The setup uses the AIDB extension to maintain context via standard Postgres comments, foreign keys, and native row-level security. Amazon Bedrock provides the Claude model to plan queries and AgentCore capabilities to manage the operational runtime environment. In a demonstrated Stardog customer 360 scenario, the system prevented agents from confusing total order prices with unit costs. External agents access the catalog via a Model Context Protocol endpoint fronted by an Application Load Balancer.
Key points
Embedding business logic directly into the database prevents agents from relying on falli…: Embedding business logic directly into the database prevents agents from relying on fallible advisory prompts.
Different caller roles interacting with the exact same agent receive restricted results b…: Different caller roles interacting with the exact same agent receive restricted results based on database privileges.
Connecting external agents via a built-in Model Context Protocol endpoint simplifies inte…: Connecting external agents via a built-in Model Context Protocol endpoint simplifies integration with existing enterprise catalogs.
Sources checked by our analysis pipeline: 1
Artificial Intelligence
Build a semantic layer for agentic AI with EDB Postgres AI and Amazon Bedrock AgentCore
In this post, we show how to build a semantic layer for agentic AI using EDB Postgres AI. We run a Strands Agents agent on Amazon Bedrock AgentCore that queries the layer to answer customer 360 (C360) questions. Earlier posts in this series built the same C360 pattern with Stardog’s knowledge graph, Denodo’s data virtualization platform, AtScale’s dimensional model, and Strategy Mosaic’s linked models.
EDB Postgres AI puts the semantic layer inside the operational Postgres database as an AIDB extension. Business meaning lives next to the data in standard Postgres COMMENT
statements, the join graph comes from Postgres foreign keys, and governance uses Postgres GRANT
and row-level security through the Model Context Protocol (MCP) endpoint that ships with AIDB.
By the end of this post you will know:
- How to build an AIDB semantic knowledge base (SemKB) over a Postgres schema, how
COMMENT ON
statements andaidb.create_semantic_alias
behave as the authoring surface, and how foreign keys crawl into join paths. - How to…
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