Use cases· Last updated

HR audit trail with Jev

Inbound applications and tickets mix eligibility, policy questions, and messy free text. The ATS, payroll, and your employment counsel still own outcomes. Jev can score job-related criteria you wrote. It is not an ATS and must not become a proxy for protected-class decisions.

This unofficial page is the audit trail slice of the HR screening operations pack. Intent: apply the Jev (TypeSafe System One) decision model to HR screening operations audit trail. Primary search language: HR Jev audit trail. 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): Job-criteria Nouls with an explicit do-not-encode-protected-class lint — not a clone of an ATS or HR-screening product page.

HR use-case context

An audit trail for HR screening operations is a decision trace: replayable inputs, typed answers, floors, and the action the screening worker took. It is not a chat log and not a clone of a SIEM product page.

Hub: Use cases. Compare, when the other tool is the real job: HR screening.

Audit Trail inputs

Persist the filtered payload (the contract), not whatever arrived at the edge:

{
  "app": { "id": "c-190", "text": "5 years Python; no work auth mentioned; relocating July." },
  "role": { "must": "Python in production; authorized to work without sponsorship this cycle." },
  "ticket": { "type": "inbound_app" }
}

Redact secrets before the object hits cold storage.

Decision signals and actions

Minimum fields:

Also store usage.input_tokens (vendor meter) and the full probabilities map — argmax-only logs cannot explain a close screen.

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

Guardrails and escalation

If you cannot explain auto-rejecting a candidate or taking employment action from the trace, you are not ready to auto-act. TypeSafe’s confidence-gated examples use a lower bar for recoverable reads than for irreversible actions. Those numbers are illustrations. For HR screening operations, treat auto_reject as the high bar (auto-rejecting a candidate or taking employment action). Tune on labels — see offline evaluation.

Evaluation and rollout notes

Traces are the eval warehouse. Replay against screen gold from recruiters, work-auth gold, and whether a human would have held docs after criteria or alias changes. 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

Slice Page
Graph and primitives decision workflow
What may enter state input contracts
What to gather first evidence collection
Atomic rules policy checks
Act / review / abstain confidence thresholds
Reviewer payload human handoff
What to persist you are here
How it breaks failure modes
Labeled replay evaluation
Shadow → canary production rollout

FAQ

Is the HTTP log enough? No. Persist the filtered state, full probabilities, floors, and downstream action as a decision trace.

May I log raw secrets? Redact in code. Jev will not be your DLP layer.

Where is the rest of the HR pack? Start with HR human handoff and HR evaluation. Cluster hub: Use cases.

Is this an ATS or hiring decision system of record? No. It is an unofficial typed-screening pattern. Employment law stays with you and counsel.

Can we score “culture fit”? We recommend you do not. Keep criteria job-related and lint for proxies.

What this page does not claim

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.

Sources

Public TypeSafe or adjacent documentation only. No private claims.