# Introduction

Aurora is a sovereign cloud platform for storing data, running AI models, and deploying compute workloads. Its services use familiar APIs and give organizations clear control over where their data and workloads are hosted.

## Products

### Object Storage

Store application data, backups, analytics datasets, and AI workloads through an S3-compatible API.

- [Get started with Object Storage](https://docs.aur.lu/docs/s3/getting-started)
- [Create buckets and access keys](https://docs.aur.lu/docs/s3/buckets-and-api-keys)
- [Browse supported tools and integrations](https://docs.aur.lu/docs/s3/tools/aws-cli)

### Inference

Run language models through OpenAI-compatible endpoints, with usage billed by input and output tokens. Prompts and outputs are not retained or used for training. Contact support if you have specific data residency requirements or need a dedicated model deployment.

- [Get started with Inference](https://docs.aur.lu/docs/inference/getting-started)
- [Browse the API reference](https://docs.aur.lu/docs/inference/api-reference)
- [Use the OpenAI Python SDK](https://docs.aur.lu/docs/inference/sdks/inference-python)

### Compute

> **Info — [Private preview]**
>
>
> Create and manage virtual machines, networks, and block storage with Aurora Compute. The service is currently available to selected private-preview customers. Documentation will be published before broader availability.
>

## Aurora Portal

The [Aurora Portal](https://portal.aur.lu/) is where you create resources, manage credentials, switch between organizations and workspaces, and review usage.

## APIs and automation

Use the [Portal API](https://docs.aur.lu/docs/portal-api) to automate common management tasks, such as creating buckets, rotating credentials, and provisioning compute resources.

Learn more about Aurora at [aurorainfra.ai](https://www.aurorainfra.ai/). If you need help, see [Support](https://docs.aur.lu/docs/support).