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

# Feed data into dashboards

> Connect GeoArk AI to Looker, Metabase, or custom dashboards

# Feed data into dashboards

Connect your AI visibility data to BI tools or custom dashboards.

## Looker Studio / Google Data Studio

Use the **Community Connector** or **Data Connector** with a custom backend that calls the GeoArk API. Your connector can:

1. Call `POST /reports/brands` with date range
2. Map response `data` to a table
3. Refresh on a schedule

## Metabase

Use a **Custom JSON** or **API** data source. If your BI tool supports REST APIs, point it at:

* URL: `https://api.geoark.ai/api/customer/v1/reports/brands`
* Method: POST
* Headers: `X-API-Key: your_key`, `Content-Type: application/json`
* Body: `{"start_date":"2025-01-01","end_date":"2025-02-19"}`

## Custom dashboard (React example)

```javascript theme={null}
const { data, total } = await fetch('https://api.geoark.ai/api/customer/v1/reports/brands', {
  method: 'POST',
  headers: {
    'X-API-Key': process.env.REACT_APP_GEOARK_API_KEY,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({ start_date: '2025-01-01', end_date: '2025-02-19' }),
}).then(r => r.json());

// data = array of { brand, visibility, sentiment, position, ... }
```

Store the API key in env vars; never expose it in client-side code for public dashboards. Use a small backend proxy if needed.