Question

A financial advisory startup builds a customer support assistant using Amazon Bedrock Agents. Users interact across multiple sessions over several days, and the business requires the agent to remember key facts from earlier conversations (such as a customer's stated risk tolerance) so that follow-up sessions feel continuous. The team already uses session state for within-conversation context, but that context is lost once a session ends. Which approach most directly satisfies the requirement with the least custom development?

Accepted Answer

Enable Amazon Bedrock Agents memory retention, which summarizes and persists session information across multiple sessions for a configured retention period

Answer

Increase the foundation model's context window and pass the full transcript of every prior session in each new request

Answer

Store each session's raw messages in an S3 bucket and re-ingest them into the agent's knowledge base after every conversation

Answer

Rely on the agent's default session state, which automatically carries over across separate user sessions