Most enterprise intelligence is rented. Strategy consultants arrive, analyze a snapshot of your data, deliver a deck, and leave. The insights age immediately. The institutional knowledge walks out the door. And the next strategic question — a new market opportunity, a shift in competitive dynamics, a distribution channel underperforming — sends you right back into the same expensive cycle. Enterprises spend north of $300 billion a year on this model, and what they're really paying for is a temporary answer to a permanent need.

Hometap, the Boston-based fintech redefining home equity investing, decided to stop renting intelligence and start building it. Operating in a genuinely novel financial product category with no off-the-shelf data models to lean on, Hometap faced a unique challenge: they couldn't just bolt AI onto existing analytics infrastructure. Under CIO Eric Chacon, the team built a revenue intelligence engine from the ground up — powered by a semantic knowledge graph foundation and GraphRAG — that continuously transforms the company's proprietary data into strategic insight, revenue acceleration, and operational advantage across sales, marketing, and distribution.

This session is a candid customer-vendor dialogue between Fluree CEO Brian Platz and Hometap CIO Eric Chacon. Together, they make the case that knowledge graphs are the missing infrastructure layer between enterprise data and AI you can actually trust with strategic decisions.