Jev ecosystem projects

Build and run agents you can see, understand and trust.

Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.

Fastest and cheapest web agent

The Generative UI framework

Open-source AI Trading OS, agent trading, and vibe trading, with Jev System One integration. Research, build Python strategies, backtest, and paper/live trade across crypto, stocks, and forex. Launch your own multi-tenant trading SaaS with built-in user management, billing, payments, and settlement.

✨ All your agents and workspaces in one place, on every device you own. Track tasks on a board, accessible from desktop, mobile, browser, or API. Self-hosted.

Claude Code plugin that replaces the compaction summary with Jev decisions: every tool call and result is scored in one fast request, stale ones are dropped or truncated, everything kept stays verbatim.

tiny Jev-like family of decision models built on top of Qwen3.5 you can train and run on your own

装在手机上的对话副驾：在微信 / QQ / X / 飞书里读懂对方、给出候选回复、一键填入输入框，发不发由你。非侵入，只读屏幕，不 hook 不改包。

The Open Framework for Building Agents

Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.

Unix like coding agent

A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown and Milvus.

One AI trade decision every Monad block. Jev on Kuru MON-USDC.

A nano replica of Jev: parallel decisions, dynamic candidates, and an end-to-end training pipeline.

Agent skills for building with TypeSafe's System One API

A curated list of public projects, integrations, and discussions built on Jev — TypeSafe AI's System One model for typed decisions.

OpenTelemetry Instrumentation for AI Observability

Computer use for about $0.0002 a step: OCR the screen, classify the next action with TypeSafe, click. macOS.

Evidence-backed use cases, patterns, prompts, and starter code for TypeSafe Jev — a System One model for fast, typed, confidence-aware decisions in software.

AI agents can generate code, but still struggle to understand what they build. Reticle brings Jev-style machine-native runtime perception to web & desktop applications.

A verified, community-maintained catalog of 896 open-source projects built with Jev.

Biologically-inspired memory for AI agents. Decay, retrieval strengthening, consolidation. Zero runtime deps, SQLite, MCP. Benchmarked retrieval with an opt-in hosted TypeSafe Jev reranker.