Webinar – Lifting the Lid on AI Agents: Exposing Performance Through Evals

AI agents are beginning to transform industries from customer service to manufacturing, but understanding and improving agent decision-making remains a major challenge.

Agents often operate as black boxes, making tool selections — i.e., choosing which APIs, knowledge bases, or even other models to use — without clear reasoning. Traditional debugging methods fall short because we can’t fully decode these choices. Instead, we need to expose agent behavior through structured evaluations, using data-driven diagnostics to assess performance and refine decision-making.

Watch our webinar to learn:

• Why agent tool selection is opaque – How and why AI agents make decisions without explicit transparency.
• How to evaluate tool selection – Using systematic evaluations to understand both individual tool effectiveness and system-wide performance.
• Common pitfalls and real-world case studies – Where agentic workflows break down and how industries are applying these insights in areas like AI-driven customer support, autonomous research, and industrial automation.
• Ways to optimize decision-making through evaluation – How feedback loops, error tracing, and performance benchmarking drive continuous improvements.