Use cases· Last updated

Ecommerce audit trail with Jev

Catalog copy, reviews, and promo banners need a keep / edit / hold decision before they go live. Recs, search rank, and inventory still own merchandising math. Jev judges language against your policy excerpt. It does not set prices or personalize a homepage.

This unofficial page is the audit trail slice of the ecommerce merchandising decisions pack. Intent: apply the Jev (TypeSafe System One) decision model to ecommerce merchandising decisions audit trail. Primary search language: Ecommerce 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): Claim/policy + merchandising action on catalog text — not a clone of a personalization-engine sitemap or recs API landing page.

Ecommerce use-case context

An audit trail for ecommerce merchandising decisions is a decision trace: replayable inputs, typed answers, floors, and the action the catalog gate 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: ecommerce personalization.

Audit Trail inputs

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

{
  "item": { "id": "sku-88", "title": "Lose 10kg tea", "bullets": "Guaranteed results in 7 days." },
  "policy": { "health": "No absolute health outcomes.", "stock": "Do not claim in-stock if inventory_flag is false." },
  "flags": { "inventory_flag": true, "locale": "en" }
}

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 action.

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

Guardrails and escalation

If you cannot explain publishing customer-visible copy or a live promo 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 ecommerce merchandising decisions, treat publish as the high bar (publishing customer-visible copy or a live promo). Tune on labels — see offline evaluation.

Evaluation and rollout notes

Traces are the eval warehouse. Replay against publish/hold gold from merch+legal, plus claim_risk gold 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 Ecommerce pack? Start with Ecommerce human handoff and Ecommerce evaluation. Cluster hub: Use cases.

Will Jev personalize the homepage? No. Recs stay in your personalization stack. This pack gates language.

Can we send product images? Not to System One. Transcribe claims. Images are not accepted.

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.