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Guide

GDPR-compliant AI, the on-premise way

How keeping AI on your own hardware simplifies GDPR, and where the EU AI Act still applies to European companies.

Runs locally · Data stays in the building · Made in Germany

What is on-premise AI?

On-premise AI means the artificial intelligence runs on hardware you own and control, inside your own building, instead of on a provider's cloud servers. Your documents and prompts are processed locally, so personal data never leaves your premises. This keeps you in full control and strongly simplifies GDPR compliance.

Below are the questions European companies ask most before bringing AI in house. The short version: locality is the single biggest lever you have for data protection. The tool that runs it here is Ara OS, a local AI operating system that runs on your own server.

At a glance

On-premise AI vs cloud AI

The same task, two very different data protection footprints.

Aspect
Cloud AI (ChatGPT etc.)
On-premise AI (Ara OS)
Where data goes
Sent to a third-party provider, often outside the EU
Stays on your own hardware, never leaves the building
Legal basis and contracts
Needs a lawful basis plus a data processing agreement (Art. 28)
No external processor to contract with for the AI itself
International transfer
Must be safeguarded if data leaves the EU
No transfer, so the question does not arise
DPIA (Art. 35)
Frequently required for sensitive or large-scale use
Often simpler or unnecessary once transfer risk is removed
EU AI Act obligations
Apply by risk class
Apply by risk class (running locally does not change it)

Is ChatGPT GDPR-compliant for companies?

Not automatically. When staff paste customer records, contracts, or health data into a public AI tool, that personal data is sent to a third-party provider, often outside the EU. Under the GDPR you then need a valid legal basis (Art. 6), a data processing agreement with the provider (Art. 28), and in many cases a Data Protection Impact Assessment (Art. 35). It can be done with a business agreement and the right settings, but it takes real work and the data still leaves your control. On-premise AI sidesteps most of this by keeping the data local.

What makes an AI server GDPR-compliant?

A GDPR-compliant AI server processes personal data lawfully, transparently, and with data protection built in by design (Art. 25). The strongest lever is data minimisation and locality: if the AI runs on hardware you own and no personal data is transmitted to an outside party, there is no third-party transfer to justify and no international data transfer to safeguard. You still need the usual basics, access control, logging, a lawful basis, and a record of processing activities. But keeping the compute in the building removes the hardest questions before they are ever asked.

On-premise AI vs cloud AI: which is better for GDPR?

For GDPR, on-premise AI is usually the simpler path. With cloud AI your input travels to someone else's servers, so you inherit their sub-processors, their storage locations, and their retention policy, and you carry the legal weight of that transfer. With on-premise AI the model runs on your own machine and the data never leaves the building, so there is no external processor to contract with and nothing to transfer abroad. Cloud AI can still be compliant, but it typically needs more contracts, more documentation, and a closer look at where data physically sits.

What does the EU AI Act require from companies using AI?

The EU AI Act sorts AI systems by risk. Most everyday business uses, drafting text, summarising documents, sorting email, fall under minimal or limited risk, where the main duties are transparency, such as telling people when they interact with AI or see AI-generated content, plus general AI literacy for staff. High-risk uses, for example AI that materially affects hiring, credit, or access to essential services, carry heavier obligations around risk management, data governance, human oversight, and documentation. Importantly, running AI on-premise does not change its risk class. Where you run the model is a GDPR question; what the model decides is an AI Act question, and both still apply.

Does on-premise AI remove the need for a DPIA?

Not on its own, but it often makes one far easier or unnecessary. A Data Protection Impact Assessment (Art. 35) is required when processing is likely to result in a high risk to people, for instance large-scale handling of sensitive data. Keeping everything local removes one of the biggest risk factors, the transfer of personal data to a third party, which frequently lowers the overall risk. Whether a DPIA is still needed depends on the specific use case and data involved, so treat this as general information and confirm the details with your own data protection officer.

General information, not legal advice

This guide explains how on-premise AI typically affects GDPR and EU AI Act duties. It is general information, not legal advice. Your obligations depend on your specific data and use case, so confirm the details with your own data protection officer or lawyer.

Bring AI into your company without sending data away.

Ara OS runs private AI on your own hardware. Local, GDPR-friendly by design, no cloud lock-in. See what it looks like for your business.

Runs locally · Data stays in the building · No cloud lock-in