Your attorneys are confirming boilerplate is boilerplate

LLM-based extraction returns each clause as a typed JSON object with clause type, extracted text, page reference, and confidence score, validated against a JSON Schema so hallucinated fields never reach the review interface. NER identifies parties, dates, monetary values, and notice periods as structured data. Covers limitation of liability, indemnification, confidentiality, IP assignment, termination, governing law, and any custom clause types in your playbook.

Extracted clauses compared against your defined playbook positions: acceptable ranges, positions you'll accept with modification, and positions requiring escalation. Deviations get a three-tier severity classification, standard, deviation, or high risk, each with the extracted language, the position it deviates from, and why it matters, replacing the manual line-by-line comparison that occupies most of a routine review.

Detects required provisions absent from the counterparty draft against your standard agreement checklist: GDPR DPA clauses under Article 28, warranty disclaimers, IP assignment language, governing law, dispute resolution. When a required provision is silently missing, most reviewers don't notice what isn't there. The system flags the specific absence and the reason it's required.

A confidence-scored risk rating per contract section and overall, factoring deviation severity, clause category weight, number of non-standard positions, and counterparty history. High-risk contracts and sections surface first in the review queue. Low-confidence extractions route to a separate manual-attention queue so attorneys know what the AI is confident about and what needs independent judgment.

When a clause deviates and your playbook defines a fallback position, the system generates a tracked-changes redline comparing counterparty language against your preferred position, saved directly into iManage, NetDocuments, or SharePoint. The AI generates the first draft of the redline, not the final version; attorney review and approval is required before anything goes to the counterparty.

Integration into your existing contract lifecycle so AI review is a step in the workflow, not a separate tool requiring export and re-import. Contracts landing in an iManage matter or NetDocuments cabinet trigger review automatically via webhook; SharePoint libraries are monitored via Microsoft Graph API. For organisations without a CLM, we build a lightweight review interface that tracks status and stores results alongside the document.