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

The article details how to construct a customer‑360 semantic layer that spans Amazon Redshift and Amazon Aurora using Strategy Mosaic. The layer is then exposed to a Strands agent running on Amazon Bedrock AgentCore via the Mosaic MCP server, enabling end‑to‑end per‑user row and column security. This integration allows an agent to query the unified view securely without exposing raw database schemas. The approach demonstrates a practical method for combining relational data sources with Bedrock’s agentic capabilities while maintaining strict data‑access controls.

⚡ Key Takeaways

• The semantic layer aggregates data from Amazon Redshift and Amazon Aurora into a single customer‑360 view.
• Strategy Mosaic’s MCP server serves the unified schema to a Strands agent on Amazon Bedrock AgentCore.
• Row‑level and column‑level security policies are enforced across the entire pipeline, ensuring per‑user data isolation.
• Integration requires configuring Mosaic MCP to expose the semantic layer via Bedrock AgentCore’s API endpoints.
• WhyItMatters: Engineers building production AI systems can now layer semantic abstractions over heterogeneous data stores and expose them to Bedrock agents, simplifying data access while preserving security.
• TechnicalLevel: Intermediate
• TargetAudience: ML Engineers
• PracticalSteps:
• Set up Strategy Mosaic to ingest and unify data from Amazon Redshift and Amazon Aurora.

Engineers building production AI systems can now layer semantic abstractions over heterogeneous data stores and expose them to Bedrock agents, simplifying data access while preserving security.

✅ Practical Steps

1. Set up Strategy Mosaic to ingest and unify data from Amazon Redshift and Amazon Aurora.

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