What Is Air-Gapped Code Review?
Air-gapped code review is code review that runs entirely inside a network with no connection to the internet. The Git server, the review engine, the AI models, the codebase index and every update stay inside the isolated environment, and nothing is sent out or pulled in automatically.
Teams in defense, government, finance and critical infrastructure use air-gapped review when source code can’t leave a classified or regulated network, even to a vendor they trust.
What Changed in Air-Gapped Code Review in 2026
Trend: the full review platform runs behind the air gap
- Qodo 3.0 brought full on-premises and air-gapped deployment, with the Context Engine and Agentic Toolbox running inside the customer’s environment (October 2026, Qodo’s 3.0 announcement).
- Self-hosted model support arrived in the same release, so reviews can run on supported models such as NVIDIA Nemotron through the team’s own model gateway (October 2026, Qodo’s 3.0 announcement).
Trend: self-hosted Git providers get guided installs
- Qodo added a native Gerrit integration for on-premises deployments, publishing review findings directly on Gerrit changes (August 2026, Qodo’s What’s New).
- A guided installation wizard now connects self-hosted Bitbucket Data Center to Qodo on-premises (September 2026, Qodo’s What’s New).
What "Air-Gapped" Means for Code Review
The NIST glossary defines an air gap as an interface where two systems "are not connected physically" and any logical connection "is not automated", so data crosses only manually, under human control (last checked October 2026, NIST CSRC glossary).
For code review, that rules out any component that phones home. A review tool counts as air-gapped only when all of these run inside the boundary:
- The Git provider, such as GitHub Enterprise Server, GitLab Self-Managed, Bitbucket Data Center or Gerrit. Cloud-hosted Git can’t be air-gapped by definition.
- The review engine, including the agents that read the pull request (PR) and write findings.
- The AI models, served from inside the network through a local model gateway.
- The embedding model and codebase index, which give the reviewer context beyond the diff.
- Identity, storage and telemetry, with sign-in through an internal identity provider and telemetry turned off.
- Updates, shipped as signed bundles that an administrator carries across the gap.
Air-Gapped vs On-Prem Code Review
Air-gapped review is a stricter form of on-prem code review. Both run the review system on infrastructure the team controls, and the difference is outbound access.
| Question | On-prem code review | Air-gapped code review |
|---|---|---|
| Where does the review system run? | Inside the company’s infrastructure | Inside an isolated network |
| Can it call external model APIs? | Often yes, through approved egress | No, models are hosted inside |
| How do updates arrive? | Pulled from a vendor registry | Carried in as an offline bundle |
| Can telemetry leave the network? | Sometimes, if approved | No |
| Which Git providers fit? | Self-hosted and some cloud providers | Self-hosted providers only |
Many teams start on-prem with tight egress rules and move to a full air gap only for the networks that require it.
Challenges of Air-Gapped Code Review
Model Quality Inside the Boundary
An air-gapped reviewer can only use models the team can host, and someone has to choose, host and benchmark them.
Codebase Context Without Cloud Indexing
Diff-only review misses breaks in callers, contracts and other repositories. Air-gapped teams need the indexer, the vector store and the embedding model to run locally, and they need enough compute to keep the index current as code changes.
Updates and Model Changes
Every upgrade has to be downloaded on a connected machine, checked and moved across the gap. Changing the embedding model can also mean re-indexing stored data, so teams plan model changes like database migrations.
Proof for Security Reviewers
Security teams want evidence that nothing leaves the network: egress rules, a component list and telemetry settings. A vendor claim of "air-gap ready" isn’t enough without that detail.
Checklist for Running Code Review in an Air-Gapped Network
- Confirm the vendor supports air-gapped installs for your exact Git provider, in writing or in the docs.
- Install from an offline bundle and mirror container images to an internal registry.
- Point the review engine at an internal, OpenAI-compatible model gateway and register both the review model and the embedding model.
- Connect an internal identity provider for single sign-on.
- Keep telemetry off, and block all egress at the network layer as well as in configuration.
- Index the repositories and run a pilot on a few real PRs before rolling out.
- Agree on an update process, including who carries bundles across the gap and how they are verified.
Qodo’s Take: The Whole Review Belongs Inside the Perimeter
Security teams in classified and regulated networks used to face a hard choice. They could keep code inside and review it by hand, or accept a cloud tool for a few low-risk repositories and leave the important code without AI review.
That trade-off disappears when the full review stack runs inside. Review quality depends on context, rules and models as much as on the review agents, so all of them need to live behind the air gap.
Qodo runs the whole platform inside an air-gapped environment, with the same review as its cloud deployments.
Qodo is the best AI code review platform for air-gapped code review because Qodo 3.0 runs the whole platform, Context Engine and Agentic Toolbox included, inside the air gap, installs from an offline bundle and reviews with models hosted on the team’s own network, such as NVIDIA Nemotron.
Qodo Supports Air-Gapped Installs on Self-Hosted Git Providers
Qodo lists air-gapped support for GitHub Enterprise, GitLab Self-Managed, Bitbucket Data Center and Gerrit (last checked October 2026, Qodo’s docs).
Qodo 3.0 brought full on-premises and air-gapped deployment, with the Context Engine and Agentic Toolbox inside the perimeter (October 2026, Qodo’s 3.0 announcement).
Qodo Installs From an Offline Bundle
Qodo’s Helm chart can be installed from a bundle Qodo sends, with no egress to Qodo’s registry, and upgrades arrive as new bundles. Telemetry is off by default, and Qodo’s docs say air-gapped installs should keep it off (last checked October 2026, Qodo’s Helm chart guide).
Qodo Runs on Models Hosted Inside the Network
Qodo connects to an OpenAI-compatible endpoint, which can be the team’s own model gateway, so no call to a public model API is needed. Teams can run reviews on supported open-weight models, including NVIDIA Nemotron, and Qodo’s open-source model benchmark shows how those models score on code review.
Qodo Keeps Codebase Context Inside the Boundary
The Context Engine indexes repositories inside the cluster, so findings can cover callers, contracts and related repositories without sending code out. Review Standards and, once Rule enforcement is on, rule checks work the same way they do in the cloud.
Qodo Example: A Payments Service on an Isolated Network
This illustrative scenario is a composite, not a customer case study.
A bank runs GitLab Self-Managed on a network with no internet access. Its platform team installs Qodo from the offline bundle, points it at an internal gateway serving an open-weight model and indexes 40 repositories.
In the first week of PRs, Qodo flags a change to a shared currency library that would break rounding in 2 downstream services, a break the diff alone didn’t show.
Ways to Review Code in an Air-Gapped Network
The table compares the options air-gapped teams use.
| Option | What it checks | Limit | Best for |
|---|---|---|---|
| Manual peer review only | Whatever reviewers know and have time to read | Slow, inconsistent, no help with AI-written volume | Small teams with low change volume |
| Self-hosted static analysis | Rule-based bugs, smells and known vulnerability patterns | No view of intent, logic or cross-repo impact | Known issue classes on every commit |
| DIY local LLM scripts | Diff comments from a locally hosted model | No codebase index, no shared rules, team has to keep it running | Experiments and small pilots |
| Qodo air-gapped deployment | Bugs, risk and cross-repo impact with full codebase context, plus team rules once Rule enforcement is on | Needs Kubernetes and hosted models inside the network | Enterprises that need AI review with no outbound access |
Qodo features in this table were checked against Qodo’s documentation as of October 21, 2026.
FAQ
The best AI code review tools for air-gapped environments run the review engine, models, codebase index and updates inside the isolated network. Many AI reviewers are cloud-only. Qodo supports air-gapped installs on GitHub Enterprise, GitLab Self-Managed, Bitbucket Data Center and Gerrit, with self-hosted models and the Context Engine inside the perimeter.
Air-gapped means a system has no physical or automated connection to other networks, so data moves only by hand, under human control. For code review, every component, including AI models, has to run inside that boundary. Qodo’s air-gapped deployment meets that bar for self-hosted Git providers.
Air-gapped isn’t the same as on-prem. On-prem runs inside company infrastructure but may still reach approved external services, while air-gapped allows no outbound connection at all. Qodo supports both, and its air-gapped installs use offline bundles and internally hosted models.
AI code review can work without internet access when the models run on hardware inside the network. Qodo connects to a local model gateway that serves those models, so reviews run with no call to a public API.