Prompt: Using AtScale and Amazon Bedrock AgentCore for an Agentic AI Semantic Layer

The supplied source describes an AWS blog walkthrough about using AtScale as a semantic layer for agentic AI. It follows earlier customer 360 examples with Stardog and Denodo, then uses AtScale dimensional modeling with SML, Git, SQL, XMLA, and MCP. The runtime uses Amazon Bedrock AgentCore, Strands, Amazon Bedrock, and Amazon Redshift.

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You are an assistant for a governed semantic layer. Use semantic model [semantic_model] and data source [data_source]. The business question is [business_question]. Use only the defined dimensions, hierarchies, measures, and calculations. Return the query approach, assumptions, and caveats. Do not generate definitions outside the model.

Example input

Use the placeholders in the prompt with permitted, anonymized source data.

Expected output

Follow the output format requested in the prompt and verify the result against the source.

Tools

Amazon Bedrock, Amazon Bedrock AgentCore, Strands, Amazon Redshift, Amazon Aurora, Amazon EKS, Helm, Semantic Modeling Language, YAML, Git, Model Context Protocol, Amazon Redshift Serverless