How to Use Evaluation Pipelines to Build Smarter AI

Continuous improvement in LLM engineering requires a structured approach to evaluation, yet traditional testing methods often fall short when dealing with dynamic AI behavior. In this webinar, we’ll explore the fundamentals of evaluation pipelines—what they are, why they matter, and how they streamline testing for both deterministic and non-deterministic systems.

Through real-world examples, we’ll discuss how evaluation pipelines help with improving prompts, testing new techniques, and managing architectural changes. You’ll gain insight into the trade-offs between open-source, cloud-based, and custom-built evaluation frameworks and learn why we built versus bought. We’ll also share how Lumigo leverages evaluation pipelines to optimize our AI-powered Co-Pilot, from collecting the right test cases to defining meaningful metrics and integrating evaluations into CI/CD.

What You’ll Learn:

• How evaluation pipelines enhance LLM testing and continuous improvement.
• Key challenges in LLM engineering and practical solutions for overcoming them.
• The trade-offs between open-source, cloud-based, and custom-built evaluation frameworks.
• How to measure your LLM application and integrate evaluation to the development lifecycle