All builds

Evidence-driven frontend QA built on Jev Ultrafast and Browser Harness, with a synthetic todo demo.

Fast structured Android control loops with TypeSafe Jev and Mobile MCP.

Hybrid browser harness: an LLM turns goals into verifiable subgoals, Jev chooses each action and DOM field, Playwright acts.

MacOS computer use driven by Jev (TypeSafe System One) as the decision maker.

Drives a real browser with Jev making every decision and Vercel's agent-browser performing every action, with a benchmark.

Browser agent where Jev selects actions, an LLM reads and plans, and answers cite page evidence.

2D autonomous car simulation in the browser, driven by TypeSafe's Jev decision model.

TypeScript browser agent for ego lite: Jev Ultrafast indexed actions, TypeSafe Jev decisions, persistent observe/act CLI. No Chrome or Playwright.

ACP and MCP adapter that bridges TypeSafe Jev with any LLM — computer use and typed decisions alongside Codex, Claude, Grok, and OpenCode.

Browser automation where an LLM plans and Jev (Typesafe System One) decides. Library, CLI and MCP server.

🧹 Fun project: a Chrome extension that asks a tiny AI decision model (TypeSafe Jev) "is this DOM element an ad?" and pops it off the page. BYOK, no backend, not a real ad blocker.

Chrome extension: vibe-check your X posts with TypeSafe's Jev before you hit Post.

Control a real browser by voice. Jev (TypeSafe System One) decides intent + target in ~300 ms per spoken word; Playwright acts — often before you finish the sentence.

5–10x faster browser operations: Jev clicks, Codex thinks and verifies. Built at EZCollegeApp.

WXT browser extension: Jev-powered page clutter removal with reusable template rules.

Browser use using Typesafe's Jev model.

Standalone Android agent for Mobilerun where Jev makes every decision, with a live React studio and an Uber demo.

Browser Use's ultrafast agent: Jev picks the operation and DOM element in one request; a small LLM only writes text when typing is needed.

Pi coding-agent extension built on the TypeSafe AI System One API (Jev).

Autonomous Jev pull-request review with typed decisions, calibrated approval gates, and trusted-owner escalation.

Jev-powered model-judged permission gate for OMP (TypeSafe System One).

A CLI and GitHub Action that assesses code-change risk using deterministic rules and TypeSafe Jev, recommending checks and reviewers before merge.

A flexible and configurable CLI model router using TypeSafe Jev.

A pi extension that exposes TypeSafe (Jev, System One) judgments as five pi tools, so a model can make narrow semantic judgments while your code and your users keep control of thresholds, weights, and actions.

Single-agent Pi coding coprocessor with Jev semantic gates, baseline-to-current diff review, and append-only observability telemetry.

MCP server exposing TypeSafe System One judgments (noul, choice, score) as agent tools.

Guardrail + model router for LLM gateways on TypeSafe's Jev (System One model), with an independent accuracy/calibration/latency evaluation. Stdlib Python.

TypeSafe AI (Jev) adversarial reviewer and typesafe_ask tool for the omp coding agent.

Utilizing Jev, the RLCD-type model provided by TypeSafe AI, to independently and cheaply judge agentic coding sessions.

Predict another skill's next closed decision with TypeSafe Jev — without running that skill.

Uses typeful jev, zero sync to pull and sync large repositories for issue triage.

Per-prompt capability router for coding agents: resolves installed skills, MCP servers, agents and commands against your prompt via TypeSafe Jev, and measures whether the injection actually helps.

Grounded GitHub and crates.io discovery CLI and MCP server that uses Jev to score architectural fit, licensing, and maintenance.

Sub-second pre-commit and pre-push semantic gate that screens staged diffs with Jev.

Type-safe model router. Jev (System One) banks each request to a typed catalog route.

Cut Claude Code's skill manifest by ~75% with TypeSafe Jev. Scores every installed skill for relevance and hides the rest via skillOverrides — 12,750 → 3,185 tokens on a 217-skill install, for $0.0009 a session.

Automated database migration safety reviewer powered by TypeSafe AI (Jev System One model).

Build versioned judgment functions on TypeSafe's Jev once, then call the same published version from your backend over HTTP and from coding agents over MCP. The vendor key stays on your machine.

Shift every LLM call to the cheapest model that can handle it. Routing decided by TypeSafe Jev in ~180 ms. No training data. Policy in plain YAML. TypeScript and Python.

Semantic MCP firewall powered by Jev — screens every tool call, tool result, and tool description with calibrated System One verification. 94% block recall, 0 false positives, ~$0.00002/check.