.
These estimates cover licensing, setup, integrations, staff time, security, administration, and support.
| Cost measure | Low | Base | High |
|---|---|---|---|
| First-year total | $64.3K | $101.5K | $164K |
| Three-year total | $137.2K | $207.8K | $322.5K |
| First-year cost per unit | $64.3K | $101.5K | $164K |
| Average annual cost per unit (over three years) | $45.7K | $69.3K | $107.5K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $18.8K | $25K | $33.8K |
| Implementation | $10.8K | $18K | $30.6K |
| Integration | $12.1K | $22K | $39.6K |
| Staff time and change management | $7K | $10K | $14K |
| Security | $6K | $8.5K | $12.8K |
| Administration | $4.5K | $6K | $8.1K |
| Support | $2.1K | $2.8K | $3.8K |
Estimate assumptions: This scenario uses a category-based allowance, not a verified price for this product. Based on 1 production workspace. Confirm the vendor’s billing unit and current price or quote before budgeting.
Benefits have not been estimated: The current research does not estimate potential savings, return on investment, or how long it would take to recover the cost. Earlier benefit estimates are excluded.
Confirm current product identity, commercial packaging, data processing terms, sign-in and access rules, retention, integrations, support model, implementation effort, and rollback conditions.
Verify identity, package, availability, ownership, pricing, and security evidence before approving a pilot
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Define what success looks like for a test of Harvey and assign someone to lead it.
Once the requirements above are met, compare a small trial with how your team works today.
Track adoption, output quality, business results, and actual costs against the estimate.
Use the results to decide whether to stop, adjust, or expand the pilot.
Confirm encryption, how the vendor uses your data, customer data separation, how long data stays and how to delete it, activity records, sign-in and user setup, where data is handled, other companies that process data, past incidents, and what your team must manage.
Export executed documents, matter links, clause libraries, playbooks, redlines, obligations, approvals, citations, review history, and audit evidence from Harvey. Keep authoritative source records in Microsoft 365. Preserve privilege and document-to-metadata relationships during export; trained review behavior may not transfer, so validate active matters and obligation continuity before cutover.
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
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Research observations recorded: 1. Evidence quality: Good support.
Recorded score and category rank across research updates.
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