Harvey
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.
An AI contract review tool that redlines contracts against more than 135 lawyer-written playbooks, scaling from a solo attorney to a 40-person department.
LegalOn is an AI contract review tool. Legal teams use it to triage incoming contract requests from email, Slack, or forms, then review and redline them against company standards using more than 135 attorney-built playbooks covering different contract types, industries, and countries. It sells three tiers, from Core Review for solo attorneys up to a full Productivity Suite that adds matter management and intake automation for larger teams, and works as an add-in inside Microsoft Word. It is made by LegalOn Technologies, holds SOC 2 Type II, ISO 27001, and ISO 27007 certifications, and states it meets GDPR and CCPA rules.
This fits a legal team that reviews a high volume of routine contracts, like NDAs or vendor deals, scaling from a single in-house lawyer up to a legal department with 40 or more staff; the company reports more than 9,000 organizations use it. LegalOn does not publish exact prices but names three plans, Core Review for solo attorneys and the Contracting and Productivity Suites for larger teams, so ask a sales rep for a quote scoped to the right tier for your size. A sensible starting point is the Core Review tier for one or two attorneys, using its built-in playbooks on your highest-volume contract type first. The main thing to check is playbook fit, since a generic attorney-built playbook may not match your company's own risk tolerance right away, so plan real time to customize it before a full rollout.
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 LegalOn 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.
Review before rollout: confirm how to export your data, revoke access, and return to your existing workflow. Assign an owner and test the rollback plan before expanding use.
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.
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.
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Research observations recorded: 1. Evidence quality: Some support.
Recorded score and category rank across research updates.
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