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Jev by use case

Classification

22 curated entries. Assign a label or category to text or records, from intent and sentiment to topic and spam.

By format

  • Repos & sites14
  • Videos5
  • Articles2
  • Playgrounds1

22 resources

1.1kGitHub stars
A local yes/no decision model that speaks Jev's wire format on a laptop CPU, refusing Choice and Score until those question types ship.
Models & Reimplementations#community#python#open-models
702GitHub stars
A local daemon that pulls open decision models and serves them on TypeSafe's /v1/systemone, so a Jev client switches hosts with TYPESAFE_BASE_URL.
Models & Reimplementations#community#rust#open-models
689GitHub stars
A local server that reads next-token probabilities from a fine-tuned Spark model and returns Choice, Score, and Noul answers with zero generated tokens.
Models & Reimplementations#community#python#open-models
520GitHub stars
A Node and TypeScript package that runs Convai's Laya checkpoint through ONNX Runtime, with the same system_one shape as the Python reference.
Repos & SDKs#community#typescript#open-models
39GitHub stars
A local /v1/systemone server that reads label probabilities from a GGUF chat model, with prompt repetition and a confidence shrink toward uniform.
Models & Reimplementations#community#python#open-models
7GitHub stars
A Python server in front of llama-server that reads one-token label probabilities and exposes them as POST /v1/systemone.
Models & Reimplementations#community#python#open-models
344GitHub stars
A multimodal decision model that scores text, image, and video candidates with a shared head on Qwen3.5, plus SFT and experimental RLCD training code.
Models & Reimplementations#community#python#open-models
468GitHub stars
Classifies and splits PDFs, DOCX, and PPTX with local page text from LiteParse and category decisions from Jev.
Tools & CLIs#community#python#document
323GitHub stars
A single-binary MCP tool named evaluate that sends Noul, Choice, and Score questions to hosted Jev or a local System One server.
Agents & MCP#community#go#mcp
27GitHub stars
Five typed tools — classify, check, score, rank, and ask — plus a skill, wired into Claude Code, Codex, Pi, and OpenCode in one setup command.
Agents & MCP#community#typescript#mcp
19GitHub stars
An IMAP client that turns each inbox category into a Noul, then tags, moves, flags, or calls a webhook when the probability clears that category's threshold.
Tools & CLIs#community#python#email
A 770-post benchmark that scores Jev, Sonnet 5, GPT-5 nano, and two local models on Reddit verdicts with weighted Brier scores.
Benchmarks & Evaluations#community#python#evaluation
An independent browser playground that runs TypeSafe Jev on one question or several, with ready examples for routing, refunds, urgency, and the next agent action.
Demos & ExperimentsPlayground#community#playground#tutorial
Community
Vercel's guide for when a typed Jev decision is enough and when a job still needs GPT-6 Astra to write, see images, or call tools.
Guides & ArticlesArticle#community#article#routing
Community
Sam Reghenzi's product-taxonomy benchmark: a Jev Choice at every level versus a gpt-5.2 agent that descends the tree and can be sent back by a judge.
Guides & ArticlesArticle#community#article#evaluation
Community
Riley Brown on a decision model that cannot write: a model router, Choice, Score, and Noul, then speed, cost, and where to get access.
Guides & ArticlesVideo#community#video#explainer
Community
Codevolution's walkthrough of state, questions, and answers, then a customer-message demo in the TypeSafe playground and the TypeScript SDK.
Guides & ArticlesVideo#community#video#tutorial
Community
Yash Thakker's intro to System One, plus 50 open-source demos that compare Jev with a regular LLM, linked from the description.
Guides & ArticlesVideo#community#video#use-cases
Community
Joe Maddalone on using Jev for routing and filtering before a generative model, with demo code in a transcript-analyzer repo.
Guides & ArticlesVideo#community#video#routing
Community
KodeKloud on why a System One model returns calibrated probabilities, then a Papers, Please-style queue where Jev is compared with GPT-5.5 and DeepSeek.
Guides & ArticlesVideo#community#video#explainer
Community
57GitHub stars
An Apache-2.0 decision engine with a TypeSafe-compatible endpoint, document answers with source passages, and a ViZDoom demo that picks actions from structured game state.
Models & Reimplementations#community#python#local
3GitHub stars
A self-hosted System One server: one /v1/systemone contract, a Docker image each for Laya and kev, and a playground where snake, dino, and tetris call that endpoint.
Models & Reimplementations#community#python#local

Articles

Original guides that go deeper on classification.

All articles
A base URL is the whole client change. What still works when Ollaya, Lichen, verdict, Rizzo Flow, or jevos answers POST /v1/systemone on your machine.
Models & Reimplementations#open-models#local#api
Read article
Jev labels a record that already exists. Code moves, flags, or holds it. How the document, mail, and transfer tools keep the action out of the model.
Tools & CLIs#classification#email#security
Read article
A game tick is a state plus a legal action list. How Clash Royale, Minecraft, and the earlier Mario, Pokémon, StarCraft, and drone loops ask Jev one step at a time.
Demos & Experiments#gaming#agents#control
Read article

Watch: Jev in action

Video walkthroughs and demos from the community.

YouTube: Greg Isenberg and Ryan Vogel on the businesses Jev unlocks, and a path in through the Vercel AI Gateway.

YouTube: CJ from Syntax demos browser use, classification, code review, a model router, and a chat bot with no LLM.

YouTube: Ryan Vogel runs Jev on 100 and then 1,000 emails: category, priority, spam, and reply predictions.

Discussions

Threads from Reddit and Hacker News about building with Jev.

Reddit: Matthew Berman's video on Jev, at roughly 290K views.

Hacker News: Show HN: a GIF decider that lets Jev pick the reaction.

arminn2 pointsShow HN: I Built a GIF Decider with JevRead the thread on Hacker News

Hacker News: Show HN: a mouse colony where each next move is Jev or a fixed rule.

1 pointShow HN: Jev-mice – mouse colony simulation using Jev and deterministic engineRead the thread on Hacker News

From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

Trading bot, one decision per block

Classifying 1,500 real emails

this model is actually insane at email classification i tested it on 1500 of my own emails to see how well it works and I am blown away

Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

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Fast browser use with Stagehand

we built blazing fast computer/browser use with Jev + @Stagehanddev. this task cost $0.001 and executed at near instant speed (in a remote browser btw) the loop: observe the page, send a11y tree as state + actions as questions, Jev decides the next action, then Stagehand Show more

Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

Reply

LLM-as-a-judge, sped up

Jev has spoken. It picked which model is AGI. 20–200x faster. 40–400x cheaper. This could make things like LLM-as-a-judge insanely fast and nearly free. (I tried a bunch of prompts and still didn’t burn through $0.10.)

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Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

Reply

Instant compaction with Jev

A Claude session from 1M to 86K tokens

This is actually insane. This uses @typesafeai Jev model, as a plugin in Claude to review all the un-nesseasary tool calls, and it takes 1s to run! Like, literally, 1 second to take my Claude session from nearly 1M to ... 86K tokens! 😮 Ask your claude to install it and be  Show more

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tamara
tamara
@tamarajtran

found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant

Reply