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Catch churn early

Detect churn before clients decide to leave

34% churn rate with no early warning? Our AI analyzes transcripts, scores client health Red/Yellow/Green, and alerts your team before it's too late.

Where it breaks today

No early warning system. No historical trend analysis. Your team only learns about at-risk clients when it's too late to save them. You find out about churn after they've already decided

The fix

We analyze every interaction and flag risk signals before clients make the decision to leave.

What we build

An agent is a stack.

01

Transcript health analysis

AI analyzes coaching transcripts using C3 health methodology. Every session scored automatically.

  • Automated transcript analysis
  • C3 health scoring methodology
  • Red/Yellow/Green client ratings
  • Historical trend tracking
Core
02

Real-time risk alerts

High-risk signals trigger immediate Slack notifications. Your team acts while there's still time.

  • Slack notifications for high-priority risks
  • Negative trend detection across sessions
  • Risk flag categorization
  • Team-specific alert routing
Module

How it works

Analyze. Score. Alert.

01

Connect your data

Integrate with BigQuery and Slack. We ingest transcripts automatically.

Step 1
02

AI scores every client

Health scoring applied to every interaction. Trends tracked over time.

Step 2
03

Your team acts on alerts

Real-time Slack alerts for at-risk clients. Your team intervenes early.

Step 3

What it delivers

Outcomes, in weeks.

Churn detected before client decides
Historical trends tracked automatically
Real-time alerts via Slack

Before → After

Detection after decision to leave

Detection before client decides

Before → After

No trend visibility

Historical momentum tracked

Before → After

Proactive intervention: None

Real-time Slack alerts

No lock-in

Built in your stack.

Live in 4-6 weeks. You own the system — sovereign, no vendor lock-in.

  • Data Warehouse (BigQuery, Snowflake, Redshift, or custom)
  • Team Communication (Slack, Teams, or your tool)
  • Runtime & Orchestration (Trinity by Ability AI)

Questions

Questions about churn prevention

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?

Mid-market companies typically see 3-5% churn reduction in the first year. For a company with $5M ARR and 34% churn, preventing 5% of churn = $85K retained revenue. System pays for itself in 60-90 days.

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.

Start here

Bring one workflow.

A 30-minute working call. We’ll map this workflow to an agent stack and tell you honestly whether it’s worth building.

Churn prevention engine

Early warning before churn

Detect churn risk before clients decide to leave. AI-powered health scoring with real-time alerts.