Jev (TypeSafe AI)
System One model that returns typed decisions with calibrated probabilities instead of text
API
Available
Mobile App
No
Users
Early access (waitlist)
Free tier
Free playground with login; early-access waitlist at typesafe.ai
Paid plans
$42 per billion input tokens ($0.042/M); output tokens free
Integrations
Key Features
- Typed decisions (Choice, Score, Noul) with calibrated probabilities
- No text generation, no parsing needed
- 70-500ms end-to-end response time
- Many questions evaluated in parallel per call
- Confidence estimates on every answer
- Cost from $0.042/M input tokens, free output tokens
Overview
Jev is TypeSafe AI’s first System One model — a new class of AI model purpose-built for decisions inside software, not text generation. You send it a state (any text) plus a set of typed questions, and it returns structured answers — a boolean probability, a choice from a list, or a rubric score — each with a calibrated confidence value. There’s no parsing, no prompt scaffolding, and no hallucinated prose: the model’s output is constrained to exactly the schema you declare. It launched in public early access on September 15, 2026.
Read our full Jev AI review.
Key Features
- Three primitives: Choice (pick an option), Score (rate on a rubric), Noul (0–1 truth probability) — mix them freely in one call
- Parallel evaluation: every question runs against the same state in a single pass; adding questions barely changes latency
- Calibrated confidence: every answer reports how sure the model is, so your software can act at high confidence and escalate at low confidence
- No hallucinations structurally: outputs can’t be malformed, undeclared, or wrong-typed — the schema is enforced at the model level
- Fast and cheap: 70–500ms latency, about 193x faster and 440x cheaper than frontier LLMs on System One-style tasks
Use Cases
- Support triage: classify tickets by department, urgency, and refund-triggering sentiment in one call
- Agent orchestration: decide which tool or subagent to invoke next, or whether to continue, retry, or stop
- Guardrails and moderation: verify model outputs, detect policy violations, and block risky actions
- Scoring and ranking: rate fit, risk, or quality with a custom rubric
- Routing: choose the right pipeline, provider, or queue per request
- Email and message triage: flag urgency, intent, spam-likelihood, and sentiment
Pricing
- Input tokens: $42 per billion ($0.042/M) — charged per input token
- Output tokens: free (the model returns tiny structured answers)
- Rate limits: 250,000 tokens/second, 1,200 requests/minute
- Context: 64k tokens per request (32k for state plus the longest question)
- Access starts on the early-access waitlist at typesafe.ai; API keys are issued in console.typesafe.ai
Reviews & Comments
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