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aws builds a semantic layer for agentic ai using denodo and amazon bedrock agentcore

learn how to build a semantic layer for agentic ai on aws using the denodo platform and amazon bedrock agentcore.

aws builds a semantic layer for agentic ai using denodo and amazon bedrock agentcore — image from AWS
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Summary

aws published a guide on building a semantic layer for agentic ai applications using the denodo platform and amazon bedrock agentcore. the setup federates amazon aurora, amazon redshift, and an on-premises postgresql database into a single view exposed via the denodo mcp server. it also enforces security policies and identity propagation.

What changed

  • federated amazon aurora, amazon redshift, and an on-premises postgresql database into a single view in denodo for agent queries.
  • exposed semantic views to an agentcore-hosted agent through the denodo mcp server registered as an agentcore gateway target.
  • implemented agentcore identity token exchange to flow the end user identity from the enterprise identity provider to denodo.
  • applied row and column filters at query time using global security policies.

Availability

Available now

“The Denodo MCP Server exposes governed views to the agent through the Model Context Protocol (MCP).”

Founder takeaway

review the integration steps to connect your distributed enterprise data to amazon bedrock agents using denodo and agentcore with secure identity propagation.

Source

AWSBuild a semantic layer for agentic AI on AWS with Denodo and Amazon Bedrock AgentCore | Amazon Web Services

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