Build multi-tenant agentic chat applications on enterprise data with Amazon Bedrock Managed Knowledge Base

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Multi-tenant agentic chat assistants have become a frequent request for large-scale customers, and document chat sits at the top of the list. A user uploads a contract, a report, or a product manual, and then researches or asks questions about it immediately or in the future. The conversational interface is straightforward to build, but the multi-tenant agentic retrieval system behind it is not. Each tenant’s documents must stay isolated from every other tenant’s, and that boundary must be enforced from a verified identity rather than a value sent by the client. Agentic retrieval compounds the problem. The agent decomposes a question into sub-queries and runs multiple retrievals, and every one of those hops must carry the tenant filter or isolation breaks. You also still need a vector and full-text search engine, an ingestion pipeline that parses and embeds multiple modalities, and a synchronized index. For a team that set out to ship this feature, that is a substantial amount of infrastructure to build, secure, and operate. With Amazon Bedrock Managed Knowledge Base, you can alleviate that undifferentiated work. The service manages ingestion, storage, embedding, and ranking, so there is no infrastructure to provision or capacity to monitor. Beyond infrastructure, it provides built-in agentic retrieval that uses iterative planning and multi-hop retrievals to answer complex questions, and it honors access permissions on every hop. With direct ingestion through the custom connector, your application sends a document straight to the knowledge base, and it becomes …

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