Metal AI, an institutional intelligence platform for private equity firms, built its retrieval layer on Vespa Cloud to handle entity- and relationship-driven data at scale. With 95% of retrieval handled by AI agents, Metal uses Vespa's multi-entity modeling, advanced ranking, and real-time filtering to power workflows like DDQ
Table of contents
IntroductionThe Need for Relationship-Driven RetrievalChoosing a Retrieval Layer without LimitsArchitecture in ActionTurning DDQ Chaos into Structured, Approved IntelligenceScaling without Infrastructure HeadachesLooking Forward: Build for an Agentic FutureSort: