Swimm

Swimm is an AI-powered developer documentation assistant that provides contextual, on-demand answers to complex coding questions as if from your most experienced engineers. It analyzes your existing codebase, performs static analysis to surface relevant context, and captures internal developer knowledge to keep Swimm documents up to date. This enables developers to quickly find accurate information without interrupting senior engineers, improving productivity and code quality.

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How Swimm works

1. Contextual answers: The Swimm Engine analyzes your codebase and generates context-aware responses tailored to your project and language.
2. Static analysis: It performs static analysis to surface information about code you may not fully understand or document well.
3. Knowledge capture: Internal knowledge about code logic is stored in Swimm documents, enabling /ask to deliver accurate answers and improve over time.

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Use cases

• Quick answers to difficult coding questions without pinging senior engineers
• Understanding legacy codebases through contextual explanations
• Keeping project documentation in sync with code changes
• On-demand tour and discovery of relevant code components
• Integrations with existing DevOps and IDE workflows

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Integrations & Ecosystem

• GitHub app
• VS Code plugin
• JetBrains plugin
• Documentation platform with AI-ready code support

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How to Use Swimm

1. Integrate Swimm with your codebase (GitHub, GitLab, or other repo host). Install the Swimm app or plugins for your IDE.
2. Ask contextual questions using the /ask command or via the Swimm UI to get answers tied to your codebase.
3. Browse captured knowledge through Swimm documents to quickly understand complex modules.

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Safety and Best Practices

• Use Swimm as a supplementary knowledge source; always validate critical changes in code reviews.
• Ensure access controls are in place so sensitive information is not exposed in public documentation.

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Core Features

• Contextual answers tailored to your codebase and language
• Static analysis to surface poorly documented or obscure parts of the code
• Internal knowledge capture to keep documentation up to date
• Developer-first design that minimizes interruptions to senior engineers
• Integrations with GitHub, VS Code, JetBrains, and other popular tools
• AI-ready documentation platform for scalable knowledge management