Use cases· Last updated 2026-09-21

Churn confidence thresholds with Jev

Usage curves belong to your warehouse. Jev reads why someone is unhappy (cancel language, effort, save-offer fit). Code blends the two.

This unofficial page is the confidence thresholds slice of the churn risk decisions pack. Intent: apply the Jev (TypeSafe System One) decision model to churn risk decisions confidence thresholds. Primary search language: Churn Jev confidence thresholds. Confirm patterns on docs.typesafe.ai. This site does not sell, issue, or proxy TypeSafe keys. Use a credential you already have from the console or a documented gateway.

Independent angle (cover ≠ clone): Evidence-first risk bands from tickets and language, with arithmetic in code — not a black-box churn-model clone or rival recipe IA.

Churn use-case context

Thresholds turn churn risk decisions answers into act / review / abstain. They are product policy, not a hyperparameter TypeSafe ships. Official 0.5 / 0.9 sketches are illustrations. This slice also carries the false-reject discussion: over-gating churn risk decisions hides calibration.

Hub: Use cases. Compare, when the other tool is the real job: churn models.

Confidence Thresholds inputs

You need (1) pinned answers on a frozen contract and (2) labels for cancel-intent gold and whether the chosen save play was appropriate. State shape:

{
  "account": { "id": "A-12", "plan": "pro", "seats": 40 },
  "usage": { "wow_delta_bucket": "down_gt_30", "last_active_days_bucket": "21_plus" },
  "tickets": { "latest": "We are moving to a competitor unless SSO ships." },
  "nps": { "comment": "Setup took weeks." }
}

Decision signals and actions

FLOORS = {
    "csm_nudge": 0.55,      # illustrations — replace
    "exec_outreach_or_discount": 0.88,
}
NOUL_TAU = 0.75  # for cancel_intent

def allow(ans, action):
    return ans.confidence >= FLOORS[action]

Do not treat a Noul of 0.5 as a “medium” churn risk decisions score — it means yes and no are equally likely. Conjunctions stay in your code.

Guardrails and escalation

TypeSafe’s confidence-gated examples use a lower bar for recoverable reads than for irreversible actions. Those numbers are illustrations. For churn risk decisions, treat exec_outreach_or_discount as the high bar (exec outreach or a commercial concession). Tune on labels — see offline evaluation.

Band around 0.5 on cancel_intent always reviews. Do not copy 0.75 onto Choice confidence.

Evaluation and rollout notes

• Precision of exec_save pages
• Missed competitor-threat language
• Do not attribute revenue save to Jev without a designed experiment

Fit loop: pin jev-1.13.0 → replay → plot error vs confidence → pick floors where auto-act error ≤ your SLA. Pin jev-1.13.0 (the versioned id) after you fit thresholds. jev-latest and the marketing line jev-1.13 can move. Log the response model. TypeSafe’s published list price for jev-1.13 is $0.042 per million input tokens (vendor claim — confirm on the models page); output tokens are free on that same page. Unused distractors still bill as input.

Official Python and JavaScript SDKs read TYPESAFE_API_KEY and retry documented 429/529. This site does not sell, issue, or proxy TypeSafe keys. Use a credential you already have from the console or a documented gateway.

Pack map

FAQ

Should exec_outreach_or_discount use 0.9 everywhere? No. Over-gating hides calibration and dumps the queue on humans. Fit per action.

Can I reuse a Noul τ as Choice confidence? No. Jaggedness: they are not interchangeable. See confidence.

Where is the rest of the Churn pack? Start with Churn decision workflow and Churn human handoff. Cluster hub: Use cases.

Can Jev replace our churn model? No. Keep warehouse risk; use Jev on unstructured complaints and save-offer fit.

TypeSafe mentions churn in the use-case map — is that a product? It is an example of more questions on ticket state, not a separate TypeSafe churn API.

What this page does not claim

• No causal save-rate numbers.
• Not a billing system.
• Not official TypeSafe.
• Official TypeSafe status, or that jev.pro issues API keys.
• That a schema-constrained answer is automatically factually correct.

Disclaimer

This is an independent unofficial site and is not affiliated with TypeSafe AI; official documentation is available at https://docs.typesafe.ai.

Primary documentation: https://docs.typesafe.ai. Hub: Use cases.