Why Evaluation is the Key to Scaling Generative AI

Building generative AI projects in enterprise environments requires a strong evaluation strategy, as emphasized by AI leaders like Greg Brockman and Rishabh Mehrotra. The process involves four key stages: assessing the use case potential, building a functional MVP, iterating and scaling the product, and deploying to production. While many teams can reach the second stage, they often struggle with the complexities of the third stage, such as ensuring model reliability and measuring improvements. This difficulty arises from a mismatch between evaluation techniques and project stages, highlighting the need for evolving evaluation approaches. Galtea provides solutions by offering automated testing, scoring mechanisms, and traceability to help teams transition their generative AI projects from MVPs to production with confidence.