AI in Deal Sourcing & Proprietary Origination

This three-day masterclass gives investment teams a working command of the AI tools now reshaping how top-quartile funds source deals. Top-quartile firms already derive a significant share of deal flow from AI-powered platforms that continuously monitor millions of companies and flag opportunities before they reach the broader market — the firms still sourcing manually are competing against teams that screen thousands of targets a quarter. The program is built around the single distinction that determines whether an AI tool creates real competitive advantage: proprietary deal access vs. shared market access. Participants work hands-on with signal-detection platforms, semantic search engines, relationship-intelligence graphs, and LLM-assisted screening workflows, and leave with a firm-specific AI sourcing stack design ready to present to their IC.

Features:

• Distinguish proprietary AI-sourcing platforms from shared-access databases and evaluate tools against that lens
• Apply alternative-data signal detection to identify “ready-to-sell” companies ahead of broader market visibility
• Use semantic search and lookalike modeling to build thesis-aligned target lists at scale
• Build LLM-assisted screening workflows for CIM parsing, thesis-matching, and deal scoring
• Apply relationship-intelligence tools to map warm-intro pathways and prioritize outreach
• Design an integrated, firm-specific AI sourcing stack with governance and confidentiality safeguards