Evaluation Framework for Generative AI Applications

This white paper presents an Evaluation Framework designed for enterprises to assess the performance of Generative AI (GenAI) applications. It outlines the necessity for a unified approach to evaluate GenAI-enhanced applications, which utilize both structured and unstructured data. The framework employs both black box and white box testing methodologies to evaluate the performance of these applications. It emphasizes the importance of developing sophisticated metrics tailored to GenAI applications, as traditional metrics may not adequately reflect the quality of generated responses. The document details the creation of test data, including various question types, to evaluate application performance from multiple perspectives. Additionally, it discusses the integration of diverse data types, including text, structured data, and graph data, into the evaluation process. The framework also introduces metrics for assessing agentic workflows, providing insights into the operational performance of GenAI applications. Overall, the Evaluation Framework aims to enhance the reliability and accuracy of GenAI applications in enterprise settings.