Build Multi-Tenant AI Chat with Amazon Bedrock
Key takeaways
- Amazon Bedrock enables building multi-tenant AI chat applications on private data.
- Per-user data isolation is crucial for security and privacy in multi-tenant systems.
- Asynchronous indexing improves efficiency for document processing.
- The solution supports grounded question-answering from user-uploaded content.
Who benefits
Summary
This post demonstrates how to create a multi-tenant agentic document chat application using Amazon Bedrock's Managed Knowledge Base, allowing users to upload documents and ask grounded questions. It covers data ingestion, retrieval, asynchronous indexing, per-user data isolation, and best practices for scaling the solution.
Why it matters
Professionals can develop secure, scalable, and personalized AI chat applications for diverse user bases, enabling efficient information retrieval from private data while maintaining strict data isolation.
How to implement this in your domain
- 1Design a robust data ingestion pipeline for user-uploaded documents into the Bedrock Knowledge Base.
- 2Implement mechanisms for strict per-user data isolation to ensure tenant privacy and security.
- 3Develop the agentic chat logic to leverage the knowledge base for grounded question answering.
- 4Consider asynchronous indexing strategies to handle document uploads efficiently at scale.
- 5Apply best practices for monitoring and scaling the multi-tenant application in a production environment.
Original post by George Belsian
"Learn how to build a multi-tenant agentic document chat application on Amazon Bedrock Managed Knowledge Base, where users upload documents and immediately ask grounded questions. This post covers the ingestion and retrieval flows, the asynchronous indexing lifecycle, per-user dat…"
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