Self-Hosted AI Code Review
Most AI code review tools are closed SaaS: you connect your repositories, and your code is sent to their servers, processed by their pipeline, and forwarded to their choice of model provider. For a lot of teams that's fine. For others — regulated industries, security-conscious startups, companies with strict data-residency rules, or anyone who simply doesn't want their proprietary source leaving their network — it's a dealbreaker.
Self-hosted AI code review solves this by letting you run the entire review system on infrastructure you control. This guide covers why teams choose it, what it actually protects you from, and what to look for.
What "self-hosted" really means
Self-hosting means the code review application runs in your environment — your cloud account, your VPC, your on-prem servers — instead of a vendor's. When a pull request opens, the diff and repository context are processed by software you deployed, and you decide where the model inference happens.
That last point matters. A truly self-hostable AI reviewer is model-agnostic: you can point it at a commercial API like OpenAI or Anthropic if you're comfortable with their data terms, or at a model running entirely inside your own network. The decision about where your code goes stays with you, not the vendor.
Why teams choose self-hosted code review
Data control and privacy
The obvious reason: your source code never touches a third party you didn't explicitly choose. For companies whose code is the product, or whose contracts forbid sharing customer-adjacent code, this is the whole ballgame. With self-hosting plus a local model, your code can be reviewed without a single byte leaving your infrastructure.
Compliance and data residency
Regulations like GDPR, HIPAA, SOC 2 commitments, and government data-residency rules often constrain where data can be processed and stored. Self-hosting lets you keep everything in a specific region or network segment and produce a clean answer to "where does our code go during review?" — namely, nowhere we don't control.
No vendor lock-in
Open-source, self-hosted tools don't disappear when a startup pivots or gets acquired, and they don't hold your workflow hostage to a pricing change. You can read the source, fork it, patch it, and run the exact version you've audited.
Cost control at scale
SaaS review tools usually price per seat or per repository. If you're a large org, running the software yourself and supplying your own model capacity can be substantially cheaper — and you can choose cheaper models for routine reviews and reserve expensive ones for critical paths.
The trade-offs to weigh
Self-hosting isn't free in effort:
- You own the operations. Deployment, upgrades, monitoring and uptime are yours. A good project keeps this light with containers and clear docs, but it's still work.
- You supply the model. Either an API key with its own costs, or the hardware to run a local model well enough for quality reviews.
- You do your own scaling. Bursty PR traffic is your problem to capacity-plan.
For many teams the control is worth it. For others, a hosted option with strong data terms is the pragmatic choice — which is why the best tools offer both and let you switch.
What to look for in a self-hosted AI code reviewer
If you're evaluating options, check for:
- Model-agnostic design — bring your own provider, including local models, with no lock-in.
- Straightforward deployment — containerized, documented, runnable without reverse-engineering.
- Repository-aware reviews — full pull-request context, not just the raw diff. (We cover why this matters in what is AI code review.)
- Configurable, so the reviewer enforces your standards, applied consistently.
Where Scopy fits
Scopy is an open-source AI code reviewer built to be run either way. The full source is on GitHub for you to read, fork and deploy. It's model-agnostic — connect OpenAI, Anthropic, a compatible API, or a local model, with no lock-in. And when you'd rather not run infrastructure at all, Scopy gives you a Cloud option with the same reviews as a managed service.
That means you can start in the cloud today and self-host later, or self-host from day one and keep your code entirely on your own machines. Either way you get repository-aware reviews and your own custom review rules — without surrendering control of your source.
Ready to dig in? Start with what AI code review is and how it works, or view Scopy on GitHub to self-host it yourself.