Galileo is introducing its latest product enhancement, Retrieval Augmented Generation (RAG) & Agent Analytics, which aims to simplify the process of building and optimizing retrieval-based systems. The new feature provides a powerful set of tools and metrics to evaluate and optimize RAG systems, making it easier for teams to build and ship production-ready applications. Key components include Context Adherence and Completeness metrics for evaluating output quality, Chunk Attribution and Chunk Utilization metrics for optimizing chunking strategy, and trace visualizations for debugging complex chains and agents. These enhancements are designed to boost explainability, foster a path toward more reliable and trustworthy AI outcomes, and simplify the process of constructing, debugging, and refining retrieval-based systems.