The 3-step guide to configure, control, and evaluate your AI support agent

About the webinar

When an AI support agent handles a customer conversation, most operators have no systematic way to review what it actually did: which actions it took, whether it stayed within the boundaries it was given, or whether the customer's issue was resolved. The standard metrics, containment rate and CSAT, do not capture what happened inside the conversation.

This session is a practical walkthrough of three things that address that directly.

What you will take away

— Why visibility into what your AI agent is doing matters

An AI agent handling hundreds of conversations a day makes autonomous decisions on every call. Without a way to see what it did, cost overruns, experience failures, and compliance breaches accumulate before anyone catches them.

— Three steps to get that visibility

Configure guardrails before the agent handles a single conversation. Maintain full visibility of every action it takes mid-call. Score 100% of conversations after, not a sample, with an explanation behind every score.

— What needs to be in place for this to work

All three steps require the configuration layer, the conversation layer, and the scoring layer to operate as one system. When they are separate tools, the intelligence cannot flow between them and the loop breaks.

Speakers

Sumeet Khullar

Co-founder & CTO @ Level AI

Rob Dwyer

CX Executive in Residence, Sr. Technical Account Manager @ Level AI