Automated NDA Redlining for a $1B+ AUM PE Firm

Every M&A deal starts with an NDA. For a PE firm running dozens of transactions a year, that means dozens of incoming NDAs — each written differently, each requiring a lawyer to manually compare every clause against the firm's preferred language and rewrite the ones that don't align. The process was time-consuming, repetitive, and created bottlenecks at exactly the wrong moment in a deal cycle. The firm wanted to know: could AI handle the first pass?

The system ingested NDA documents (.docx), embedded them into a vector store, and ran a 5-step decomposition chain for each of 18+ clause categories — covering everything from Definition of Representatives to Non-Solicit duration to Governing Law. For each clause, the chain: extracted what the NDA actually said, checked it against the firm's preferred position playbook, determined whether alignment was needed, identified the exact text to modify, and rewrote that specific chunk. The output was a Word document with tracked changes — directly usable by the firm's attorneys.