Test the conversation your customers will actually have.
Build an evaluation set around the real customer task, the business action, and the human boundary. Review what the agent says, what it does, and how the complete interaction behaves under difficult conditions.
A repeatable acceptance process for a customer-facing voice workflow.
Know what moved forward.
Evaluate the business task
Define the evidence that proves the request was handled accurately in the connected system.
- Correct answers and required information
- Permitted actions with confirmed results
- Appropriate human escalation
Evaluate the voice experience
Use realistic audio and customer behavior to test the conversation beyond the written transcript.
- Interruptions, silence, and unclear speech
- Language, names, and domain vocabulary
- Response timing and recovery
Evaluate operational boundaries
Include the failures that can change what the agent is allowed or able to do.
- Provider and tool failures
- Authentication and consent conditions
- Recording, context, and handoff behavior
From a conversation
to a completed task.
Connect the steps that make the outcome possible.
- 01
Write acceptance rules first
Choose one workflow and define required outcomes, unacceptable actions, escalation triggers, and response-time measures before running evaluations.
- 02
Build a representative scenario set
Cover routine requests, ambiguous inputs, every consequential branch, language variation, and dependency failures. Preserve the configuration and expected outcome for each case.
- 03
Review and retain the evidence
Compare task results, action accuracy, handoff quality, response-time distributions, and cost. Turn observed failures into regression cases and rerun them when relevant configurations change.
Make it useful
in your business.
Start with a specific conversation, connect the right systems, and define what a successful outcome looks like.
Pre-launch acceptance
Provider configuration changes
Agent version review
Production quality improvement
Can an automated judge make the final decision?
Use automated grading to support repeatable review, with explicit rubrics and sampled human checks. Review consequential errors against source evidence and the workflow’s acceptance rules.
Which latency should we measure?
Define the start and end events for each measure, such as end of customer speech to audible response. Inspect the distribution and slow cases rather than relying on a single average.
When should the evaluation set change?
Add cases when new workflows, languages, tools, or observed failures introduce meaningful behavior. Keep previous relevant cases so improvement in one area does not conceal a regression elsewhere.
Keep exploring.
Make the next release better than the last conversation.
Turn production conversations into tests, evaluate the voice experience and compare agent changes before publishing. Give quality a repeatable workflow that includes knowledge, actions, timing and handoffs.
Explore productConversation IntelligenceSee what conversations accomplished—and what needs attention.
Bring call history, customer signals, operational performance and costs into one review loop. Understand which agents complete useful work and where customers still need help.
Explore productHuman handoff scorecardJudge a handoff by what the next person can do.
Use this scorecard to review whether an AI-to-human transfer preserves context and reaches an accountable owner. Evaluate the complete transition, including the caller’s expectations and the destination’s ability to act.
Explore resourcesGive every conversation
somewhere better to go.
Start with one agent. Build an operation around what works.