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

In the first post in this series, we built a semantic layer on AWS using Stardog’s knowledge graph over Amazon Aurora and Amazon Redshift. We ran a Strands agent on Amazon Bedrock AgentCore against that layer. The second post kept the same customer 360 (C360) pattern and swapped in Denodo’s data virtualization platform, extending the source mix to include an on-premises PostgreSQL cluster. This post uses the same C360 pattern again, with AtScale as the semantic layer.

AtScale takes a different shape from the first two. The semantic model is dimensional (dimensions, hierarchies, and measures) rather than a graph of triples or a set of views. AtScale authors the model in the Semantic Modeling Language, an open, YAML-based specification versioned in Git, and exposes it simultaneously, from a single deployed model, over three protocols: SQL, XML for Analysis (XMLA), and the Model Context Protocol (MCP). The Strands...

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