Call quality,
made clear.
Call insight
Illustrative workflowCustomer10:02 AM
Hi, I wanted to check on my delivery. It was scheduled for Thursday.
AI agent10:03 AM
I see it’s scheduled for Thursday, and I can confirm it’s still on track for that day.
Quality evidence
- Clear and accurate information“I can confirm it's still on track for that day.”
Evidence-linked QA
A score is only useful when you can explain it.
The same quality standards should apply to calls handled by people and by AI agents. AI calls add checks of their own: did the agent say it was automated, stay within its tasks, and complete the actions the customer agreed to?
Read: a scorecard for human and AI callsQuality criteria
- Provides accurate information
- Resolves the customer's need
- Follows process
- Professional and empathetic
- Clear next steps
Transcript and evidence
Illustrative workflowAI agent10:05 AM
Of course. I’ve updated your delivery address, and you’ll get a confirmation by email.
Customer10:05 AM
Perfect, that's all I needed. Thanks!
Meets criterion: Resolves the customer's need
The agent completed the address change, and the customer confirmed nothing else was needed.
What good QA needs
Scores that hold up to review.
- Evidence for each criterionThe transcript moments that support, or don’t support, each result.
- A review stepA way to confirm or correct results, and to settle disputes by looking at the call itself.
- Human and AI callsOne set of standards for calls handled by your agents and by AI agents.
Reporting by client
Each client measured on its own standard.
- Results by client and campaignPerformance against each client’s own scorecard, kept separate from other programs.
- The calls behind the numbersTranscript, actions and outcome for each scored call.
- Coaching opportunitiesWhere agents missed a criterion, alongside what went well.
Review, evidence, coaching
- 01
Review the conversation
Start from the full transcript, with quality notes in context. - 02
Find the evidence
Check each criterion against the moments that support, or don't support, the result. - 03
Coach the next call
Turn findings into clear, practical coaching for each agent.
Agent coaching
Agent coaching built on call evidence.
Give agents clear, evidence-based coaching that builds skills and confidence, and resolve disputes by looking at the moment in the call.
Talk to sales about coachingCoaching insight
Illustrative workflow- What went wellThe agent gave a clear, accurate update and resolved the customer's request.
- Coaching opportunityConfirm the new address back to the customer before closing.
- Suggested coaching focusRead-back of changed details on delivery calls.
From QA to coaching
How agent coaching works after the call.
- 01
Score the call
Review the call against your scorecard, with transcript evidence for every criterion. - 02
Find the opportunity
Criteria an agent missed become coaching opportunities, alongside what went well. - 03
Choose a focus
Repeated misses across an agent’s calls suggest one coaching focus instead of a list of faults. - 04
Check later calls
Review later calls on the same criteria to see whether the focus is holding.
AI agents need the same review. For an AI caller, a missed criterion points to its instructions, and any change to those should be approved by an authorized person. How we think about approved changes
Agent coaching reading
Agent Performance
AI-Powered Coaching: Turn Call Findings Into Better PracticeTurn call QA findings into specific coaching tasks, reviewed examples and follow-up checks. Separate human training from controlled AI-agent changes.
Agent Performance
AI-Powered Agent Training From Call EvaluationsBuild a weekly human-agent training loop from verified call findings, focused practice and follow-up reviews. Keep AI-caller changes on a separate release path.
Agent Performance
Real-Time AI Coaching for Call Agents: A Buyer's GuideEvaluate live coaching prompts for human call agents: useful scenarios, latency, distraction, evidence quality and differences from AI calling and post-call QA.


