This session is repeated. One of the biggest promises for LLM agents is automating all knowledge work over unstructured data — we call these "knowledge agents". To date, while there are fragmented tools around data connectors, storage and agent orchestration, AI engineers have trouble building and shipping production-grade agents beyond basic chatbots. In this session, we first outline the highest-value knowledge agent use cases we see being built and deployed at various enterprises. These are: Multi-step document research, Automated document extraction Report generation We then define the core architectural components around knowledge management and agent orchestration required to build these use cases. By the end you'll not only have an understanding of the core technical concepts, but also an appreciation of the ROI you can generate for end-users by shipping these use cases to production.