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TutorialsAWS Machine Learning BlogFrom the source· Suntosh Murthy·· 3 hours ago

Build a semantic layer for agentic AI on AWS with Denodo and Amazon Bedrock AgentCore

Who
AWS Machine Learning Blog
What
explains how to build a governed semantic layer for agentic AI using Denodo and Amazon Bedrock AgentCore
Quote
This post uses the same customer 360 pattern, but swaps in a different semantic layer implementation and extends the source mix.

What happened

AWS and Denodo present a guide to building a governed semantic layer for an AgentCore-hosted agent across Amazon Aurora, Amazon Redshift, and on-premises PostgreSQL. The walkthrough defines reusable customer views and spending metrics in Denodo, exposes them through its MCP Server, and propagates user identity through AgentCore. A governance example shows the same query returning visible or masked sensitive fields depending on the caller’s role.

The story so far

AWS and Denodo published a guide showing how an agent hosted on Amazon Bedrock AgentCore can query data across Amazon Aurora, Amazon Redshift, and on-premises PostgreSQL through a governed semantic layer built with Denodo. The walkthrough defines reusable customer views and spending metrics in Denodo and makes them available to the agent through Denodo’s MCP Server. The design propagates the user’s identity through AgentCore so access controls can apply to the person making the request. In the guide’s governance example, the same query returns sensitive fields either visible or masked, depending on the caller’s role.

OpenAI / ChatGPTAgentsDeployment engineeringMCP and tool useTutorials#Tutorials and practice#Agent#RAG#MCP and tool calling#Deployment and engineering#OpenAI

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