Aaron Linsky of Bridgewater Associates and Nikhil Benesch of turbopuffer explain how permission-aware retrieval over a 100-million-document research vault broke a conventional search setup, and why native filtering over a clustered vector index is needed to keep search fast without sacrificing recall.
Bridgewater Associates' Applied AI and product engineering leads explain how they built the Vault, a governed repository of more than 100 million unstructured documents, and why humans and agents need different things from the same search system. They cover a hand-built benchmark that lifted precision at 10 from about 60% to over 90%, the filtering and scaling choices behind it, and the shift toward proactive agents that bring investors the topics most deserving of their attention.