Summary

This article discusses the construction of a semantic layer on AWS using Stardog's Semantic AI Application integrated with Amazon Aurora and Amazon Redshift. It highlights the importance of a semantic layer in enabling AI agents to reason over fragmented enterprise data without the need for ETL processes. The article also covers the architectural components necessary for implementing agentic analytics, including the model layer, meaning layer, and agent runtime layer, while providing a practical example of a customer 360 agent that utilizes this semantic layer.

💭 Your Thoughts

What the Graph storing: The ontology captures the concepts, relationships, attributes and rules that matter to your business. stable identifiers for every entity, and rules that derive new facts, and constraints that validate the data against the ontology

Data Problems Addressed

Technologies Referenced