As enterprises deploy AI copilots, autonomous agents and multi-step workflows, ensuring reliability becomes increasingly complex. Unlike traditional AI systems, agentic architectures reason across multiple steps, invoke tools, and make decisions autonomously making failures harder to detect and evaluate with conventional testing methods. 

In this joint webinar, Arize AI and QualityKiosk explore how enterprises can embed continuous evaluation into their agentic AI ecosystems to ensure reliable outcomes.  

What we will cover:

1. Why Agentic AI Systems Fail in Production

 Common failure patterns in multi-step reasoning systems, tool misuse, decision drift, and compounding errors. 

2. Evaluate: Measuring Agent Performance at Scale 

Assessing task completion, reasoning consistency, and tool-use accuracy using offline tests and production traces. 

3. Observe: Understanding Agent Behavior in Production 

Tracing reasoning paths, tool calls, and workflow decisions to gain visibility into agent operations. 

4. Improve: Using Evaluation Insights to Strengthen Agents 

Refining prompts, tool orchestration, and guardrails based on evaluation signals. 

5. Live Demo: Evaluating an Agentic Workflow 

How Arize AI helps diagnose and improve agent performance. 

6. Enterprise AI Reliability Framework 

How QualityKiosk embeds evaluation into QA, SRE, and governance models for production AI systems. 

Register now and learn how organizations are moving beyond static benchmarks.