Rethinking access control for document-grounded AI with Amazon Quick and Amazon Bedrock

What happened

Rethinking access control for RAG (letting a model look information up instead of relying on memory) with Amazon Quick and Amazon Bedrock, AWS Machine Learning Blog announced. Enterprise RAG unlocks insights from knowledge sources like SharePoint (Stack Exchange site for SharePoint enthusiasts), Google Drive, and Confluence, but those sources carry complex permissions. Learn how Amazon Quick and Amazon Bedrock Knowledge Bases enforce document-level access controls in real time, verifying permissions directly with authoritative sources at query time.

Enterprise organizations are adopting Retrieval Augmented Generation (RAG) to unlock insights from company knowledge sources like Microsoft SharePoint, Google Drive, and Atlassian Confluence. However, these knowledge sources contain sensitive information governed by complex permission structures.

Making sure that AI-generated answers respect those permissions is one of the hardest challenges in enterprise AI. The business problem Consider this scenario: A SharePoint site owner creates a knowledge base for their organization.