Build a semantic layer for agentic AI on AWS with Strategy Mosaic and Amazon Bedrock AgentCore
This post is co-written with Zhili Cheng, Principal Product Manager, George Earle, Director, AI Engineering, and Kyler K, Sales Engineer of Strategy. 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 and 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 Strategy Mosaic as the semantic layer. Stardog’s semantic layer is ontology-based: concepts and relationships modeled as RDF, with IRIs as the unit of federation and SPARQL as the query language. Denodo’s is data virtualization: base and derived views composed in VQL. Mosaic’s is dimensional: attributes, hierarchies, facts, and metrics composed through Strategy’s metric expression syntax, with linked mo…
Why it matters
This post is co-written with Zhili Cheng, Principal Product Manager, George Earle, Director, AI Engineering, and Kyler K, Sales Engineer of Strategy Reported by AWS Machine Learning on October 20, 2026.