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Use Case

Churn Signal Monitoring

Surface accounts showing real disengagement signals before they cancel, instead of finding out after.

The problem

By the time a customer cancels, the warning signs (usage drop, support complaints, missed renewals) were visible weeks earlier — nobody was watching for them.

How we'd approach it

Usage and engagement data from your existing tools is monitored for defined risk signals, surfacing at-risk accounts to your team early enough to actually act — not a black-box churn-probability score.

Typical stack

Python / FastAPI,n8n,Supabase

FAQs

Is this a churn-prediction AI model?

No — it's rule-based monitoring of signals you define (usage drop, support complaints, missed renewals), not a black-box probability score. You can see exactly why an account was flagged.

Have a project in mind?

Tell us what you're trying to automate or build — we'll reply with next steps, not a sales pitch.