Why Self-Hosted AI Code Review Matters for Your Team

Every AI code review tool needs to read your source code. The question is: where does that happen?

Most hosted AI code review services work by receiving your diffs via webhook, sending them to an LLM provider, and posting comments back to your PR. Your code travels through at least two external services before you see a result.

For many teams, this is a dealbreaker.

The Data Flow Problem

When you use a hosted code review service, here's what happens to your code:

Your Git provider sends the diff to the review service
The review service sends the code to an LLM API (OpenAI, Anthropic, etc.)
The LLM processes the code on their infrastructure
Results flow back through the review service to your PR

At minimum, two external companies see your source code. Depending on the service, there may be caching, logging, or training data collection along the way.

What's at risk?

Proprietary logic — business-critical algorithms and trade secrets
Security-sensitive code — authentication flows, encryption implementations, access control
Credentials — API keys, tokens, and secrets that appear in diffs (it happens)
Compliance data — code that handles PII, financial data, or health records

Compliance Requirements

For teams in regulated industries, sending source code to third parties creates compliance complications:

SOC 2 — requires documented data flow and third-party risk assessments for every service that touches sensitive data
HIPAA — if your code processes health data, sending it to external services may require a BAA with each provider
GDPR — European teams need to verify data residency and processing agreements
Financial regulations — banks and fintech companies often have blanket prohibitions on sending code externally

Even if a hosted service offers a BAA or DPA, you're still adding links to your compliance chain. Self-hosting eliminates the question entirely.

The Self-Hosted Alternative

With a self-hosted code review tool like Reviewate:

Your code stays in your network — the tool runs on your infrastructure, processes code locally, and only makes outbound API calls to your configured LLM provider
You choose the LLM — use OpenAI, Anthropic, Google, or any OpenAI-compatible API. Run a local model if you need fully air-gapped operation
You control the logs — no telemetry, no analytics, no data leaving your environment
You own the configuration — tune review behavior, set per-repository rules, and customize the pipeline

Deployment Options

Reviewate is designed for two deployment patterns:

Docker Compose — multi-service deployment, minimal setup:

git clone https://github.com/numberly/reviewate.git
cd reviewate
cp .env.example .env
# Edit .env with your credentials
docker compose --profile all up -d

This starts the full stack: backend, frontend, PostgreSQL, and Redis.

Kubernetes — production-grade with scaling. See the Kubernetes deployment docs for full configuration including high availability and enterprise setups.

Bring Your Own LLM

Self-hosting the review tool is only half the picture. You also need to control where the LLM inference happens.

Reviewate supports any LLM provider with an OpenAI-compatible API:

Cloud APIs — OpenAI, Anthropic, Google Gemini, or OpenRouter (your existing enterprise agreement applies)
Self-hosted models — vLLM, Ollama, or any OpenAI-compatible API

This means you can configure the entire data flow to stay within your infrastructure, or use your existing cloud provider agreements without adding new third parties.

The Cost Question

Self-hosting adds operational overhead. You need to:

Maintain the deployment (though the Docker Compose setup is straightforward)
Monitor uptime and resource usage
Handle updates and upgrades

For teams already running Kubernetes, the marginal cost is close to zero. For smaller teams, the Docker deployment takes about 10 minutes to set up.

The LLM API costs are the same whether you self-host the review tool or use a hosted service — you're paying per token either way. The difference is that you're not also paying a SaaS fee on top.

Open Source Transparency

Reviewate is licensed under AGPL v3. This means:

Full source code visibility — audit every line of code that touches your source
No vendor lock-in — fork, modify, and run your own version
Community contributions — benefit from improvements by the open-source community
No surprise changes — a hosted service can change their data practices; open-source code is immutable once you've audited it

Ready to keep your code in your network? Deploy Reviewate in minutes or browse the source on GitHub.