Launches on September 16, 2026

This browser agent turns visible page controls into an indexed action space for a natural-language goal. Jev chooses the operation and compatible element in one request; a separate small LLM generates text for TYPE_TEXT.

SemIf handles small semantic decisions such as routing, retries and evidence checks by reading option probabilities without generating an answer sentence. It reproduces Jev's interface pattern with open models, not Jev's undisclosed model or training, and has no TypeSafe affiliation.

The bot replaces post-only limit quotes on Monad blocks and streams book, order and fill events to a dashboard. With MODEL=jev and TYPESAFE_AI_API_KEY, Jev chooses buy or sell; the default mock model is a momentum heuristic.

typesafe-computer-use turns a written goal into desktop actions using OCR and accessibility controls on a Mac. TypeSafe Jev chooses the action, target and site; code supplies facts, while a separate writer handles free text. Provide a TypeSafe key and screen-recording and accessibility permissions. The CLI offers a dry run before real mouse and keyboard control.

decider returns Choice, Score and Noul probabilities from a state and typed questions in one forward pass. This independent Jev-style model family uses Qwen bases; its training data was not distilled from Jev. Call the Python Decider interface or point TypeSafe SDKs at its compatible local HTTP endpoint.

Jev Review scans Git diffs or complete codebases for correctness, security, reliability, compatibility and test coverage. Jev selects evidence, classifies mechanisms, scores severity and, when needed, uses Choice to select a reviewer. Code applies thresholds and workflow policy. Use Node.js 24+, Git and a TypeSafe key to generate JSON reports or inspect saved reviews locally.

jev-router launches the native coding CLIs through a local proxy and selects a model tier for each new user turn. Install jev-router with npm, configure JEV_API_KEY, and launch jev-claude or jev-codex with an installed, authenticated upstream CLI.

TypeSafe Mario is an experimental NES controller loop using emulator telemetry and RAM-derived game observations. With Python 3.13, a TypeSafe key and your local game setup, inspect state-demo before running the play command.

Define semantic expectations in perch.yaml, scoped to files or methods, and inspect the resulting code findings. The System One client asks typed questions about supplied state, defaults to jev-latest and calls TypeSafe's API.

Camera-only autonomous drone in MuJoCo with a small judgment model (TypeSafe Jev) in the loop at 2.5Hz

Guardrails for Pi that steer instead of interrupt: enforces your project rules on every write, holds only hard-to-undo actions (3 per 1,000 calls, measured on real sessions), catches unverified "done" claims and stuck loops, and trims tool output. Built on pi-typesafe.

Typesafe.ai System One Model Jev navigating a Neo4j graph by using a classifier over neighbouring relationships

TypeSafe Jev as a decision layer for the Pi coding agent: a measured tool-call gate plus jev_ask for typed, calibrated answers

A calibrated context sieve for Claude Code: every tool result is judged by a System One model before it enters context.

A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.

Browser automation where an LLM plans and Jev (Typesafe System One) decides. Library, CLI and MCP server.

Codebase search powered by Jev from @typesafe-ai

Typed semantic decisions for Unix pipelines and CI, powered by TypeSafe AI Jev.

JEV-inspired parallel decisions for CUDA LLMs. One context, many decisions. vLLM API, game-agent examples, and reproducible benchmarks.

TypeSafe decisions for Pi: batched evaluation tool, terminal playground, and typed API for extension authors

Typed JSON inference with DiffusionGemma, with Every and Jev benchmark results

This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.

Local bilingual probability decisions from context, questions, and candidate answers. Independent research preview inspired by TypeSafe Jev.

TypeSafe Jev controls original StarCraft shareware through keyboard and mouse with recorded action probabilities.

Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell

Unofficial study: Jev-style parallel typed decisions on stock 1.5B-8B models on an Apple Silicon laptop. Benchmarks, research notes, and a Hugging Face Space demo.

MCP server for TypeSafe Jev: typed classify, score, check, match and screen for any agent, with confidence on every answer

Typed, confidence-aware agent skill routing with TypeSafe Jev.

Community TypeSafe AI playground: 110 use cases, games, dilemmas and model challenges, with editable prompts, A/B comparisons and a mobile-friendly UI.

TypeSafe structured-output provider for RubyLLM 2

BrighTO LLM Router: free open-source, ultra-fast self-hosted Rust LLM gateway for OpenAI/Anthropic APIs, SystemOne/JEV/DJEV decisions, Ollaya/Laya, load balancing, fallback routing, team keys and token budgets.

TypeSafe (Jev) skill routing for Hermes Agent: names the one skill worth loading, before the model call. Opt-in, stdlib only, ~$0.001 per routed turn.

Async LangGraph workflow that gets a typed Jev Choice (invoice or general) and routes each inbound email to the matching handler.

Community .NET SDK for the TypeSafe AI System One API — typed noul, choice, and score questions with structured, confidence-scored answers. Not affiliated with TypeSafe AI.

Can a decision model beat dedicated rerankers? TypeSafe Jev vs Cohere Rerank 4 vs ZeroEntropy zerank-2 vs a chat-model baseline: 14 datasets, every raw API response, bootstrap ranges on every gap.

Hybrid coding harness: System 2 writes, System 1 (Jev) runs reflexes.

Ruby client for typesafe.ai

macOS computer use driven by Jev (TypeSafe System One) as the decision maker

Benchmarks and a playground for TypeSafe's Jev (System One) model: chess, and who-is-the-player-talking-to for speech-to-text game NPCs

A word-level language model whose output layer is Jev: n-gram drafter, Noul chunk verification, bits-per-token eval

Jev (TypeSafe) vs Claude Haiku 4.5 on 2 000 phishing emails: accuracy, calibration, latency, cost. Reproducible benchmark.

Discriminative Monte Carlo Tree Search using System One and Harnesses

Go client for TypeSafe's System One API and its model Jev: typed judgments and calibrated probabilities instead of generated text

Experimental multi-horizon BTC signal generator using TypeSafe Jev probabilities and Binance market data.

DeepSeek Harness (dsh) 插件:论文伴读工作台 —— PDF 转录 / 检索 / 流式问答 + 内置阅读器页面。

Eight minimal working examples of TypeSafe's Jev (a System One model) applied to mechanical and electrical engineering: CAD/CAE/CAM routing, FEM result triage, DFM screening, BOM alignment, hallucination-proof extraction. Zero dependencies.

Jev-style calibrated decision model (Choice/Score/Noul) on Qwen3.5-0.8B

Ask Jev typed questions from the shell: noul, choice, and score answers as numbers, not prose

Independent Jev 1.13.0 behavior study: report, controlled prompt experiments, raw results, and offline verification.

Drives a real browser with Jev making every decision and Vercel's agent-browser performing every action, with a benchmark.