> ## Documentation Index
> Fetch the complete documentation index at: https://dataglue.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Architecture

> Understanding DataGlue's system architecture and data flow patterns.

# Architecture

DataGlue follows a modular architecture designed for flexibility, performance, and privacy compliance.

## System Overview

```mermaid theme={null}
graph TB
    subgraph "Browser Environment"
        A[DataGlue Core]
        B[Storage Layer]
        C[Attribution Engine]
        D[Form Integration]
        E[Dynamic Content]
    end

    subgraph "Data Sources"
        F[URL Parameters]
        G[User Interactions]
        H[Third-party APIs]
    end

    subgraph "Output Destinations"
        I[Forms]
        J[Analytics]
        K[CRM Systems]
    end

    F --> A
    G --> A
    H --> A

    A --> B
    A --> C
    A --> D
    A --> E

    D --> I
    C --> J
    B --> K
```

## Core Components

### Storage Layer

* **localStorage**: Persistent user data
* **sessionStorage**: Session-specific data
* **Cookies**: Cross-tab synchronization

### Attribution Engine

* Multi-touch attribution tracking
* UTM parameter management
* Third-party platform integration

### Form Integration

* Automatic field population
* Element selector patterns
* Fillout form enhancement

### Dynamic Content

* Conditional content display
* User attribute evaluation
* Real-time personalization

## Data Flow

1. **Collection**: Gather data from URLs, interactions, and APIs
2. **Processing**: Normalize and validate collected data
3. **Storage**: Persist data across multiple storage mechanisms
4. **Application**: Use data to enhance user experience

## Security & Privacy

DataGlue is built with privacy-first principles:

* Client-side data processing
* Configurable data collection
* GDPR/CCPA compliance
* No server-side data storage by default