Foundry
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Ship your backlog with the team you already have.

Foundry puts a fleet of AI coding agents on your GitHub issues. They work around the clock, test every change against a copy of your data, and hand your engineers pull requests to review.

Book a walkthrough How it works

How it works

Your team decides what gets built and what ships. Foundry does the work in between.

  1. Issue

    Your team labels a GitHub issue as ready.

  2. Build

    A free agent machine claims it and writes the code on its own branch.

  3. Test

    Separate agents write and run tests against a copy of your data. Failures go back to build.

  4. Pull request

    Work that passes is opened as a pull request.

  5. Review

    Your engineers review it and decide what ships.

Why not just use a coding assistant?

Assistants make one engineer faster on one task. Foundry works through the whole queue at once, with nobody at the keyboard.

Coding assistant Foundry
Tasks at once One Many, each in its own VM
Hours Only when prompted Around the clock
Testing Up to you Separate test agents on every change
Record Chat history Every task, change and result logged

What teams use it for

The internal tools and automations that sit on the wish list because nobody has time to build them.

  • Invoice and document processing
  • In-house tools that replace SaaS subscriptions
  • Data pipelines, reconciliation and reporting
  • Integrations between the systems you already run
  • Bug fixes, upgrades and test coverage
  • Internal AI tools built on your own data

Built for sensitive data

You decide where the fleet runs and what it can reach.

Your hardware or ours
Run it on-premises, reachable only from your network, or on dedicated rented machines.
Isolated by task
Every task gets its own VM and its own copy of the data it needs.
No secrets in code
Credentials are supplied at run time and never written to the repository.
Full audit trail
Every task, change and test run is logged.
Local models
For data that can't leave your network, agents can run on models hosted on your own machines.

Start with a pilot

We'll run a small fleet on a real project from your backlog, so you can judge Foundry on actual pull requests.