RAG evaluation and testing: webinar and live demo

​RAG (Retrieval-Augmented Generation) is a popular technique that helps ground LLM outputs in up-to-date, relevant information. But how do you know if your RAG actually works well?

​If you’re building a RAG-powered chatbot or any complex system, you need to check two things:
✅ Can it find the right information?
✅ Is the final answer complete, relevant, and free of hallucinations?

​In this hands-on webinar, we’ll show you how to evaluate and test your RAG system — both during development and in production. You’ll learn:

​📈 How to measure both retrieval and generation quality
✅ Evaluation techniques — with and without ground truth
⚠️ Common pitfalls to watch out for
🔡 How to create and use synthetic data for testing
💻 Live demo: using Evidently for RAG evaluation

​Speakers:

​Elena Samuylova — CEO & Co-founder at Evidently AI, the company behind Evidently, an open-source framework for AI evaluation with 25+ million downloads.

​Emeli Dral — CTO & Co-founder at Evidently AI. She led over 50 applied ML projects for various industries: from banking to manufacturing. She is a data science lecturer at Harbour.Space University, and co-author of the Machine Learning and Data Analysis curriculum at Coursera with over 150,000 students.