Build a semantic layer for agentic AI on AWS with Denodo and Amazon Bedrock AgentCore
Agentic AI applications need governed access to live enterprise data.
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Key points
- In the previous post in this series, we built a semantic layer on AWS using Stardog’s knowledge graph over Amazon Aurora and Amazon Redshift.
- Amazon Bedrock AgentCore is a platform to build, connect, and optimize agents at scale, with any framework or model.
- First, the semantic layer is the Denodo Platform: an AI data layer that provides active context and live, zero-copy access to distributed enterprise data.
- How to expose that semantic view to an AgentCore-hosted agent through the Denodo MCP Server, and how to register the MCP Server as an AgentCore Gateway target.
Sources (1)
- [1]Build a semantic layer for agentic AI on AWS with Denodo and Amazon Bedrock AgentCoreAWS Machine Learning Blog · Oct 20, 03:39 PM
Agentic AI applications need governed access to live enterprise data.
In the previous post in this series, we built a semantic layer on AWS using Stardog’s knowledge graph over Amazon Aurora and Amazon Redshift.
Extractive summary: sentences quoted from the sources.
Before this
- Oct 20, 2026Build a semantic layer for agentic AI on AWS with Strategy Mosaic and Amazon Bedrock AgentCore
- Oct 20, 2026Build a semantic layer for agentic AI on AWS with AtScale and Amazon Bedrock AgentCore
- Oct 19, 2026How Deepgram optimized voice AI at scale with AWS Trainium
- Oct 19, 2026Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM
- Oct 19, 2026Improve TTFT for multi-turn agentic workloads with bi-directional KV transfer in vLLM
- Oct 19, 2026Autonomous intelligence for mining productivity: a multi-agent AI approach to operational value creation
