Sourcegraph Cody vs GitHub Copilot Enterprise — AI for a large codebase
At enterprise scale the question stops being completion quality and becomes which tool can see enough of your code to be useful. Cody's answer is a search engine; Copilot's is the platform your code already lives on.
AI Tools Hub Editorial · published · updated
Different theories of context
Cody inherits Sourcegraph's Code Search, which was built to index and search across many repositories. That is a genuine advantage when an engineer's work spans a dozen services and the relevant example lives in one of them.
Copilot Enterprise builds context from the GitHub platform — your repositories, pull requests, discussions. If everything is in GitHub, that is an enormous amount of context available without any additional system.
Side by side
| Cody Enterprise | Copilot Enterprise | |
|---|---|---|
| Context source | Sourcegraph index across repositories | GitHub platform |
| Editors | VS Code, JetBrains and others | VS Code, JetBrains, Visual Studio, Neovim |
| Requires | A Sourcegraph deployment | GitHub Enterprise |
| Self-hosting | Yes | Via GitHub Enterprise Server |
| Certification | SOC 2 Type II | SOC 2 Type II, ISO 27001 |
| Best when | Code is spread across many repositories | Everything runs through GitHub |
The practical determinant
Do you already run Sourcegraph? If yes, Cody is a natural extension of a system your engineers already use, and the marginal cost is low. If no, standing up Sourcegraph to get Cody is a significant project that needs its own justification.
If your organisation is on GitHub Enterprise and does not have a cross-repository search problem, Copilot Enterprise is the shorter path to the same outcome.
Can we run both?
Technically yes, and it is rarely worth the licence cost. Pick based on where your context problem actually is.
What about Cursor for enterprise?
Cursor Business exists, but the VS Code fork requirement and the lighter governance tooling make it a harder sell at this scale.
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