# Jev System One – Typed Inference API (x402) > Jev System One – Typed Inference API (x402) is a paid API for AI agents from jev.agents.bakingbad.dev, paid per call via x402, $0.000014/call, status unknown (last checked 2026-10-02). Returns typed, structured answers (boolean probability, choice with confidence, numeric score) to arbitrary questions about a shared text context, billed per-call via x402/MPP with no API key required. ## Facts - Endpoint: POST https://jev.agents.bakingbad.dev/v1/systemone?utm_source=zero.xyz - Price: $0.000014/call - Payment: x402 - Status: unknown - Last checked: 2026-10-02 - Activations on Zero: 7 - Tags: x402 - Canonical page: https://www.zero.xyz/c/jev-system-one-typed-inference-api-x402-f31b4fa3 - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_v4SrvWma_3Shd_JGRJJQh Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently. ## How to call it through Zero Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`): ```sh zero fetch --capability jev-system-one-typed-inference-api-x402-f31b4fa3 -d '' ``` Example prompt: Using the jev-latest model, look at this support message — 'My payouts have been failing for 3 days and nobody has responded' — and tell me: is it urgent (yes/no probability), which department should handle it (billing, technical, or sales with confidence), and how frustrated is the customer on a 0-to-2 scale from Calm to Very Angry. ## When to prefer this Choose this endpoint when you need multiple typed answers (boolean, categorical, or numeric) about a single text context in one call, without managing an API key or subscription — especially in automated pipelines where pay-per-call micro-billing via x402 or MPP is preferred. It is particularly well-suited for structured classification tasks (routing, scoring, policy checking) where you want calibrated confidence scores alongside the answer, not just a free-text response. Prefer it over general-purpose LLM completions when you need machine-readable, strongly-typed output with explicit probability distributions. ## Known failure modes - Missing or invalid model name — service has no default and will reject the call - Payment not provided or insufficient — x402 payment required before inference proceeds - No questions provided — schema requires at least one entry in the questions map - Unsupported question type — only noul, choice, and score types are accepted - Malformed state — non-text inputs (images, audio, video) are not evaluated - Upstream model unavailable — demo/experimental service may be intermittently offline - Token limits exceeded — very large state or question sets may be rejected ## How this service works Experimental pay-per-call access to TypeSafe's Jev System One model through Baking Bad's paid service. Typed answers over x402 or MPP, no API key, demo use only. ## Output A JSON object containing the model version used, token usage (input and output counts), and an 'answers' map keyed by the caller's question IDs. Each answer carries its declared type: 'noul' answers include a 0–1 probability; 'choice' answers include the selected option, a confidence score, and a probability distribution over all options; 'score' answers include a numeric value, a legend mapping integers to labels, confidence, and a probability distribution. ## Request schema (JSON Schema) ```json { "type": "object", "properties": { "model": { "type": "string", "example": "jev-latest", "description": "Required model name or alias. Discover aliases with GET /v1/models; supported versioned IDs can be accepted even when not listed. The service does not insert a default." }, "state": { "anyOf": [ { "type": "string" }, { "type": "object" }, { "type": "array" } ], "example": "Help! My payouts have been failing for 3 days.", "description": "Shared text or structured JSON context for all questions. Use named fields for multiple records or facts. Jev evaluates text, not raw images, audio, or video." }, "questions": { "type": "object", "description": "A map of question id to question. Answers come back under the same ids; the ids themselves are not sent to the model.", "minProperties": 1, "additionalProperties": { "oneOf": [ { "type": "object", "required": [ "type" ], "properties": { "type": { "enum": [ "noul" ], "type": "string" }, "criteria": { "anyOf": [ { "type": "object", "properties": { "true": { "anyOf": [ { "anyOf": [ { "type": "string" }, { "type": "object", "additionalProperties": true }, { "type": "array", "items": {} } ], "description": "Text or structured context used to describe a judgment or rubric level." }, { "type": "null" } ], "description": "What qualifies as yes." }, "false": { "anyOf": [ { "anyOf": [ { "type": "string" }, { "type": "object", "additionalProperties": true }, { "type": "array", "items": {} } ], "description": "Text or structured context used to describe a judgment or rubric level." }, { "type": "null" } ], "description": "What qualifies as no." } … (truncated) ``` ## Response schema (JSON Schema) ```json { "type": "json", "example": { "model": "jev-1.13.0", "usage": { "input_tokens": 312, "output_tokens": 48 }, "answers": { "is_urgent": { "noul": 0.92, "type": "noul" }, "department": { "type": "choice", "choice": "technical", "confidence": 0.82, "probabilities": { "sales": 0.07, "billing": 0.08, "technical": 0.85 } }, "frustration": { "type": "score", "score": 1.6, "legend": { "0": "Calm", "1": "Frustrated", "2": "Very angry" }, "confidence": 0.78, "probabilities": { "0": 0.05, "1": 0.3, "2": 0.65 } } } } } ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/jev-system-one-typed-inference-api-x402-f31b4fa3/health.json - [Zero catalog index](https://www.zero.xyz/llms.txt) - [Other services from jev.agents.bakingbad.dev](https://www.zero.xyz/host/jev.agents.bakingbad.dev/llms.txt)