Enterprise knowledge is often scattered across document stores, business systems, SharePoint, OneLake, and the public web. The real challenge isn’t simply putting documents into a vector database—it’s helping agents select the right sources, plan retrieval, and return traceable answers.
✅ Connect internal and external knowledge sources
✅ Automate content extraction, chunking, and vectorization
✅ Combine static documents with live web information
✅ Use an LLM to plan queries and select sources
✅ Run parallel retrieval, semantic reranking, and result aggregation
✅ Share one knowledge base across multiple agents
✅ Return grounded results with citations
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