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SAFA
Complete Software Documentation at the Click of a Button

What is SAFA?

SAFA provides an innovative solution for automated software documentation generation and maintenance. The platform reads code and its related context to create natural language summaries, system documentation, and change logs, while maintaining traceability across various documentation sources.

The platform offers programming language-agnostic capabilities, including AST extraction, interactive knowledge graphs, and system visualizations. It streamlines documentation processes by automatically generating user stories, requirements, and change summaries, all while keeping documentation synchronized with code changes.

Features

  • Generated Code Summaries: Automatic creation of natural language code summaries with AST extraction
  • Document Generation & Maintenance: Automated creation of user stories, requirements, and change logs
  • Change Analysis & Summarization: Natural language descriptions of system evolution
  • Relationship Generation: Traceability across documentation sources and code bases
  • System Visualization & Search: Interactive knowledge graphs and system visualization tools
  • Jira Integration: Relationship mapping with Jira tickets

Use Cases

  • New developer onboarding
  • Software documentation maintenance
  • Code change tracking and analysis
  • Compliance documentation
  • System architecture visualization
  • Engineering team collaboration
  • Project management oversight
  • Regulatory compliance tracking

FAQs

  • Which programming languages does SAFA support?
    SAFA is programming-language agnostic, meaning it supports documentation generation for any programming language.
  • How much does it cost per code file?
    The self-service document generation costs $0.35 per code file, with free project and code summaries included.
  • Does SAFA integrate with version control systems?
    Yes, SAFA currently supports GitHub integration for self-service document generation.

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SAFA Uptime Monitor

Average Uptime

99.72%

Average Response Time

183.33 ms

Last 30 Days

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