M&A due diligence automation

Problem

M&A due diligence requires reviewing hundreds or thousands of contracts, leases, and agreements in a data room. Paralegals and junior associates spend 2–6 weeks manually reading documents, extracting key terms, and flagging issues. The cost is enormous ($50K–$200K+ for a mid-market deal), and human fatigue leads to missed risks.

Solution

The AI agent reads every document in the data room, extracts key terms (change of control provisions, assignment clauses, termination triggers, IP ownership, indemnification caps, non-compete terms), flags risks against a configurable checklist, and generates a structured due diligence report with citations to source documents. Lawyers review the AI-generated report and dig deeper on flagged items instead of reading every page.

Benefits

• 70% faster due diligence cycle time
• 3–5x more documents reviewed per dollar spent
• Consistent extraction—no terms missed due to fatigue
• Structured output that maps directly to deal risk frameworks

How to get started

1. 1

   Configure extraction criteria

   Define the key terms and risk factors for this deal type: change of control, assignment, IP, indemnification, non-compete, data privacy obligations, and any deal-specific concerns. Use templates for common deal types.

2. 2

   Ingest the data room

   Connect to the virtual data room (Intralinks, Datasite, etc.) or upload documents. The agent reads every document, classifies by type (lease, employment agreement, customer contract, etc.), and begins extraction.

3. 3

   Review and finalize

   Review the structured report: extracted terms organized by risk category, flagged items with citations, and a summary for each document group. Lawyers focus review time on flagged items and edge cases rather than reading every document.

Recommended tools

Harvey AI, Casetext CoCounsel, Kira Systems. See the full list on the AI Legal Agent pillar page.