GDPR-compliant AI, the on-premise way
AI on your own hardware makes GDPR compliance simpler, and that still holds once the AI Act applies.
Runs locally · Data stays on your server · Software from Dresden
What is on-premise AI?
On-premise AI means the artificial intelligence runs on hardware you own and control, on your own server, instead of on a provider's cloud servers. Your documents and prompts are processed locally, so personal data never leaves your premises. You decide what goes out, and GDPR compliance becomes much simpler.
The General Data Protection Regulation (GDPR) applies in every EU member state, so these questions come up the same way in Lisbon, Vienna or Dresden. Below are the ones European companies ask most before bringing AI in house. The short version: where the data is processed matters more for data protection than anything else you can choose. The tool that runs it here is Arasul, which hosts internal apps on a server inside your company and lets the models compute there.
On-premise AI vs cloud AI
The same task, compared point by point from a data protection view.
Is ChatGPT GDPR-compliant for companies?
Not automatically. When staff paste customer records or contracts 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) and a data processing agreement with the provider (Art. 28), in many cases also 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 and transparently, with data protection built in by design (Art. 25). What helps most is data minimization 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 and logging, a lawful basis and a record of processing activities. But keeping the compute on your own server 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. You also carry the legal weight of that transfer. With on-premise AI the model runs on your own server and the data never leaves it, 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 and 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 such as drafting text, summarizing documents or sorting email fall under minimal or limited risk. There 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 are for example AI that materially affects hiring, credit or access to essential services. They carry heavier obligations around risk management and 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.
Arasul hosts internal apps on a server inside your company, and the models compute there. Local, GDPR-compliant, no cloud lock-in. See what it looks like for your business.
Runs locally · Data stays on your server · No cloud lock-in