The Jev launch post
Diogo Almeida introduces Jev, a structured decision model from TypeSafe. This resource provides an overview of the model's core approach, practical examples, and performance metrics as reported by the author.
The best of Jev. Real projects, practical guides and ideas from across the internet.
Diogo Almeida introduces Jev, a structured decision model from TypeSafe. This resource provides an overview of the model's core approach, practical examples, and performance metrics as reported by the author.
TypeSafe officially launches its research lab and introduces Jev to the developer community. This announcement features a launch film by Diogo Almeida and provides foundational context for the project's mission and future direction.
TypeSafe has removed the waitlist for Jev, allowing public access to the platform. Developers can use the official console to integrate and test typed decision-making capabilities within their own software applications.
TypeSafe highlights Jev’s typed-output approach, where applications provide state and questions to receive structured probabilities, choices, or scores. The announcement also details the integration of the Venice API for developers.
Start with the Launch Post. Explore four official signals.
AI-assisted summaries and translations. Check original sources for context and performance claims.
Cyber-Breach: The Jev Protocol - A tactical cyberpunk arena combat game powered by TypeSafe AI Jev System One decision model.
Dasheng is a tool that integrates speech recognition with Jev to provide real-time, word-by-word transcription of spoken audio. It demonstrates a method for live content marking and automated text capture during speech.
This proof-of-concept demonstrates low-latency audio censorship by integrating Jev typed decisions with ffmpeg. It illustrates how structured decision-making can be applied to real-time media processing workflows.

The AI-augmented control plane for cybersecurity — unify your security stack, quantify cyber risk in dollars, and run governed AI agents.
Explore sponsorThis project demonstrates one-pass option scoring using a local Gemma 3 4B model on Apple silicon via MLX. It includes a functional Doom demonstration to showcase the implementation of this specific scoring approach.
This tool provides a CLI and GitHub Action designed to evaluate code-change risk. It utilizes deterministic rules and TypeSafe Jev to suggest appropriate checks and reviewers before merging pull requests.
This project provides a secondary MCP server implementation for Jev. It serves as a technical resource for developers looking to integrate PyModel-based components into their Jev-compatible agent workflows.
Official TypeSafe reference: API reference.
This hybrid browser harness utilizes an LLM to decompose user goals into verifiable subtasks. Jev then selects specific actions and DOM elements, which are executed by Playwright to automate web interactions.

Falconer is an AI-powered company brain that keeps your engineering documentation accurate, searchable, and up to date by syncing with GitHub, Slack, Linear, and the rest of your stack.
Explore sponsorThis project demonstrates an automated routing system for Pi that utilizes TypeSafe Jev via the Vercel AI Gateway. It provides a framework for managing model requests and traffic distribution within the Jev ecosystem.
This project evaluates the ability of Jev to predict successful A/B test outcomes for headlines. The creator reports that Jev correctly identified the winning headline in 64.5% of over 10,000 Upworthy experiments, with accuracy increasing when performance differences were more pronounced.
jev-me provides an interactive interrogation tool where Jev analyzes and challenges your project ideas. It functions as a structured brainstorming assistant designed to stress-test concepts through critical questioning and logical evaluation.
Probably: live BTC, ETH, and XRP prices with a shared TypeSafe buy-or-wait demonstration. No trades placed.
Connect JEV to MCP clients and compare its judgments against general-purpose LLMs using shared datasets and measurable accuracy.

Wallpets brings cinematic animal companions to your desktop with lightweight mouse-following behavior, idle play, and a growing pet catalog.
Explore sponsorAn agent skill to discover TypeSafe Jev opportunities, design typed questions, and learn from recent community experiments.
A developer tool for decision runtime with zero-token caching and a calibrator, collected for the tools shelf.

Für Ideen, Gespräche, Meetings und alles dazwischen.
Explore sponsorharnessjudge provides a framework for evaluating agentic workflows using TypeSafe Jev. It demonstrates how to systematically categorize agent steps as successful, requiring retries, needing escalation, or stopping execution based on defined operational logic.
This repository provides a method for batched single-token choice inference designed for open language models. It demonstrates integration compatibility with TypeSafe, offering a structured approach to handling token-level decision processes in generative AI workflows.
This Rust library provides typed clients for AI services, supporting both asynchronous and blocking backends. It demonstrates how to implement observable retry mechanisms to improve the reliability of AI-driven application interactions.
A GitHub project showcases Jev's performance in a chess benchmark, achieving perfect gameplay with minimal cost.
This tool provides a lightweight, dependency-free command-line interface for interacting with TypeSafe Jev. It serves as a utility for developers looking to integrate Jev workflows directly into their terminal environments.
Jev Social demonstrates an automated research tool that performs bounded browser operations on social media platforms. It captures evidence from Instagram, TikTok, and LinkedIn to generate cited reports based on the retrieved data.
This project introduces a 151M non-autoregressive decision engine designed for Jev environments. The creator claims the model achieves specific accuracy and calibration metrics on the LocalLLaMA typed-decisions benchmark compared to existing TypeSafe Jev and Laya implementations.
CartShield utilizes TypeSafe Jev to assist small and medium-sized businesses in managing checkout fraud. This tool provides a structured approach for evaluating transaction risks and automating disposition processes within e-commerce environments.
This project demonstrates a cost-aware LLM router designed to select the most economical model for a given query. It utilizes Jev for rapid classification, aiming to reduce operational expenses by avoiding unnecessary LLM calls.
This tool functions as a Magic 8 Ball for pull requests, providing one of twenty classic responses. The creator claims the agent selects answers based on real PR signals within approximately 200 milliseconds.

Menta es el software de gestión clínica impulsado por IA. Una plataforma todo en uno para la gestión administrativa y clínica de profesionales y clínicas
Explore sponsorThis project presents an experimental chat interface that processes raw character input using TypeSafe Jev Choice. It demonstrates a novel approach to observable, structured interaction models within the Jev ecosystem.
This project explores zero-shot spam filtering using TypeSafe Jev Noul questions. It provides a comparative analysis against traditional TF-IDF baselines to evaluate classification performance in text filtering tasks.
This project demonstrates a Next.js brick breaker game where the paddle movement is controlled in real time by the TypeSafe AI Jev model. The creator reports that the application was developed using Claude Code.
This Go client library enables integration with the TypeSafe System One API. It demonstrates how to implement typed judgments and calibrated probabilities within Go applications, moving away from traditional generative text outputs for structured data analysis.
This cyberpunk-themed game uses TypeSafe Jev to simulate a tense border crossing encounter. Players must navigate dialogue choices to bluff guards and verify digital receipts to progress through the narrative.

Whale sharks drifting past. A quiet café after hours. Sixteen living worlds, just beyond your screen.
Explore sponsorThis project demonstrates integrating LlamaIndex reranking and routing with TypeSafe Jev. It explores using typed scores and choices to manage decision-making processes, aiming to provide a more cost-effective alternative to traditional LLM-as-judge evaluation methods.
This demonstration showcases the Jev System One model identifying major cloud provider service names. The tool provides probabilistic outputs to evaluate the model's classification accuracy regarding specific cloud infrastructure terminology.
Non-Autoregressive AI Agent Decision Model. Open-source SOTA alternative to TypeSafe Jev. O(1) Tool Routing & DOM Automation on Qwen3.5-2B .
Sort by meaning: order lines along a plain-English dimension, from pairwise comparisons judged by TypeSafe's Jev model.
This experiment demonstrates the application of Jev to process a large personal writing archive. The author reports that the tool completed a comprehensive review of their entire body of work in under one second.

Falconer is an AI-powered company brain that keeps your engineering documentation accurate, searchable, and up to date by syncing with GitHub, Slack, Linear, and the rest of your stack.
Explore sponsorThis project provides a Jev-powered browser MCP designed for LLM agents. It demonstrates a method for browser interaction that aims to bypass LLM token usage for decision-making, with the creator claiming response times around 300ms.
This tool provides TypeSafe skill routing for the Hermes Agent by identifying the appropriate skill before model execution. It utilizes a standard library approach to optimize agent performance and reduce unnecessary processing costs.
⚡ Ultra-fast, low-cost intelligent task classifier and 3-tier routing engine powered by TypeSafe Jev (System One).
Pydantic AI capabilities made stronger with Jev: small runnable demos, one file each.
This Rust library provides a lightweight integration for interacting with the Jev ecosystem by TypeSafe AI. It demonstrates how developers can implement client-side connectivity to Jev services within Rust-based applications.

Guideless is an AI-powered platform that turns software workflows into video training guides.
Explore sponsorThis tool provides a local browser automation interface. It utilizes TypeSafe Jev to determine bounded page actions while restricting text models to handling field values only.
J++ is an experimental programming language designed for developers to construct Jev-based queries. This project serves as a specialized tool for interacting with Jev architectures through a custom syntax.
Unofficial go SDK for typesafe AI, with typed answers, retries, and context support.
Free, no-signup Noul demo. Ask a question, get yes, no, or maybe, with web search when needed.
This TypeSafe AI reference explains the implementation of hierarchical classification systems. It demonstrates how to structure data taxonomies to improve model accuracy when categorizing complex information into nested, multi-level labels.
Lemonpod gives founders one morning brief that combines GitHub, calendar, tasks, inbox, and other work signals into a text summary and audio update. Start the day knowing what needs attention without checking multiple apps.
Explore sponsorHome Assistant Assist conversation agent powered by TypeSafe's Jev (System One) model.
Rust SDK for the TypeSafe AI API.
This project demonstrates an autonomous web browsing agent that integrates Jev for decision-making with Vercel's agent-browser for execution. It includes a benchmark to evaluate the system's performance in navigating and interacting with live websites.
This project provides a benchmarking framework for market analysis using Jev. It demonstrates how developers can structure data-driven evaluations within the Jev ecosystem to assess specific financial modeling tasks.
Foreman is an agent supervisor designed to manage coding agents. It utilizes Jev-based decision-making processes to help maintain focus and ensure agents remain on their assigned tasks during development workflows.
TypeSafe'in Jev karar modeli gerçek bir online 2048 sitesinde oynuyor — hamle başına tek API çağrısı, tek anahtar.
This project demonstrates the application of Jev for automated trading strategies. It provides a framework to backtest buy, sell, and hold decisions using NQ L10 order-book data to evaluate model performance in simulated market environments.
This experiment demonstrates a Jev-style typed-decision interface using a frozen Qwen3-4B model. It teaches how to extract option letter logits directly instead of relying on standard JSON generation for decision-making tasks.
This project explores the utility of Jev as an automated evaluation framework. It demonstrates a methodology for using Jev to assess model outputs, providing a structured approach for researchers to implement comparative analysis within their own workflows.
This Neovim plugin utilizes Treesitter to segment code into functions for analysis. It allows users to query their buffer in plain language, with the tool ranking and returning answers via the quickfix list based on its internal scoring mechanism.

Sound notifications for any AI agent — hooks for Claude Code, Cursor, Codex & more, plus an MCP server so the agent can choose its own sounds.
Explore sponsorLatent Space's launch-day roundup: over 100x faster and 200x cheaper than small frontier LLMs.
This repository provides a live trading implementation for the Hyperliquid platform using Jev. It demonstrates how to integrate automated trading logic with the exchange's API to execute market operations in real-time.
This tool demonstrates a recursive approach to managing Jev choices within a taxonomy. It enables users to navigate more than 255 options while maintaining compatibility with TypeSafe Jev's established choice limitations.
This tool identifies breaking API changes by combining deterministic checks with TypeSafe JEV System One semantic analysis. It aims to detect inconsistencies often hidden within OpenAPI documentation prose to ensure better API reliability.
This TypeSafe AI reference explains the speculative fan-out pattern. It demonstrates how to improve system responsiveness by initiating multiple concurrent requests and selecting the first successful result to reduce overall latency in AI-driven workflows.

Für Ideen, Gespräche, Meetings und alles dazwischen.
Explore sponsorScala 3 / ZIO client for the System One API: typed end-to-end, several questions per round-trip via NamedTuple.
This repository features interactive experiments ranging from support routing to 3D driving simulations. It demonstrates how structured sensor data can be processed to generate type-safe driving decisions like steering, braking, and overtaking in a controlled environment.
This repository provides safety validation mechanisms for AI agents like Hermes. It demonstrates how to implement automated checks that require human approval or verification before an agent executes specific actions or modifies system states.
This repository provides automated crawlers built with Unix-style primitives for system analysis. It demonstrates a modular approach to bug-hunting by utilizing lightweight, composable tools to perform systematic data collection and vulnerability discovery across target environments.
decisionbridge provides a Jev-inspired interface for LLMs, enabling explicit decision-making through scoring, calibration, and review thresholds. This project demonstrates a structured approach to managing model outputs by requiring verifiable choice parameters before final execution.
This project provides a side-by-side comparison of TypeSafe and DeepSeek-flash. It evaluates performance metrics including speed, token usage, cost, and accuracy across tasks like invoice extraction, email classification, and reranking.
jevmail is an open-source tool that uses Jev to categorize Gmail messages into specific folders like Needs reply or Spam. The creator claims it processes 1,000 emails per minute locally while maintaining read-only access to your inbox.
chowder is a unified API layer that aggregates, normalizes, and serves your data from any source. One endpoint. Every ingredient.
Explore sponsorThis project provides a Rust implementation of the system-one-adapter, designed to facilitate LLM-backed evaluations. It serves as a technical port for developers looking to integrate system_one evaluation methodologies within a memory-safe Rust environment.
A GitHub project enabling voice-controlled Mac automation without vision models.
This TypeSafe AI guide explains the autoresearch feature discovery process. It demonstrates how automated systems can identify and categorize new features within a codebase to improve development efficiency and maintain project documentation.
Observable browser stealth game: Jev makes typed guard judgments while deterministic code owns the world.
This experimental tool utilizes TypeSafe Jev to provide real-time scoring for viral potential in X drafts. It demonstrates an automated approach to content evaluation, though the effectiveness of its scoring methodology remains an unverified claim by the creator.