First-pass review against your playbook.

• 01

  NDA and vendor-agreement triage

  Classifies the agreement, checks it against your playbook, and routes the standard ones for approval while flagging the rest with reasons.

• 02

  Playbook redlining

  Produces a redline against your standard positions with fallback language, so a lawyer edits rather than starts from the counterparty's paper.

• 03

  Intake and status

  Handles the business's 'where is my contract' traffic from the actual matter status, which is a surprising share of an in-house team's interruptions.

• 01

  Every claim carries its source

  Answers return the clause and the document, and refuse when retrieval is weak. An unsourced legal answer is worse than no answer, and the eval suite scores it as a failure.

• 02

  Privilege and confidentiality are architectural

  Matter-level access control in retrieval, deployment inside your tenancy, and no training on your documents — stated in the contract, enforced in the build.

• 03

  The lawyer signs, always

  The system drafts, redlines and flags. Advice and filing stay with an admitted practitioner, and no pathway lets generated text reach a counterparty unreviewed.

1. 1

   Use-case scoping

   Pick the workflow with the strongest ROI. Define success metrics, guardrails, and integration points.

2. 2

   Tools & memory

   Connect the agent to your real systems — CRM, helpdesk, data warehouse, internal APIs — with auth and audit trails.

3. 3

   Eval suite

   Build a versioned eval set from real conversations so we can prove the agent improves before each release.

4. 4

   Pilot with humans

   Shadow mode → suggested replies → autonomous on low-risk tasks. Humans stay in the loop where it matters.

5. 5

   Production scale

   Monitoring, fallbacks, cost guards, and observability. Weekly improvement cycles based on production data.

• iManage & NetDocuments
• SharePoint
• DocuSign & Adobe Sign
• Contract lifecycle management tools
• Microsoft 365 & Word add-ins
• Postgres with matter-level access control

FAQ

AI agents for contract review: your questions.

• Can it approve an NDA on its own?

  For agreements that match your playbook exactly, with no deviations, and only if you decide it should — the boundary is yours. Most teams start with 'recommend approval' and move to auto-approval once the log supports it.

• What if we don't have a written playbook?

  Building one is the first half of the work, derived from your last few hundred negotiated agreements. Teams usually find the exercise valuable on its own, independently of the automation.

• How is this different from a chatbot?

  Chatbots reply. Agents act. Our agents call APIs, update records, send emails, schedule meetings — with audit logs and rollback. They take actions in your systems, not just respond in a chat window.

• Which LLMs do you use?

  We pick the right model for the task — Claude Sonnet/Opus for reasoning, GPT-4o for tool use, Llama / open-weights when data residency demands it. We're not locked into any vendor and we'll tell you what's cheapest at your volume.

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