No project description available.
Jev ecosystem projects — page 150
5191 repositories with documented relationships and source evidence.
Sample: TypeSafe Jev via Vercel AI Gateway
Jev AI Model (Typesafe.ai) security protection and vulnerability scanner tools
Empirical experiments and API research for TypeSafe's Jev System One model trained using RLCD
Can a System One model play arcade games? TypeSafe's Jev plays Tetris, Snake and 2048 — benchmarked against random and heuristic baselines.
Evaluate typed AI decisions on labeled French-language cases.
No project description available.
Measured benchmarks of TypeSafe's Jev decision model vs LLMs: ticket triage, voice-agent decision layer, bulk tagging
No project description available.
Host a local two-truths-and-a-lie party game where Jev is a finite-choice guest.
Classify page context, score configurable risks and apply advertiser-owned brand-safety policy.
Lightweight Browser Use using Jev(TypeSafe) + CDP/Chromium/Agent-Browser
No project description available.
Render a versioned verdict schema to self-contained SVG and optional PNG with zero runtime dependencies.
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Ask questions about your documents and get answers with probabilities. Windows & Android app for Jev (TypeSafe AI) via Vercel AI Gateway — reads whole books, PDFs, Word and images, with on-device OCR. Bring your own key.
Jev (TypeSafe AI's System One model) playing chess against itself, graded by Stockfish
Jev中文体验台：TypeSafe Jev 的中文可视化操作台，支持手机访问、登录额度与结构化概率判断。
Reproducible experiments on prompting criteria in TypeSafe's Jev — how much of a classifier's behaviour is yours to define
Experimental opt-in Jev skills and config for Claude Code — the companion to jev-codex-tools.
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Command-line tool for the TypeSafe Jev decision model, through the official API or OpenRouter: typed yes/no, choice and score questions with calibrated confidence, and confidence gating as exit codes.
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High-performance Unix semantic reflex CLI powered by TypeSafe Jev for agent progressive discovery & pipelines
Early evaluation of TypeSafe's Jev on clinic call triage: 98.6% accurate when confident, 116k decisions per dollar
Qualitative coding at scale with Jev: apply a codebook to open-ended text, review uncertain items, measure agreement against your human coders.
Maintain versioned semantic decisions as indexed PostgreSQL columns with a reclaimable work queue.