Kelu vs Cody (Sourcegraph)
Cody is Sourcegraph's in-IDE coding assistant — it lives in your editor and reasons about your codebase. Kelu is a docs and support assistant that answers questions from your docs, wikis, and tickets across every surface (widget, Slack, Discord, Teams, MCP, helpdesk). Different jobs; many teams use both.
Feature comparison
Information about Cody is drawn from Sourcegraph's public product pages.
Where Kelu focuses differently
Different jobs, not competitors
Cody helps an engineer at your company navigate and write code inside the IDE. Kelu helps your customers (or your own employees) get cited answers from docs, wikis, and tickets — on your website, in Slack, in the helpdesk. Both can coexist; most teams use both for what each does best.
Where Kelu reaches that Cody doesn't
Customer-facing widget on your docs, form deflection before a ticket is filed, agent copilot inside your helpdesk, community bots in Slack/Discord/Teams, MCP endpoint so AI IDEs (including Cursor and Claude) can retrieve your docs. Cody is an IDE tool by design; Kelu is the docs-and-support assistant layer.
Where Cody reaches that Kelu doesn't
Symbol-level code understanding, in-line code completion, refactoring assistance, IDE-native context. If your primary need is 'help engineers write code faster', Cody is purpose-built for it. Kelu indexes READMEs and docs/, not full code — different retrieval story.
How they complement
Cody knows your code; Kelu knows your docs. When an engineer asks 'how do I use our payment SDK?', Cody can inspect the SDK code; Kelu can retrieve the docs that explain the intended usage patterns. Together they cover both sides of the developer-experience story.
Frequently asked questions
Do I need to choose between Cody and Kelu?
Usually not. They solve different jobs. Cody is an IDE-native coding assistant that reasons about your codebase; Kelu is a docs-and-support assistant that answers questions from your written knowledge across every surface. If your primary need is 'help engineers', evaluate Cody; if it's 'help customers or non-engineer employees find answers', evaluate Kelu.
Can Kelu answer code questions?
It can answer docs-shaped questions about your code — 'how do I use the pagination endpoint', 'what are the config options for X', 'what's the retry policy'. It cannot navigate arbitrary code files or complete code the way Cody can. The right split is: docs questions to Kelu, code understanding to Cody.
Can Cody replace an in-IDE docs assistant?
Cody's context is your codebase. For docs-shaped questions grounded in your published documentation, Kelu's MCP server (usable from Cursor, Claude Desktop, ChatGPT MCP) is the docs-side answer.
How does pricing compare?
Cody has a free tier and Pro at $9/user/month; Kelu has a free tier and Pro at $99/month flat (not per-seat). Different unit — Cody bills per-developer for IDE access; Kelu bills per-workspace for the assistant behind the widget / bots / helpdesk.
Do you index code the way Sourcegraph does?
No — deliberately. Kelu indexes the docs *inside* your repos (READMEs, docs/, ADRs, changelogs) not the source code itself. Full-code indexing is Sourcegraph's specialty; docs-and-support indexing is ours.
See for yourself
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