7. The Rise of Vectorized Due Diligence

Sub-header: How semantic AI accelerates diligence from weeks to hours.

Mini Description: Traditional diligence depends on human review; vectorized diligence adds intelligence. This white paper explains how embeddings outperform keyword search, enabling instant cross-document insights across CIMs, credit agreements, and NDAs.

Highlights:

• Comparison: keyword vs. semantic search precision
• Case study: 400-document diligence completed in under one hour
• Outcome: faster, more accurate risk identification

Context: Cited in Private-Credit.AI pilot programs with diligence teams in direct lending.

Already shared with senior leaders at top private-credit platforms.