An open-source, commercially hosted generative-engine-optimization platform that uses Jev judgments within a broader application to track brand mentions and placement in AI answers across ChatGPT, Claude, Gemini, and Perplexity.
Runs buyer prompts across AI engines and compares mention rates, recommendation positions, and share of voice by engine, prompt, and language.
Ships a REST API, an MCP server at mcp.usenotra.com/mcp, and the @usenotra/geo traffic SDK with Next.js, Nuxt, Astro, and SvelteKit integrations.
The @usenotra/geo SDK distinguishes training crawlers, search indexing, assistant browsing, and human referrals from AI answers.
A Bun and Turborepo monorepo of TypeScript, Next.js, React, Hono, PostgreSQL, and Drizzle ORM with a dashboard, public API, docs, and agents.
Local development uses Bun 1.4.0, Node.js 24.11.1, and PostgreSQL; the committed migration chain is not a complete bootstrap for an empty database.
Quickstart
bash
bun install
cp .env.example .env
bun run dev --filter=dashboard
Watch out
AGPL-3.0. Commercially hosted and paid; local development needs Bun 1.4.0, Node.js 24.11.1, PostgreSQL, WorkOS AuthKit credentials, and provider keys, and the Jev usage sits within a broader application.
A multiplayer triage dashboard for public GitHub repos: issues and PRs sync into Postgres, Rocicorp Zero replicates them live, and Jev answers typed questions about each one, including what a maintainer should do next, with human corrections kept.
An MCP server and agent skill that verifies coding-agent work by driving the real running app and returning pass, fail, or couldn't-tell verdicts with the file:line to fix; its listing frames the approach as Jev-style machine-native runtime perception.
A local SQLite memory layer for CLI agents with an opt-in Jev reranker that batches Noul judgments over the top 40 recalled memories and falls back to a local cross-encoder on errors.
cua open sourced a 706k param model that fills a whole form in one 50ms pass
the llm agent doing the same form took 23 turns and 39.6 seconds
the specialists are going to eat the generalists from the bottom
Cua
@trycua
1/ Introducing CUA-S1: a family of System One Models, small, specialized, and built for computer use.
Today we're open-sourcing CUA-S1-FORMS, the first in the family: github.com/trycua/cua
I've been using Jev by @typesafeai Here's the six things i've tried and am confident I'll still use Jev for 60 days from now.
There's many more experiments, ideas, and things I think I will use it for. It's a big deal (more on why in next post).
But I am only sharing thingsShow more
This made me rethink where AI actually fits into security engineering.
For purely engineering work, forget about ChatGPT or Claude.
TypeSafe AI just released Jev, and I think it’s going to change how we build AI into security workflows.
Instead of asking an LLM to “investigateShow more
TypeSafe AI
@typesafeai
we are officially out of stealth! join the frontier and get access to Jev on our website (link on profile)