For many enterprises, critical business information is often stored as unstructured data scattered across multiple content repositories. It is challenging for organizations to make this information available to users when they need it. It is also difficult to do so securely so that relevant information is available to the right users or user groups. Different content repositories have different mechanisms to associate users with groups. These users and groups also change over time. This makes it complex to ensure that the results of a user’s search query only include documents the user is authorized to read.
Amazon Kendra, a highly accurate and easy-to-use intelligent search service powered by machine learning (ML), is releasing a new feature, the Principal Store, to simplify secure search by improving the management of user and group associations across different content repositories.
While documents are ingested for an Amazon Kendra search index, the access control lists

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