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The full directory

All Jev AI model resources

Entries for TypeSafe AI's flagship System One model — official docs and SDKs alongside community clients, tools, and write-ups.

Entries
3,919
Categories
11
Official
102
Community
3,817
Source sites
293
Deep dives
3,919

By format

3919
  • Docs169
  • Repos & sites3102
  • Videos74
  • Posts104
  • Articles392
  • Playgrounds78

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Browse the Jev AI model by category

11 ways into the ecosystem. Each category page leads with its own shortlist of starting points.

All 3919 Jev AI model resources

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Showing 817–864 of 3919 resources

0GitHub stars
A WebGL visualization of 1,000 light-point boids whose swarm strategy is decided in real time by TypeSafe Jev: PixiJS v8 rendering, TypeScript strict and Vite 8, built by KI Boost Mittelstand.
Jev Demos & Experiments#community#github#webgl
A Spanish-language exploration of macOS voice control that pairs a small generative planner, Claude Haiku 5.5 or Gemini 3.5 Flash-Lite, with TypeSafe Jev for selecting among concrete controls; an MIT-licensed adaptation of savka777's jev-use.
Jev Tools & CLIs#community#github#macos
A documentation-only review of where a typed, local SystemOne decision component could help the SeerScore prediction pipeline, with independent perspectives from Hermes Agent and Cursor Agent and no integration code included.
Jev Practices & Patterns#community#github#review
0GitHub stars
A floating, non-blocking HUD for the Pi coding agent that monitors TypeSafe Jev classifier decisions and LLM queries in the terminal, rendering probabilities, risk badges and latency without halting the agent's work.
Jev Tools & CLIs#community#github#pi
0GitHub stars
Sol vs Jev in a Clash Royale-style tower battle where every move is a real model call through OpenRouter and the clock keeps running while a model thinks; Jev (typesafe/jev-1.13) beat the frontier model 3-0 at far lower cost per decision.
Jev Demos & Experiments#community#github#games
0GitHub stars
Tiny System One decision models trained from scratch in Rust with MLX on a MacBook and played live in the browser via WebAssembly: s3-pico packs 445k parameters into a 251 KB ternary file and decides in about 50 microseconds per frame.
Jev Models & Reimplementations#community#github#rust
A small Python client for Jev on OpenRouter: send a state with typed choice, score and noul questions, get probabilities back, and decide what to do with them; the README presents the helper as problem-agnostic and copyable into any project.
Jev Repos & SDKs#community#github#python
A ready-to-run Python project for exploring and integrating Jev, TypeSafe AI's System One decision model. The README frames Jev as a non-autoregressive alternative to slow LLM calls for routing, classification, triage and guardrails.
Jev Repos & SDKs#community#github#python
An unofficial Go client for TypeSafe's System One Jev model. It sends a state plus typed questions and returns one typed answer per question, with alpha status and no dependencies outside the standard library.
Jev Repos & SDKs#community#github#go
Communitymhmdkzr/jevGo
A pi agent extension that routes TypeSafe's Jev classifier through OpenRouter to block destructive tool calls, verify test and build output, and rank workspace files for a task. It fails open and costs about $0.00002 per call.
Jev Integrations & Adapters#community#github#typescript
0GitHub stars
A Python conformance and behaviour test harness for Jev and other System One decision models that speak the POST /v1/systemone protocol. It reports contract, correctness, calibration, determinism, batching, robustness and limits.
Jev Benchmarks & Evaluations#community#github#python
0GitHub stars
A Python dispatcher skeleton for TypeSafe System One (Jev) that turns typed signatures into batched questions, plus a Playwright browser harness that measures the dispatcher against ground truth.
Jev Demos & Experiments#community#github#python
A Streamlit lab that places a bounded System One decision inside a coding-agent workflow: Laya classifies CI failures, LangGraph applies a fallback policy, and an OpenAI agent inspects a fixture repo and proposes a fix.
Jev Demos & Experiments#community#github#python
A Next.js workbench for evaluating AI ticket triage with TypeSafe AI: classify, route and score support tickets through structured schemas, then inspect outputs, latency, token use and estimated cost in a three-column view.
Jev Demos & Experiments#community#github#typescript
A Python web app that sends every support ticket to Jev (typesafe/jev-1.13) and to configured comparison models through OpenRouter, showing team routing, urgency, severity, sentiment and draft replies side by side with latency and cost.
Jev Demos & Experiments#community#github#python
0GitHub stars
A two-app collection built with Jev models: a visual bug-triage demo that asks Jev to analyze incoming support issues and a GitHub pull-request review dashboard that evaluates changes against user-defined rules.
Jev Demos & Experiments#community#github#typescript
0GitHub stars
A placeholder repository whose entire README says it is where the author will do something with JEV from Typesafe. There is no code, install step or documentation yet, so it is only useful as a status marker.
Jev Repos & SDKs#community#github
0GitHub stars
A PHP decision engine for Laravel that replaces open-ended prompts with typed primitives: Noul for binary likelihoods, Choice for categorical classification and Score for bounded ratings, each returning calibrated probabilities.
Jev Integrations & Adapters#community#github#php
A small, standard-library-only Go library for typed AI decisions. It supports TypeSafe's Jev HTTP API and the OpenAI Decisions API, letting you declare questions once and read answers through the same typed handles.
Jev Repos & SDKs#community#github#go
A Python experiment that adapts Gemma 4 E4B for System One-style decisions: one call takes a situation and a fixed answer list and returns a probability per answer, with per-dataset adapters and held-out results across four datasets.
Jev Benchmarks & Evaluations#community#github#python
0GitHub stars
An unofficial TypeSafe Jev integration for Claude Code with hooks that suggest skills, classify task type, pick subagent model tiers and gate risky shell commands. It also ships jev-vision for yes/no, pick-one and bounding-box questions about images.
Jev Integrations & Adapters#community#github#javascript
A TypeScript WebGL lab that explains a JEV-style decision architecture layer by layer, from user intent and context through a decision core with scoring, policy and confidence to execution and output.
Jev Demos & Experiments#community#github#typescript
A Python research project that uses Jev (TypeSafe AI, System 1) with Neo4j to traverse cybersecurity knowledge graphs probabilistically, choosing promising graph edges and scoring nodes against a goal instead of generating text.
Jev Demos & Experiments#community#github#python
0GitHub stars
A Netflix-style movie recommender whose picks come from Jev: four typed questions deep, ranked in about half a second, with a probability and explanation attached to every recommendation. Built with Next.js 16 and React 19.
Jev Demos & Experiments#community#github#typescript
A Chinese-language book repository on putting Jev decision models into practice, published as an HTML project on GitHub. Grounded on GitHub metadata only: 0 stars, created and pushed 2026-10-11, and no README text captured in the digest.
Jev Guides & Articles#community#github#book
0GitHub stars
A classifier that screens shell commands requested by LLM agents before they run: each command goes to an external judgment backend — TypeSafe's Jev is the production default — and the verdict becomes allow, block, or the normal interactive prompt in the OpenCode V2 harness.
Jev Integrations & Adapters#community#github#go
0GitHub stars
A Claude Code plugin that asks Jev, TypeSafe's System One model, which model tier each prompt needs — haiku, sonnet or opus — and switches automatically, and routes classification, scoring and yes/no judgments to Jev via scripts/jev.py.
Jev Integrations & Adapters#community#github#claude-code
0GitHub stars
Adaptive React UI from a plain-English sentence: a When component asks Jev, TypeSafe's decision model, whether a described situation is true for the current user and swaps the UI, rendering a fallback on slow or unsure answers.
Jev Repos & SDKs#community#github#react
Scaffold project for implementing Jev as a gateway integration layer, demonstrated by a FastAPI service that answers weather questions for a City/State: an SLM works out intent, location and date, Open-Meteo supplies facts, and an LLM writes the answer.
Jev Demos & Experiments#community#github#python
0GitHub stars
Jev Review runs as a local MCP server that gives Claude Code, Codex, Cursor and OpenCode structured quality scores while they work. This modified fork of NiazMorshed2007/jev-review adds strict 451-fallback validation with contract tests and a noul invariant-adjudication workflow.
Jev Tools & CLIs#community#github#mcp
0GitHub stars
The Jev architecture rebuilt from Qwen3-0.6B: a calibrated, type-safe decision model on an open backbone. No decoding loop — the state is encoded once, questions are scored in one parallel pass, and answers are a distribution over options declared before the call.
Jev Models & Reimplementations#community#github#python
A Python first-project that turns messy free-text smartphone reviews into Flipkart-style per-topic star ratings, powered by Jev via the TypeSafe SDK: 14 questions per review — mention detection plus satisfaction — across 7 topics such as camera, battery and display.
Jev Demos & Experiments#community#github#python
0GitHub stars
Intent-aware navigation and command suggestions for zsh, powered by Jev and zoxide: describe where to go or which previous command to run, review the inline suggestion, and press Enter. Jev selects from existing candidates rather than generating new shell commands.
Jev Tools & CLIs#community#github#zsh
0GitHub stars
A standalone proof of concept showing Jev as a structured decision layer for support-ticket routing: fixed-option routing, 1–5 urgency scoring and probabilities for sensitive data, with a deterministic confidence and safety policy deciding auto-route versus human review.
Jev Demos & Experiments#community#github#streamlit
0GitHub stars
A repository described as Jev use cases; the captured README documents an Austrian hotel ranking pipeline that merges Google Maps and Booking.com data, matches the ÖHV member list from meinhotel.at and computes a 0–100 guest score, with dashboards and Excel reports.
Jev Tools & CLIs#community#github#python
A small HTTP service that adds a decision interface to any chat model: POST /v1/decision evaluates a finite set of candidate labels in one forward pass, reads next-token logits and returns structured JSON without model.generate() or output decoding.
Jev Tools & CLIs#community#github#python
Two Claude Code hooks powered by Jev, TypeSafe's System One model: a PreToolUse risk gate that asks three noul questions per tool call and maps the top probability to allow, ask or deny, plus a tier router that rewrites subagent calls to haiku, sonnet or opus.
Jev Demos & Experiments#community#github#claude-code
0GitHub stars
A marketing decision layer that knows when to stay silent, built with Jev and jev-state: Tacet counts and enforces limits in code, Jev chooses one next best action or none, and a person reviews any choice Jev is unsure about.
Jev Tools & CLIs#community#github#typescript
The community hub for System One decision models, live at systemone.dev. It teaches building with models that answer typed questions about a program's state using calibrated probabilities instead of generated text, and its samples work unchanged with Clef and Jev.
Jev Guides & Articles#community#github#docs
An intelligent email parsing and workflow automation system for corporate actions: a Jev ingestion gate decides whether attachments need OCR, then Jev classifies the parsed email as a cash dividend, M&A deal, stock dividend, ticker change, or spam, with Gemini handling LLM and Vision steps.
Jev Tools & CLIs#community#github#python
Four advisory decision tools for AI agents, shipped as a zero-dependency stdio MCP server backed by the TypeSafe System One API (Jev model). Each tool builds exactly one Choice question and returns a decision; nothing is ever executed.
Jev Agents & MCP#community#github#mcp
A live broadcast-delay demo powered by Jev: you talk into a microphone and each sentence prints with its language tagged, offensive words masked one emoji per word, personal information redacted, and trash-talk sentences elided, judged by Jev in roughly 150 milliseconds.
Jev Demos & Experiments#community#github#python
An Apache-2.0 repository announced as 'the open service for system one models'. The digest captures only that one-line README and description, so endpoints, language and usage stay undocumented; it was created and last pushed the same day with 0 stars.
Jev Repos & SDKs#community#github#system-one
A Rust command-line interface for OpenRouter's Jev decision model. Each command sends one state and one typed question to the Decisions API, validates the returned answer against that question, and writes JSON for scripts and agents.
Jev Tools & CLIs#community#github#rust
0GitHub stars
An unofficial decision tool that promises typed probabilities for candidate answers instead of generated text. It advertises an Open-Jev-27B download page and carries systemone and typesafe-ai GitHub topics, but its README shows no code, API or install commands.
Jev Tools & CLIs#community#github#unofficial
A pilot build of the Parking Operations Decision Layer PRD: the support desk, agent guard and shared decision layer send each item to Jev as typed questions in one call, then rules and a confidence gate route it to AUTO, REVIEW, HUMAN or BLOCKED with an audit log.
Jev Demos & Experiments#community#github#typescript
0GitHub stars
Drop-in guardrails for any AI app, powered by Jev: it asks narrow yes/no questions about text, such as whether something is a prompt injection, gets a probability, and lets the app allow, review or block in milliseconds, with adapters for Gemini, Anthropic, OpenAI and FastAPI.
Jev Integrations & Adapters#community#github#python
0GitHub stars
A Rust CLI for System One decision models: typed questions in, calibrated probabilities out, with the API key kept out of the caller. Providers include TypeSafe Jev, Cloudflare Clef, Clef on a local Ollama, and OpenAI chat models read through log-probabilities.
Jev Tools & CLIs#community#github#rust

Start here with the Jev AI model

Hand-picked entries the maintainers recommend first, from official primitives to community tools.

The Jev Day release post: Jev 1.14.0 under jev-preview plus three danger-zone features — composable images on both models, the box question type on 1.14 only, and opt-in 262k context.
Jev Guides & ArticlesArticle#official#release#vision
Official
The box question type: one bounding box per question, returned as four edges that are fractions of the image, plus confidence, with no criteria field and no not-found value.
Jev Practices & PatternsDocs#official#docs#vision
Official
LiteLLM's Day 0 post for TypeSafe Jev 1.14: the proxy adds box questions, image input and long-context mode on both POST /v1/systemone and POST /v1/decisions, forwarding TypeSafe-Danger-Zone headers only to TypeSafe deployments.
Jev Integrations & AdaptersArticle#community#litellm#gateway
Community

From the Jev community

Watch walkthroughs, read the threads, and see what builders are posting.

YouTube: KodeKloud's three-minute primer: what a System One model decides, and why it answers in milliseconds.

YouTube: Caleb Writes Code explains what Jev is and how to call it, in seven minutes.

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.

YouTube: AICodeKing tests support routing, refund detection, prompt-injection resistance, and browser automation.

Hacker News: Show HN: Ad Spend Guard gates budget before the auction, not the creative after.

Show HN: Gating ad budget with a decision modelRead the thread on Hacker News

Reddit: Reranking rebooking options with a decision model, ranked with reasons.

Hacker News: Pick Verify: a single decision at the warehouse pick station catches confusable picks.

Show HN: Verifying robot picks with a decision modelRead the thread on Hacker News

Hacker News: Software Bombe and live Enigma demo where Jev ranks cribs and judges plaintext.

ag_212 pointsShow HN: Jev as the Bletchley Park Analyst: A Software Bombe on EnigmaRead the thread on Hacker News

Hacker News: Show HN for the decide CLI: brew install, file context, and multi-question shell scripts.

vsekhar2 pointsShow HN: Decide – Jev decisions in the shell, scripts, and agent skillsRead the thread on Hacker News

How entries are chosen

Every entry is reviewed against the same bar, whether it comes from TypeSafe or the community.

  • Public and working — no paywalls, sign-up walls, or dead links.
  • Concrete — it has to be about Jev and the System One API, not generic LLM content.
  • Useful today — something a developer can learn from or use right now.
  • Distinct — if a similar entry exists, the description has to say what makes this one different: a different runtime, a cheaper path, a measured result, or a narrower focus.
  • Documented — repos state their license, and docs are in English or carry an English summary.

Spam, affiliate links, and thin AI-generated content are rejected. New entries are expected to ship with a deep dive: two to five highlights, caveats, a quickstart snippet where one helps, and a verification date. Star counts are refreshed when an entry is touched.

Common questions

Short answers about Jev and how this directory works.

What is the Jev AI model?

Jev is TypeSafe AI's first System One model — an AI model that takes a state plus typed questions and returns one structured answer per question: a choice, an ordered score, or the probability of yes, with calibrated confidence on Choice and Score answers. Code can branch on the result without parsing generated text.

What is the difference between Choice, Score, and Noul?

They are the three question primitives. Choice picks one of up to 255 options, Score rates on 2 to 10 ordered levels, and Noul answers yes or no. Choice and Score answers carry a confidence between 0 and 1; a Noul answer is the probability of yes.

Which Jev SDKs and client libraries are available?

TypeSafe maintains official JavaScript/TypeScript and Python SDKs plus a Python adapter. The community has built clients for Go, .NET, PHP, Laravel, Rust, Elixir, Ruby, and Scala, along with framework integrations such as DSPy, LlamaIndex, and Home Assistant. All of them are listed in the Repos & SDKs category.

Is the directory free, and is it affiliated with TypeSafe AI?

The directory is free to browse: every entry is reviewed, and spam, affiliate links, and sign-up walls are rejected. JevDirectory.org is community-run and not affiliated with TypeSafe AI — Jev and System One are TypeSafe AI trademarks.

How often is the directory updated?

Entries are added as new resources appear and re-checked when they are touched. The directory currently holds 3919 entries from 293 source sites, last updated Nov 6, 2026.

What is a verified deep dive?

Most entries include a deep dive: two to five highlight bullets someone would only know from using the resource, a caveats note about limits and requirements, an optional quickstart snippet, and the date the link was last checked. 3919 of the 3919 entries carry one today.

For the canonical details, read the official TypeSafe docs and the API reference.