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Jev Structured Decision Engine (SystemOne)
x402
Jev Structured Decision Engine (SystemOne) is a paid API for AI agents from sol.mapleai.shop, paid per call via x402, $0.001604/call, status unknown (last checked 2026-09-28).
Analyzes a described state and returns structured answers to named questions using typed decision categories (yes/no/null, choice, or score)
Price / call$0.001604
Success—
StatusUnknown
How this service works
Jev structured decisions via SystemOne, priced by input tokens
Output
Returns structured answers keyed to each named question: noul questions return yes/no/null, choice questions return a selected label from the defined options, and score questions return a numeric value. All keyed by the question names provided in the request.
Example use cases
Customer support ticket triage
“I have an incoming support message: 'My order never arrived and I was charged.' Can you run it through Jev and answer these: is it a billing issue (yes/no/null), is it a delivery issue (yes/no/null), and give it a priority score from 1 to 10?”
Content moderation decision
“Use Jev to evaluate this user report: 'This post contains a photo of someone without their consent.' I need to know: does it violate privacy policy (noul), what category of violation is it — privacy, harassment, or spam (choice), and how severe is it scored 1 to 10?”
Lead qualification scoring
“Run this sales lead description through Jev: 'The prospect is a mid-size SaaS company with 200 employees looking to replace their CRM next quarter.' Answer: is the budget likely above $10k (noul), which segment does it fit — SMB, mid-market, or enterprise (choice), and score the overall lead quality from 1 to 10.”
Technical details
Endpoint
POSThttps://sol.mapleai.shop/jev?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need structured, typed answers from an unstructured text description — especially when you need a mix of binary (yes/no/null), categorical (choice), and numeric (score) outputs in a single call. It is purpose-built for decision automation workflows like triage, classification, and qualification rather than open-ended text generation. Prefer it over general chat completions when you need machine-readable structured outputs without post-processing.
Side effects
- Invalid question type enum (must be noul, choice, or score) causes validation error
- Missing required 'state' or 'questions' fields returns 400 bad request
- Empty questions object may return empty results without error
- Ambiguous or very short state descriptions may yield low-confidence or null answers
- Payment failure (insufficient USDC) blocks the call with 402 response
- Malformed question instructions may produce unexpected classification behavior
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | |
| state | string | |
| questions | object | Named questions. Each value needs type (noul, choice or score) and instructions. |
Tags
x402
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