Secure AI for Transactional Due Diligence

Overview

Milbank’s transactional teams regularly analyze thousands of deal documents during mergers and acquisitions. The firm wanted to improve speed and consistency while keeping all client materials inside its private network.

Challenges

Challenges

• Manual term extraction from 500+ contracts per transaction.
• Limited visibility into historical patterns or recurring risk terms.
• Inconsistent diligence summaries across different deal teams.
• Reluctance to use public AI tools due to client-confidentiality concerns.

Solution

Solution

Milbank leveraged AtlasAI’s Tabular Review and Private AI Search to automate diligence reviews while maintaining full data control.

• The Tabular Review feature transformed unstructured contracts into structured, searchable tables, automatically tagging key provisions like governing law, indemnities, assignment clauses, and termination rights.
• The Knowledge Graph cross-linked prior deal outcomes and surfaced frequently negotiated risk positions.
• Using AtlasAI’s Word Plugin, attorneys could generate side-by-side comparisons and instant redline suggestions.

AtlasAI operated within Milbank’s Azure-hosted environment, directly connected to their DMS (iManage) and identity controls, ensuring zero external exposure.

Results

Results

• 50% reduction in time spent on due-diligence reviews.
• Increased accuracy in identifying anomalies and risky language.
• Secure, auditable data lineage for all diligence outputs.
• A shared institutional dataset of deal patterns to guide negotiations.