Description

Conversational AI systems are becoming increasingly complex, integrating multiple channels, languages, and use cases. Traditional testing approaches often struggle to keep up with this dynamic environment, leading to gaps in quality, scalability, and reliability. In this session, we will explore how Retrieval-Augmented Generation (RAG) combined with AI Agents can revolutionize the way conversational interfaces are tested in a continuous delivery pipeline. Attendees will learn how RAG-enabled agents can automatically generate, execute, and evaluate test cases, adapting to evolving conversational contexts.