Evaluating LLM-based chatbots: A framework for reliable AI assistants

Write your awesome label here.

Learn a practical framework to build test cases, choose metrics, set regression tests, and add guardrails to make LLM-powered chatbots reliable, safe, and less prone to hallucinations. This webinar also covers live monitoring strategies to make your chatbot reliable.

Chatbots powered by large language models can either delight or frustrate users depending on how reliably they handle conversations. In this session, Lena Shakurova, Founder of ParsLabs and Chatbotly, and Willem Don, Conversational AI Trainer at CDI, will walk you through a practical framework for making conversational LLMs production-ready.

You’ll learn how to build effective test cases, choose the right metrics to compare prompt versions, and set up regression tests so you can release chatbot updates with confidence. The session will also cover how to add guardrails to block harmful or irrelevant responses and reduce hallucinations, along with strategies for live monitoring and log analysis to catch failures and continuously improve performance.

Expect concrete examples using Python and chatbot platforms, giving developers, AI engineers, and conversation designers actionable tools to deploy and maintain reliable conversational AI systems at scale.

What you’ll learn:

How to build test cases that reveal weak points in LLM behavior.
Choosing metrics that accurately reflect performance and reliability.
Setting up regression tests to safely deploy chatbot updates.
Adding guardrails to minimize hallucinations and harmful outputs.
Live monitoring and log analysis strategies to continuously improve performance.

Why attend?

Even advanced LLM chatbots can fail users if they’re not tested and monitored effectively. Many teams rely on intuition or ad hoc evaluations, which makes it hard to track improvement or maintain reliability.

This webinar gives developers, AI trainers, and conversation designers a structured approach to evaluate chatbot quality, deploy updates safely, and ensure your assistants remain stable, transparent, and trustworthy over time. You’ll leave with practical, actionable frameworks and real-world examples you can apply immediately.

Lena Shakurova is the founder of ParsLabs, a Conversational AI agency, and Chatbotly, a no-code platform for building AI assistants trained on custom data.

At ParsLabs, she leads a team blending AI, user research and conversation science to design and develop high-quality AI Conversations that sound more human. She has a background in NLP and Artificial Intelligence and 7+ years of experience, and 100+ successful projects building production-ready chatbots and voice assistants.

Lena focuses on ethical, user-first AI, leveraging her expertise in Linguistics & AI to create responsible, high-quality AI solutions. She shares insights on AI innovation and human-centred design through her blog and LinkedIn.

Willem Don has a strong background in content creation and editorial work. With experience in companies such as ABN AMRO Bank, Vodafone, and CDI Services, Willem has specialized in developing and optimizing AI assistants and chatbot content. Willem's expertise includes training NLP models, analyzing performance metrics, and driving continuous optimization. Alongside their professional roles, Willem has also been involved in editorial positions for various organizations and magazines. Willem holds a Bachelor's degree in Journalism from Windesheim.