title: "From enterprise search to enterprise context: what AI agents actually need"

Effective AI agents in a corporate setting require a move beyond traditional enterprise search to a more comprehensive 'enterprise context'. This context involves a deep, real-time understanding of a company's knowledge, including its people, activities, and the relationships between data. Simple retrieval-augmented generation (RAG) and vector search are insufficient because they lack this nuanced understanding and fail to handle complex permission structures. Building a robust enterprise context necessitates a foundation of comprehensive connectors, continuous indexing, strict permission enforcement, and a dynamic knowledge graph to map relationships.