// AI news · 2026-11-04 · AWS Machine Learning Blog
Build Semantic Layer for Agentic AI with EDB Postgres AI and Amazon Bedrock
A semantic layer built within EDB Postgres AI enables agentic AI agents to query business-meaningful data via Amazon Bedrock AgentCore.
Published 2026-11-04 00:41 (Beijing time)Source AWS Machine Learning BlogAuto-summarised, fact-checked against source
01Summary
Business definitions are stored in PostgreSQL comments, join paths derive from foreign keys, and access control is enforced through native PostgreSQL privileges. The AIDB extension exposes the semantic knowledge base via MCP endpoint, allowing external agents to query it securely. All SQL executions are traced and stored in aidb_otel schema for auditing.
Summarised from the original article by an open-source model, then checked automatically: every number and English name must appear in the source. The original article is authoritative.
02Key points
- Semantic layer resides inside Postgres with business meaning in comments and joins from foreign keys.
- Access control enforced via PostgreSQL GRANT and row-level security, not prompt-based rules.
- Agents query the semantic layer through MCP endpoint routed via AgentCore Gateway.
- Every SQL execution is traced and stored in aidb_otel schema for visibility.
03Source
Build a semantic layer for agentic AI with EDB Postgres AI and Amazon Bedrock AgentCore
AWS Machine Learning Blog · published 2026-11-04 00:41 Beijing time
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