Solution · Customer support
Detect churn before clients decide to leave
No early warning before a client leaves? The department reads every session transcript, scores client health Red/Yellow/Green, and alerts your team while there is still time to act.
Delivers
- Churn detected before client decides
- Historical trends tracked automatically
- Real-time alerts via Slack
Time to live4-6 weeks
Where it breaks
You find out about churn after they've already decided
No early warning system. No historical trend analysis. Your team only hears about at-risk clients when it's too late to save them.
The fix
We analyze every interaction and flag risk signals before clients make the decision to leave.
- Detection after decision to leaveDetection before client decides
- No trend visibilityHistorical momentum tracked
- Proactive intervention: NoneReal-time Slack alerts
What we build
An agent is a stack.
2 capabilities working as one, built in your customer support stack.
- Automated transcript analysis
- C3 health scoring methodology
- Red/Yellow/Green client ratings
- Historical trend tracking
- Slack notifications for high-priority risks
- Negative trend detection across sessions
- Risk flag categorization
- Team-specific alert routing
How it works
Analyze. Score. Alert.
- Step 01Connect your dataIntegrate with BigQuery and Slack. We ingest transcripts automatically.
- Step 02AI scores every clientHealth scoring applied to every interaction. Trends tracked over time.
- Step 03Your team acts on alertsReal-time Slack alerts for at-risk clients. Your team intervenes early.
Under the hood
Plugs into your stack.
Churn prevention engine works inside the tools your team already uses, on infrastructure you own. Typically live in 4-6 weeks.
- Data Warehouse (BigQuery, Snowflake, Redshift, or custom)
- Team Communication (Slack, Teams, or your tool)
- Runtime & Orchestration (Trinity by Ability AI)
Time to live4-6 weeks
Agents in Customer support
Ready-made agents for this department.
Questions
Before you ask.
What data does it analyze?
Coaching transcripts from BigQuery. The AI applies C3 health analysis methodology to score every session.
How fast are alerts?
Real-time. When a high-risk signal is detected, your team gets a Slack notification immediately.
What results should we expect?
Earlier warning: your team sees at-risk clients while there is still time to step in, with the transcript evidence quoted. What that is worth depends on your client base and how your team acts on the alerts, so we agree the measures with you before go-live.
How long does implementation take?
4-6 weeks from kickoff to production. Week 1-2: BigQuery integration and C3 methodology mapping. Week 3-4: Alert configuration and Slack setup. Week 5-6: Team training and validation.
Do we own the system?
Yes. You own the system. We build the infrastructure in your stack, hand over the keys, and you own it forever - no vendor lock-in.
Next step
Want this in your company?
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