Introduction

An AI testing agent reviewing a web app - reading the code change, running the app, and checking the database

Autonoma is an agentic end-to-end testing platform. Connect your repository and every pull request gets reviewed automatically on a live preview environment - an AI agent exercises your app in a real browser, checks that it still works, and reports back on the PR.

You don’t write or maintain test scripts. There are no selectors to update when a button moves. Autonoma generates a suite of natural-language tests from your codebase, and an agent figures out how to run them - picking elements, making assertions, and healing itself when your UI changes.

How it works

Every pull request runs through the same loop, from opening the PR to a reviewed result:

The Autonoma review loop: pull request, preview environment, seed data, run tests, review on PR

  1. Pull request - you open a PR (or push a change to one).
  2. Preview environment - a preview environment builds an isolated, full-stack preview of your app for that PR and gives it a live URL.
  3. Seed data - the Environment Factory creates fresh, isolated test data so every run starts from a known state.
  4. Run tests - the agent runs your test suite against the preview, exercising the app in a real browser.
  5. Review on PR - Autonoma reviews each run, confirms what passed and what broke, and comments the result back on the pull request.

A pull request page in Autonoma. A red badge reads "1 open bug" beside a note that one environment or scenario issue was found. The headline reads "This PR has open bugs to fix", and the summary underneath says checkout is broken on this PR - the Place order button never enables even with a valid card and address, so no customer can complete a purchase, while cart and add-to-cart still work. Below is the written report, and a Checkpoint history rail on the right lists the latest run as "needs attention" with 1 failed, 2 passed and 1 bug, over an earlier healthy run with 3 passed

That last step is the one you live with day to day: a written verdict on the pull request, the bugs separated from the infrastructure noise, and the evidence for each.

When the PR closes, the preview environment and its data are torn down automatically.

What you set up

Autonoma gets you value in two stages: connect your repo to go live with preview environments and automated PR reviews, then deepen coverage by generating a test suite and wiring up real test data. Three pieces, set up in order:

1. Preview Environments

Install the GitHub app and configure your stack. Every PR then gets a live, isolated preview - and an automated review. This alone gets you live.

Set up Preview Environments →

2. The Planner CLI

Reads your codebase and generates a complete, natural-language E2E test suite - pages, flows, and scenarios. One command.

Run the planner →

3. The Environment Factory

One endpoint in your backend that creates isolated test data before each run and tears it down after, so tests always start clean.

Set up the Environment Factory →

The Environment Factory has an SDK for every major stack - TypeScript, Python, Elixir, Java, Ruby, Rust, Go, and PHP. Copy a working endpoint for yours.

Using these docs with AI

Every page is available as plain text for coding agents. Point Claude Code, Cursor, or Copilot at the file below and it can pull in exactly the pages it needs:

https://docs.autonoma.app/llms.txt

A single complete file with all pages concatenated is also available.

Contributing

Want to run Autonoma locally or work on the platform itself?

Development setup

Clone the repo, install dependencies, and get the platform running locally.

Get started →

Architecture overview

How the monorepo fits together and the key design decisions behind it.

Read the overview →

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