Sales evidence collection with Jev
Opportunity stage and quote PDFs live in the CRM. Jev can set a picklist from unstructured notes: is this a next-step, a risk, a closed-won hint, a discount promise that violates policy? Workflows fire after the field write. Jev does not host the Opportunity.
This unofficial page is the evidence collection slice of the sales note labeling pack. Intent: apply the Jev (TypeSafe System One) decision model to sales note labeling evidence collection. Primary search language: Sales Jev evidence collection. 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): CRM owns objects and SLAs; Jev labels messy call/email notes (next step, risk, discount-policy). Weighted scores stay in code — apply the composite-scoring win (not a Salesforce-IA or lead-score recipe clone). Fan-out extra atoms on one request; open a second HTTP call only for a new artifact, not the same state.
Sales use-case context
Evidence collection for sales note labeling happens before POST /v1/systemone. Jev does not browse your warehouse, retriever, or ESP. You gather the call or email note + policy excerpt facts, filter them, then ask snap questions. This slice is where fan-out cost math belongs: batch questions, do not re-send state.
Hub: Use cases. Compare, when the other tool is the real job: CRM workflows.
Evidence Collection inputs
Collect:
- The note text
- Stage + discount cap you already store on the Opp
- Percents extracted in code when present
Never send:
- Asking Jev to recompute forecast math
- The whole MEDDIC workbook as distractors
- Personal emails unrelated to the Opp
Shape the payload like this once the gather step finishes:
{
"note": { "id": "N-88", "text": "CFO asked for 30% off if we sign this week. Legal still redlining DPA." },
"opp": { "stage": "negotiation", "list_discount_cap_pct": 15 },
"policy": { "discount": "Promises above list_discount_cap_pct need deal-desk, not AE verbal." }
}Decision signals and actions
Each evidence field should change a named answer:
| Id | Type | Job |
|---|---|---|
label |
Choice | next_step / risk / closed_hint / discount_promise / other |
next_step_clarity |
Score | How concrete is the stated next step? |
discount_violation |
Noul | Does the note promise a discount above the cap language (compare the number in code)? |
label + clarity + discount_violation in one call. If you also composite ICP/intent Scores, do that on the lead-scoring pack — weights in app code.
Do not treat a Noul of 0.5 as a “medium” sales note labeling score — it means yes and no are equally likely. Conjunctions stay in your code.
Guardrails and escalation
If the gather step fails (empty call or email note + policy excerpt, redaction stripped everything, retriever empty), fail closed on paging deal-desk or sending a customer quote change. Do not invent evidence so Jev has something to say. TypeSafe’s confidence-gated examples use a lower bar for recoverable reads than for irreversible actions. Those numbers are illustrations. For sales note labeling, treat page_deal_desk as the high bar (paging deal-desk or sending a customer quote change). Tune on labels — see offline evaluation.
Evaluation and rollout notes
Your eval set should include thin-evidence cases, not only happy call or email note + policy excerpts. Label label gold from managers, plus off-policy-discount gold. 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 | you are here |
| Atomic rules | policy checks |
| Act / review / abstain | confidence thresholds |
| Reviewer payload | human handoff |
| What to persist | audit trail |
| How it breaks | failure modes |
| Labeled replay | evaluation |
| Shadow → canary | production rollout |
FAQ
Should evidence live in the question text?
Put facts in state and point instructions at note.text, policy.discount, opp.stage. Criteria stay stable so you can replay.
When do I split calls? label + clarity + discount_violation in one call. If you also composite ICP/intent Scores, do that on the lead-scoring pack — weights in app code.
Where is the rest of the Sales pack? Start with Sales input contracts and Sales decision workflow. Cluster hub: Use cases.
Is this the same as lead scoring? No. Lead scoring composites ICP/intent Scores. This pack labels notes on an existing Opp. Link them; do not merge slugs.
Can Jev update Amount? Not from language alone. Extract numbers in code; CRM math stays in the CRM.
What this page does not claim
- Not a CRM or CPQ product.
- No invented pipeline lift.
- 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.
Sources
Public TypeSafe or adjacent documentation only. No private claims.