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Example engagement · Legal Services

AI Contract Review for a Commercial Law Firm

Playbook-based review that flags deviations, proposes fallback language and drafts redlines for the associate to approve.

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90 → 25 min
First-pass review of a supply agreement
Same day
NDA turnaround
92%
Issues caught versus partner review
Profile — Commercial law firm, 35 lawyers, about 400 contracts reviewed a monthTimeline — 8 weeks to production on 4 contract typesTeam — 3 engineers + 1 legal knowledge lawyer
Representative engagement: a composite of the AI work we deliver in this industry, not a named client's project. Figures are the outcomes this kind of build typically delivers, and they are the targets we agree and measure in a pilot before scaling.
The problem

Associates spent hours on first-pass reviews of routine NDAs and supply agreements, at rates clients increasingly pushed back on.

What we build

The approach.

  • 01Wrote the firm's negotiation positions as a structured playbook per contract type.
  • 02Compared each contract clause by clause against the playbook.
  • 03Drafted redlines and comments using the firm's approved fallback language.
  • 04Kept all documents in the firm's own cloud with matter-level access control.
Where the AI works

Claude identifies each clause, compares it to the playbook position, explains the deviation and drafts a redline in the firm's language.

Claude APIPythonMicrosoft Word add-iniManage APIAzure
Proof, not promises

How we measure it.

Review time is recorded in the matter management system. Issue capture is measured against partner-reviewed contracts on a monthly sample.

Questions

Before you ask.

No. Beyond Technologies runs model calls without training data retention and keeps documents in the firm's own cloud.

Always. The AI produces a first pass with reasons. A lawyer reviews and sends every redline.

Next step

Want this measured on your own data? Start with a pilot.

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