Virtual
In-person
Scaling evaluation systems for agentic platforms from prototype to prod
This webinar looks to develop strategies for mastering cost-effective AI agent evaluation at scale using stratified sampling, risk-based testing, and multi-stage screening to cut costs while maintaining enterprise-grade quality control.
This webinar will share key insights on AI agent evaluation and highlight how to:
- Cut evaluation costs through stratified sampling across personas and risk-based prioritisation, focusing resources on high-impact, high-variance scenarios rather than exhaustive testing.
- Build progressive evaluation systems using multi-stage screening that catches obvious issues cheaply, then applies deeper evaluation only where needed - balancing "vibes" for content vs rigorous testing for critical processes.
- Implement enterprise-ready observability with OpenTelemetry telemetry, persona coverage maps, and continuous calibration frameworks that adapt as your agentic platform scales and models evolve
