Jev ecosystem projects — page 38

Executable cognitive architecture: validated graph context, deterministic cache, bounded JEV routing and evidence-gated model collaboration.

Bilibili sponsored-segment detection powered by TypeSafe Jev

A Paseo model router using TypeSafe Jev or local Laya to classify Codex turns.

本机运行的中文聊天分析工具：Jev 逐句观察情绪与意图 + DeepSeek 解释，数字全部由程序计算，数据只存在本机

A Jev-like decision engine powered by DiffusionGemma and SGLang. Jev with eyes.

Do what I mean: type what you want in plain words and it runs the right menu item in any Mac app. Powered by Jev (bring your own key).

Client for TypeSafe's SystemOne API for Jev

Open-source AI ad blocker for Chrome. No filter lists: TypeSafe AI's Jev model decides what is an ad. Bring your own key.

Makes Claude Code and Codex ask whether a step needs a generative LLM at all — or whether it belongs on Jev, TypeSafe's System One model. Architecture arbitrage before the code is written.

Community-maintained history of Jev / TypeSafe System One APIs, SDKs, agent guidance, and engineering best practices.

Educational demo: score simulated token launches GEM/RUG via a mocked TypeSafe Jev decision model. Shadow/active router, no real trades.

MCP server for typed decisions with Jev / System One via OpenRouter or TypeSafe

MCP server wrapping TypeSafe's Jev System One models — typed noul/choice/score judgments for AI agents

One TypeSafe Jev decision per step over the A11Y tree, executed via ADB. No screenshots and ultra fast!

Routes prompts to the right Claude tier (Haiku/Sonnet/Opus) using TypeSafe's Jev model

Route any task to the right AI agent in under 1 second using Jev (TypeSafe System One). Supports Claude, ChatGPT, Cursor, and Antigravity with auto-launch on macOS, Windows, and Linux.

Type-safe Java 21 client for the TypeSafe AI Jev (System One) decision API

Pre-message hook: use TypeSafe Jev to keep/drop skills and shrink agent context

Jev Slop Guard — a Chrome extension that scores and stamps AI slop on your X and LinkedIn feeds as you scroll

Find files by describing them in plain English: find(1) with a semantic --like predicate, answered by TypeSafe.ai's jev model

Metask-Jev: calibrated typed-decision models (Jev-class). Single forward pass, candidate-logit readout. metask-jev-4b beats Bespoke Nimble-9B and Jev on JevBench.

n8n community node for Jev by TypeSafe AI: classify, score and check text with calibrated probabilities. Parallel requests and multi-item batching.

Pytest plugin for semantic assertions on LLM output using Jev's calibrated probabilities.

Turn a pile of comments into an auditable distribution: Jev judges each item, code counts the percentages. React workspace + Python engine with pluggable data sources.