Jev 101
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Jev 101

JEV White Paper

A new AI model built for decisions: fast, low-cost answers to the choices software makes every day.

● ● ●one support message
01Customer: My parcel is late
↓
02Jev picks: delivery
↓
03App routes to the delivery team

So what is Jev?

Jev is a new AI model from TypeSafe, founded by Diogo Almeida, an early contributor to core ChatGPT research. It helps software judge, choose, and score instead of writing long answers.

Chat models write answers.
Jev helps software choose.
For example, routing a support request.

What three kinds of questions can Jev answer?

Good fit: bounded answers

  1. Yes or no NoulShould a person review this message?Returns the chance of “yes”
  2. Pick one ChoiceIs this about delivery, refunds, or payment?Chooses from your options
  3. Rate it ScoreIs this ticket low, medium, or high priority?Scores on your defined scale

Poor fit: writing or exact calculation

  • Write contentUse a generative model for emails, articles, or code.
  • Open-ended chatJev is not a conversational assistant.
  • Exact calculationsUse ordinary code for money, counts, and dates.

Jev makes a decision; your software decides what happens next.

One example: a customer asks about a parcel

01 · Customer says

“My parcel has not arrived. Can you check?”

02 · Jev chooses

Type: delivery / refund / payment → delivery is most likely

03 · Software acts

Route the ticket to delivery support; send uncertain cases to a person.

Illustrative example, not a real API response. Jev does not read inboxes or message customers by itself.

Why use it in a game?

Games need repeated choices: dodge, move, or fire. Give Jev prepared text or data about health and enemy positions, then let it pick from allowed actions. TypeSafe demonstrated this with Doom; Jev did not read the game image directly.

See the official demo →
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