Jev ecosystem projects — page 82

Escribe un tema y mira cómo Jev (TypeSafe) juzga 100 videos de YouTube en segundos. Corre en tu propia cuenta de Cloudflare.

Proof of concept: auto-tagging and triage of Readwise Reader articles using TypeSafe AI's Jev

Resume-to-job-description fit classification using TypeSafe AI's Jev model via LangChain

An autonomous risk-monitoring MCP server. Define a risk profile — a topic, the geographic locations to watch, and the policy triggers that matter — and the server runs an agentic sweep: live web search scoped by a judgment model (Jev), source scoring, and a Markdown briefing you can read from any MCP client.

PT-BR-first, local decision engine for typed decisions at volume.

Find the LLM calls you should move to JEV — scan logs & code for decision-shaped calls, price the migration, calibrate decision models, generate the migration PR. Zero deps, fully local.

Route an agent's intent to the one installed skill that fits, using TypeSafe's Jev

Vendor-neutral SDK for typed decision-making (yes/no, choice, score) — hosted and local

One CLI and Jev-compatible API for local and hosted typed-decision backends (planning)

Every new Chrome tab sorts itself into the right tab group in ~150ms using Jev (TypeSafe). Bring your own key. MV3, no dependencies, MIT.

衆目 / THE HUNDRED EYES — Interactive media art with Jev Choice + Score: one post, 100 fictional perspectives, four amplified voices, then the whole audience.

Tool-agnostic System One decision orchestration skill for AI coding agents, with optional TypeSafe, Jev MCP and CodeGraph integrations.

A security-focused, idiomatic Go client for TypeSafe’s System One API. Community-maintained; not an official TypeSafe SDK.

No project description available.

Research and scaffolding for a TypeSafe Jev MCP server

A type-safe Go SDK for building reliable integrations with strongly typed APIs. Designed to provide an idiomatic developer experience, compile-time safety, and convenient abstractions while reducing boilerplate and preventing common runtime errors.

Typed AI decisions for .NET: ask Jev (TypeSafe AI System One) yes/no, choice and score questions and get a C# enum with calibrated probabilities back.

Turn messy state into typed, auditable classifications, scores, and policy decisions over REST and MCP.

No project description available.

Jev-compatible adapter for vLLM: use any vLLM-served LLM for Choice, Score, and Noul decisions via logprobs—without modifying the model or vLLM service.

Jev for your X. XFlow is a Manifest V3 browser extension powered by Jev, with customizable filtering policies for a cleaner, more personalized X timeline. 专为 X 打造的 Jev。XFlow 是一款由 Jev 驱动的 Manifest V3 浏览器扩展，提供可自定义的过滤策略，助您打造更清爽、更个性化的 X 时间线。

Add as much tabular data as you want to Jev models using adaptive ensembles that learn to query only the rows and columns needed.

IntentFlags — semantic feature flags for websites, powered by Jev. Infers what a visitor is trying to do and hands it to your React code as a flag.

Copy the most winning ads and have a synthetic focus group.