Announcing Galileo Autotune: Your Evals Are Wrong 20% of the Time. Now They Improve Every Time You Look.

Galileo Autotune is a tool designed to streamline and enhance the evaluation process of AI applications by addressing the common pitfalls associated with traditional manual tuning of LLM-as-judge evaluators. These evaluators often struggle with domain-specific nuances, leading to discrepancies between automated scores and human judgment. Autotune enables domain experts to directly correct evaluation scores, providing reasoning without the need for prompt engineering expertise, thus allowing for an automatic and iterative refinement of evaluation prompts. This approach combines all feedback into a comprehensive rewrite of the evaluation rubric and instructions, significantly improving alignment with human judgment and reducing errors. The system not only retains all corrections without limitations but also provides a transparent interface for managing and validating changes before they go live. Testing has shown substantial improvements in evaluation metrics, demonstrating the system's ability to deliver professional-grade results with minimal examples, and showcasing its broad applicability across various output types and scenarios. Autotune's integration into the Galileo platform makes it accessible for users to refine LLM-powered metrics, bridging the gap between human expertise and automated evaluation systems efficiently.

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