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Capability overview — prioritization
Retention risk scoring
Customer churn risk scoring
Score individual accounts from structured fields (Telco-style schema): JSON in, churn probability plus coarse risk tier out—suited to trials where teams want ranked follow-up, not a replacement for CRM strategy.
Use Open scoring demo (API) on churn-api for the full interactive UI. Governance caveats still apply.
Python
scikit-learn
FastAPI
Docker
Limitations & scope
- Demonstration training uses the public Telco Customer Churn dataset; useful scores on your accounts require retraining and validation on your own labeled data.
- The HTTP API exposes POST /predict with one JSON record per request. There is no server-side CSV upload or batch queue in this codebase.
- Risk bands (high / medium / low) use fixed probability cutoffs for UI grouping; the binary churn label uses a threshold read from training outputs (see metrics).
- The published Docker image is inference-only: you mount a trained joblib artifact plus metric files from the training pipeline (see README).
- Risk bands do not encode business cost matrices or uplift models.
Try the scorer
The interactive demo (metrics strip, findings, model chart slot, customer form) lives on churn-api — same presentation as the shipped Vercel-style demo; this labs page stays positioning-only.
Production fit and integration remain separate from what you see in the browser.