Evaluating and Improving Performance of Agentic Systems with Snorkel.AI

GenAI systems are evolving beyond basic information retrieval and question answering, becoming sophisticated agents capable of managing multi-turn dialogues and executing complex, multi-step tasks autonomously.

However, reliably evaluating and systematically improving their performance remains challenging. In this session, we'll explore methods for assessing the behavior of LLM-driven agentic systems, highlighting techniques and showcasing actionable insights to identify performance bottlenecks and to create better-aligned, more reliable agentic AI systems.

To ground this talk, we will showcase a brief demo – aligning auto evaluators with SME judgment for agentic evaluation.