Build a semantic layer for agentic AI with EDB Postgres AI and Amazon Bedrock AgentCore
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This article demonstrates how to build a semantic layer for agentic AI by integrating EDB Postgres AI with Amazon Bedrock AgentCore. The solution embeds business meaning directly into the operational Postgres database using an AIDB extension, which utilizes standard COMMENT statements and foreign keys to define data relationships. An agent running on AgentCore queries this semantic knowledge base to answer customer 360 questions, leveraging Anthropic Claude for planning and execution. Governance is enforced through native Postgres primitives like GRANT statements and row-level security, ensuring that different user roles receive appropriate data access without modifying the agent code. The architecture routes requests from Amazon Cognito-authenticated users through AgentCore Gateway to an MCP endpoint hosted within the Postgres instance. Observability is maintained via OpenTelemetry traces captured in the database, allowing for detailed audit trails of SQL executions. This approach eliminates the need for separate catalogs or Lambda functions, keeping data definitions and access controls synchronized within a single schema.
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