Keeping source code private: how self-hosted AI coding agents work

Most AI coding tools ship your code to a shared cloud. A self-hosted, single-tenant agent keeps source, prompts, and keys inside your own network. Here is how that architecture works and when it matters.

Most AI coding tools are multi-tenant SaaS: your source code, your prompts, and the generated output travel to a vendor's shared cloud to be processed. For a lot of teams that is fine. For anyone under compliance rules — or anyone who simply doesn't want their codebase sitting in a third party's logs — it is a non-starter. A self-hosted AI coding agent answers that by running inside your own infrastructure, so nothing crosses your network boundary.

The core guarantee

Under a properly self-hosted model, no source code, developer prompts, API keys, or generated responses ever leave your perimeter. Your walls, your keys, your data.

Self-hosted vs. single-tenant — not the same thing

These terms get used interchangeably, but they answer different questions:

  • Self-hostedwhere it runs. On your own servers, in your own network, rather than a vendor's cloud.
  • Single-tenantwho shares it. One dedicated deployment for your organization, with no pooled control plane and no shared data with other customers.

automatedev.ai is both: one deployment per organization, running inside your walls. There is no shared backend quietly aggregating everyone's activity.

What actually has to stay inside the boundary

"Private" is only meaningful if every sensitive artifact stays in. That means the code the agent reads and writes, the prompts and context sent to the model, the model API keys, and the generated diffs and logs. A tool that keeps your repo local but ships prompts full of your code to a cloud model hasn't actually solved the problem.

Bring your own model & keys

A vendor-neutral provider factory lets you run your chosen engine with your own API keys, held in your own secrets store — not the platform vendor's.

Pluggable secrets

Use a HashiCorp Vault adapter, or a built-in encrypted store if you don't run Vault. Keys never live in plaintext config.

Offline licensing

A signed license validated locally — no phone-home — so it works in network-restricted and air-gapped-leaning setups.

Per-run isolation

Each task runs in its own isolated workspace, so concurrent runs stay separate and every change is reviewable on its own.

When self-hosting is worth the trade-off

Self-hosting is not free: you run the infrastructure and you own the upkeep. It earns its keep when you have real reasons code can't leave — regulated industries, customer contracts that forbid third-party processing, or proprietary IP you won't expose. If none of that applies, a cloud tool may be simpler. If it does apply, the deployment model is the deciding factor, and no amount of model quality substitutes for it.

Private, but still the whole job

Keeping code private shouldn't mean settling for autocomplete. A self-hosted agent can still run the full loop — plan, build, test, review, secure, and open a pull request — entirely inside your network, with a human approving at every gate. Privacy and capability are not a trade-off here.

Run AI coding agents inside your own walls.

Book a 30-minute demo to see the self-hosted, single-tenant deployment — your code, keys, and data never leave your network.

Book a 30-minute demo