Last updated 10-10-2026
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Jev AI
Jev AI is a hosted decision API and browser playground for Jev, TypeSafe's System One classification model. You feed it text (or structured JSON) plus a set of narrow questions, and it answers with probabilities, labels, and scores your backend can branch on. That makes it a fit for teams who need guardrails, routing, or evaluation logic without asking a chat model to write paragraphs.
Most LLM APIs optimize for open-ended generation. Jev does the opposite: it skips prose and returns calibrated yes/no odds, choice distributions, and numeric scores in one round trip. You can stack dozens of questions against the same input and read confidence before you auto-approve anything.
Backend engineers, ML platform teams, and support ops leads use it for ticket triage, RAG checks, lead scoring, and model routing. Guided flows on the site cover LLM-as-a-judge, MCP tool routing, and prompt-injection screening, but the same question types work for custom pipelines.
Jev AI is operated independently from TypeSafe; billing, accounts, and support run on jev-ai.pro even though the wire format matches TypeSafe's API.
Runs up to 64 typed questions on one state in a single API call
Yes/No answers ship as 0-1 probabilities, not generated text
Homepage demos land in about 0.5 seconds per run
Output tokens are free; only input tokens (or credits) are billed
POST https://jev-ai.pro/api/v1/systemone accepts TypeSafe-compatible JSON
Jev-Omni adds image, audio, or short video at a 4x token rate
Structured probabilities are easier to automate than parsing free-form LLM replies.
Failed API requests are not charged, with holds released automatically per the pricing page.
One request can answer many questions in parallel, which cuts round trips for triage and eval jobs.
The playground mirrors the API schema, so you can prototype before wiring server code.
Native Jev on Jev AI is text and JSON only; PDFs must be converted manually.
English is the documented sweet spot, so multilingual workflows need extra validation.
Clef and Jev-Omni multiply token usage (up to 6x), which adds up on long inputs.
Does Jev AI offer free credits?
Yes. Jev AI gives eligible new accounts 20 welcome credits to try the playground and web tools before you buy tokens. Daily check-in gifts add more credits to your Credit account, while paid purchases add input tokens to a separate Token account.
How much do Jev AI token packs cost?
Jev AI sells one-time input token packs on its pricing page, starting at $9 for 15M tokens ($0.600 per 1M input tokens). Larger packs include 75M tokens for $39, 200M for $76, and 600M for $170, with lower per-million rates on bigger bundles.
Does Jev AI have a REST API?
Yes. Jev AI exposes POST https://jev-ai.pro/api/v1/systemone with a Bearer API key. You send a model id, a state string or JSON object, and a map of question definitions; the response returns structured answers plus usage metadata.
What question types does Jev AI support?
Jev AI supports three shapes: noul (yes/no probability), choice (pick one labeled option with a full probability map), and score (rate text on 2-10 ordered levels you define). Each question needs instructions, and choice or score types need criteria or level labels.
Can Jev AI read PDF files?
No. Native Jev models on Jev AI accept plain text, a JSON object, or an array only. PDF upload is not supported; convert the document to text first, or use Jev-Omni in the playground for images, audio, or short video.
Which language is most accurate on Jev AI?
Jev AI documents English as Jev's primary language and the most reliable option. Other languages may work, but the site advises testing on your own data and watching confidence scores before you rely on them in production.