AWS and EDB show a Postgres semantic layer for agentic AI on Bedrock AgentCore
Overview
AWS Machine Learning Blog describes building a semantic layer inside EDB Postgres AI and exposing it to an agent on Amazon Bedrock AgentCore through the AIDB MCP endpoint.
Business meaning is stored as COMMENT ON statements and foreign keys, and access is controlled with Postgres GRANT and row-level security.
The authors report that adding a column comment changed the agent's top-customer answer from about $502,529 to $27,991.66, using the same model and prompt. The figures come from the post itself and have not been independently verified.
Written by AI from the articles below · updated Nov 3, 12:23 PM ET
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- AWS Machine Learning BlogOfficialBuild a semantic layer for agentic AI with EDB Postgres AI and Amazon Bedrock AgentCore
AIThis AWS post shows how to build a semantic layer inside EDB Postgres AI and expose it to an agent on Amazon Bedrock AgentCore through the AIDB MCP endpoint. Business meaning comes from COMMENT ON statements and foreign keys, and access is enforced by Postgres GRANT and row-level security. The authors report that a column comment changes the top-customer answer from about $502,529 to $27,991.66 for the same model and prompt.
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