Go beyond surface level analytics with smart suggestions based on real performance. Track call volume, resolution rate, and more, and get custom tips on how agents can increase performance.
Analyze tickets at scale
Every support ticket is ingested and structured for root-cause analysis
Test hypotheses
ChatGPT O3 finds root causes & verifies across dataset
Improve continuously
Verified hypotheses reveal measurable impact
Acme Co
Analytics
Dashboard
Tickets
Insights
Journeys
Agents
Agent Canvas
Knowledge
APIs
Mobile numbers
Intents
Custom fields
Review
Manual QA
Remaining memory
High
Last locked by
Internal system
Dev mode
Resolution Rate Improvement (Voice)
Voice
Today, 12:25 AM
Generate insights
Insights
Policy Modification
Fallback workflow
928 tickets were escalated because mark_order_as_delivered() returned “quota_exceeded.”. Adding a short, scripted fallback before transfer will let the AI resolve most of these cases without escalation.
928 tickets
-13.8% improvement
Delivery Resolution
Implementing retry mechanism
750 tickets faced delivery failures due to network timeouts. Introducing a retry mechanism for network issues will help recover deliveries and reduce escalations.
750 tickets
-2.2% improvement
Policy Modification
Add guided menu
60 tickets show guests saying only "operator/representative." Current policy forces three open-ended asks before an "unspecific" transfer, causing frustration and lost self-service opportunities.
167 tickets
-4.9% improvement
Resolution Rate Improvement (Voice)
Improvement Opportunity
+ 75%
35%
40%
10%
928
35%
Fallback workflow for quota
exceeded
431
40%
Automatic retry mechanism for failed requests
AI-generated optimizations that drive real ROI
Every workflow built from flexible, customizable policy blocks
HOW IT WORKS
Lightning-quick deployment
Day 1
Ingest
Parse past policies and transcripts; Copilot autogenerates ~90% of a draft
Day 3
Build
Use modular code and APIs to deliver a review-ready version
Day 6
QA Loop
Run manual QA; Copilot refines revisions into a release-ready policy
Day 9
Deploy and testing
Launch with 1% safe slice; logs and feedback guide final tweaks
Day 12
Scale-up & verify
Roll out to 100%, driven by KPI insights and ongoing refinement
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