Sourcegraph

Code search and AI assistance across large, multi-repository codebases

AI Coding & DevelopmentFree planOverseasβ˜…β˜…β˜…β˜…β˜† 4.0

What is Sourcegraph?

Sourcegraph indexes source code across many repositories and languages, so you can search for a symbol, a pattern or a regular expression and get results with structural understanding rather than plain text matches. That index is what makes it useful at scale: finding every caller of a function, tracking how a deprecated API is used, or planning a migration across hundreds of repositories. Cody, its assistant, draws on the same index for context, so answers reference real code from your organisation. It is available as a managed service or fully self-hosted, which is often the deciding factor for large enterprises.

Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.

Key features

  • Cross-repository code search with structural and regex queries
  • Symbol and reference navigation across many projects at once
  • Cody assistant grounded in your own indexed codebase
  • Batch changes for large-scale automated refactoring
  • Managed cloud or self-hosted deployment options
  • Integrations with major Git hosts and common code editors

Pros & cons

Strengths

  • Search across hundreds of repositories in one query
  • AI answers use real organisational code as their context
  • Batch changes make organisation-wide refactors tractable

Watch out for

  • Indexing infrastructure is non-trivial to run yourself
  • Value scales with codebase size, so small teams gain less
  • Enterprise pricing puts it out of reach for hobby projects

Best for & use cases

large codebases, code migrations, enterprise search, refactoring at scale and code intelligence

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FAQ

When is it worth the effort?

Once a codebase spans enough repositories that nobody can hold it in their head. Below that threshold a standard editor search is usually sufficient and the indexing overhead is hard to justify.

Does the AI require sending code to a vendor?

Not necessarily. Self-hosted deployments keep the index and the assistant inside your network, and the assistant can be configured with different model backends, which is why regulated organisations look at it.

What are batch changes?

A way to apply one code modification across many repositories as reviewable pull requests rather than manual edits. It is the feature that makes organisation-wide refactors realistic.