Enterprises are drowning in documents, tribal knowledge, siloed systems, and fragmented tools. Traditional knowledge management solutions struggle with discoverability, context preservation, and continuous learning. This session introduces a bold new model—an "Enterprise Brain" built with Agentic AI. You’ll learn how autonomous agents can dynamically ingest, summarize, contextualize, and retrieve information from diverse sources (emails, tickets, docs, wikis), acting as reasoning intermediaries between employees and organizational knowledge. We’ll showcase design patterns for retrieval-augmented generation (RAG), memory persistence, knowledge graph construction, and agent alignment with enterprise policies.

Takeaways:

Designing agents for ingestion, summarization, and retrieval

Role of RAG, embedding stores, and fine-tuned models

Agent lifecycle management and continuous learning

Risks: hallucination, information governance, and access control