How to trust LLMs in production

Unlike traditional software, LLMs don’t break loudly. Ensuring that AI applications behave as intended requires continuous monitoring and evaluation of their outputs. LLM evaluation is more nuanced than traditional QA testing, as it requires defining what good looks like for a specific use case and turning that into a systematic, repeatable process. In this Power Pause webinar hosted by Brillian, Lead AI Architect Samuel Rönnqvist and CEO & Co-founder Jussi Järvinen explore how to evaluate LLM quality over time, assess when an AI application is ready to ship and keep its outputs aligned with user intent.