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Getting Started Platform Architecture Overview

Welcome to the GitDocAI platform architecture overview. This guide provides a high-level look at how our system is designed, helping you understand the underlying technical components, data flow, and security layers that power your documentation experience.

High-Level Architecture

The GitDocAI platform is built on a modern, scalable architecture divided into three primary layers: the frontend interface, backend services, and the data storage layer.

flowchart TB
    User((User))
    
    subgraph "Frontend Layer"
        VE["Visual Editor"]
        Dashboard["Admin Dashboard"]
    end
    
    subgraph "Core Services"
        API["Core API"]
        Auth["Access Control and Security"]
        Billing["Billing and Plans"]
        AI["AI Processing Engine"]
    end
    
    subgraph "Data Layer"
        DB[("Data Models and Storage")]
    end

    User --> VE
    User --> Dashboard
    VE --> API
    Dashboard --> API
    Dashboard --> Auth
    
    API <--> Auth
    API <--> Billing
    API <--> AI
    API <--> DB

Core Components

Our architecture is modular, ensuring that each component can scale independently while maintaining a seamless experience for your team.

Visual Editor Architecture

The Visual Editor is the primary interface for creating and managing documentation. It relies on a block-based architecture that allows for real-time rendering, collaborative editing, and seamless integration with your content.

Data Models & Storage

Content is structured using robust data models that ensure consistency across your documentation. We separate raw content from metadata (like tags, authors, and reading times) to optimize retrieval and search performance.

AI Processing Engine

The AI engine is deeply integrated into the backend. It handles automated documentation generation, intelligent search indexing, and context-aware content suggestions without blocking the main user interface.

Security and Access Control

Security is a foundational element of the platform. The system handles access at multiple levels to ensure your data remains protected.

  • Authentication: All requests to the Core API require valid authentication tokens. We support secure session management and standard authentication flows.

  • User Roles & Permissions: Granular access control allows you to define exactly who can view, edit, or manage specific documentation sections.

  • Public vs. Private Documentation: The routing layer dynamically checks permissions to serve public pages globally while restricting private content to authenticated users with the correct roles.

When setting up a new project, we recommend configuring your user roles and permissions before inviting your broader team to ensure everyone has the correct level of access from day one.

Typical Data Flow

Understanding how data moves through the system can help you conceptualize how your documentation is saved and processed.

  1. 1

    User Action

    A user makes a change in the Visual Editor or triggers an AI generation request.

  2. 2

    Authentication Check

    The request is routed through the Access Control layer to verify the user's identity and confirm they have the necessary permissions.

  3. 3

    Processing

    The Core API processes the request. If AI generation or billing validation is required, the API communicates with those specific microservices.

  4. 4

    Storage and Response

    The updated data model is saved to the Data Layer, and a success response is returned to the frontend to update your screen in real-time.

For detailed specifications on integrating directly with our backend, please refer to the API Reference section of the documentation.