***

title: Integration patterns
description: How AISquare fits into different application architectures.
------------------------------------------------------------------------

This guide explains how AISquare fits into different application architectures.

Depending on your use case, you can integrate AISquare in multiple ways.

***

## Overview

AISquare is typically used as a backend service layer that powers:

* Content feeds
* Personalization
* Analytics
* AI-driven experiences

Most integrations follow this pattern:

```
Frontend → Your backend → AISquare API
```

Your backend acts as the integration layer between your application and AISquare.

***

## Pattern 1: Frontend + backend integration (recommended)

This is the most common and recommended setup.

### Architecture

```
Client (Web / Mobile)
       ↓
Your Backend
       ↓
AISquare API
```

### How it works

1. User interacts with your app
2. Your backend calls AISquare APIs
3. Your backend processes the response
4. Frontend renders the data

### Why use this pattern

* Keeps API keys secure
* Allows custom business logic
* Enables caching and transformations
* Supports personalization

### Example use case

* Displaying AI Studio content feed
* Showing personalized recommendations
* Building dashboards

***

## Pattern 2: Server-to-server integration

Used when AISquare is part of your backend workflows.

### Architecture

```
Your Backend → AISquare API
```

### How it works

* Your backend directly calls AISquare
* No frontend involvement required
* Runs as part of internal services or pipelines

### Example use case

* Syncing user data
* Generating reports
* Running analytics jobs

***

## Pattern 3: Platform embedding (partner integration)

Used when AISquare powers features inside another platform.

Example: integrating AISquare into a product like a learning or gaming platform.

### Architecture

```
User → Your Platform → AISquare API
```

### Key idea

Your platform:

* Manages users
* Handles authentication
* Calls AISquare on behalf of users

AISquare acts as a **data and intelligence layer**.

### Important considerations

* Register users via API
* Store API keys securely
* Map your user IDs to AISquare users

***

## Choosing the right pattern

| Use case          | Recommended pattern |
| ----------------- | ------------------- |
| Web or mobile app | Frontend + backend  |
| Internal services | Server-to-server    |
| Partner platform  | Platform embedding  |

***

## Best practices

### Use a backend layer

Never call AISquare directly from the frontend with sensitive credentials.

### Store credentials securely

* API keys should be stored on your backend
* Never expose them in client-side code

### Handle errors gracefully

* Retry failed requests
* Handle authentication errors
* Validate inputs before sending requests

### Use pagination

Avoid fetching large datasets at once.

***

## Putting it together

A typical AISquare integration looks like:

1. User opens your app
2. Backend authenticates user
3. Backend fetches AISquare data
4. Frontend renders content
5. User interacts with resources

***

## Related pages

* [Authentication](/docs/getting-started/authentication) — set up API keys and tokens
* [Build your first integration](/docs/integration-guides/build-your-first-ai-studio-integration) — step-by-step guide
* [User onboarding & account lifecycle](/docs/integration-guides/user-onboarding-account-lifecycle) — manage users programmatically
* [Token lifecycle & session management](/docs/integration-guides/token-lifecycle-session-management) — manage tokens in production
* [Permissions and access control](/docs/data-ux-guides/permissions-and-access-control) — understand access patterns
* [Errors](/docs/reference/errors) — handle error responses gracefully