GDPR-compliant AI, on your own terms.
Your team wants AI on your company documents. Your DPO wants to know where that data goes. Pasting internal files into US SaaS tools creates exactly the GDPR exposure you are trying to avoid. Ainomiq builds GDPR-compliant AI assistants that run on your own infrastructure instead.
What a GDPR-compliant AI assistant actually is
A GDPR-compliant AI assistant is an AI system that processes personal data under the conditions the GDPR sets for any processing: data stored and processed in the EU or transferred under a valid legal mechanism, a data processing agreement with every provider in the chain, a guarantee that your data is never used to train public models, access control that mirrors your existing permissions, an audit trail of questions and answers, and the ability to actually delete someone's data when they ask. Miss any one of these and the tool, however impressive, is a liability.
That is a description of what the regulation requires in plain language, not legal advice for your specific situation. The practical takeaway: compliance is decided by architecture and contracts, not by the logo on the chatbot.
What it takes to run AI on company data
Four requirements separate a private AI assistant for company documents from a data leak with a chat interface.
EU data residency
An EU-hosted AI assistant keeps personal data inside the EU/EEA. The GDPR allows transfers abroad only with a valid legal mechanism; hosting in the EU largely takes that question off the table, which is why many DPOs simply require it.
Permission-aware access
The assistant must respect the access rights you already have. If someone cannot open the HR folder, the AI must not quote from it either. Answers are filtered per user, per role, per document.
No training leakage
Your documents must never be used to train a public model. That means contractual no-training commitments from every model provider, or models running on infrastructure you control.
Auditability
GDPR accountability means you can show what happened: who asked what, which documents the answer used, and when. An audit trail is also what makes data subject requests and incident response workable.
How Ainomiq builds GDPR-compliant AI
The same rules, applied to every system we ship: an EU-hosted AI assistant for your team, a chatbot for your customers, or both.
Custom systems, built on your infrastructure
We do not resell a SaaS subscription. Every system is built from scratch and deployed on infrastructure you control, and you own the code, the models and the data, with no vendor lock-in. See how we work on our development page.
Permission-aware answers with Business Brain
Business Brain is our private AI assistant for company documents: a secure, permission-aware assistant grounded in your own company data and connected to your business systems. Every answer is sourced and filtered by who is asking.
A GDPR-compliant AI chatbot for customers
Reply answers repetitive customer questions on WhatsApp from your own knowledge base, in your brand voice, with human handoff. Built with the same rules: your knowledge base, no training on your conversations.
EU AI Act and NIS2 awareness
GDPR is not the only regulation that touches AI systems. Our security team covers GDPR, NIS2 and EU AI Act readiness, so the system you ship today does not become a compliance problem in the next audit.
GDPR and AI, honestly answered.
Is ChatGPT GDPR-compliant for business use?
It depends on which ChatGPT and how you use it. The consumer version trains on your conversations by default and is not offered with a data processing agreement, so it is generally unsuitable for personal or confidential company data. ChatGPT Enterprise, Team and the OpenAI API do offer DPAs and no-training commitments. Even then, compliance is not a property of the product: it depends on your configuration, what data actually flows into the tool, your legal basis, and often your own DPIA. No subscription makes you compliant by itself.
Can we use AI on personal data under GDPR?
Yes, if you meet the same conditions that apply to any processing of personal data: a legal basis, a defined purpose, data minimization, a data processing agreement with every processor involved, appropriate security measures, and the ability to honor data subject rights like access and erasure. AI does not get an exemption, but it is not banned either. The practical risk with AI tools is usually uncontrolled data flows to third parties, which is exactly what a private, EU-hosted setup avoids.
What is EU data residency and do we need it?
EU data residency means personal data is stored and processed on servers physically located in the EU/EEA. The GDPR does not strictly require it: transfers outside the EU are allowed with a valid mechanism such as standard contractual clauses or an adequacy decision. But those mechanisms carry legal uncertainty and extra paperwork, so many DPOs, works councils and enterprise customers simply require EU hosting. If you handle sensitive data or sell to larger EU companies, residency is the path of least resistance.
Do we need a DPIA for an internal AI assistant?
Often, yes. Article 35 GDPR requires a data protection impact assessment when processing is likely to result in a high risk to individuals, and an assistant that uses new technology on large sets of employee or customer data frequently meets that bar. A DPIA for a well-scoped internal assistant is not a large project: describe the data flows, the risks and the mitigations. When in doubt, do one; it is far cheaper than explaining to a regulator why you did not.
How do you handle the right to erasure with AI systems?
By architecture. We keep personal data in your source systems and a retrieval index, not baked into model weights: the model looks documents up at question time instead of memorizing them. Erasure then works the way it should: delete the data at the source, re-index, and it is gone from every future answer. Logs get defined retention periods. Fine-tuning models directly on personal data makes erasure nearly impossible, which is one of the reasons we avoid it.
How long does it take to build a private AI assistant?
Most Ainomiq systems go live in 3 to 8 weeks, depending on how many sources and systems the assistant needs to connect to. We start with a free discovery call, then send a fixed-scope proposal, so you know the timeline and the cost before you commit.
AI on your data, without the exposure
Tell us what data you want AI to work with and what your DPO needs to see. We come back with an architecture and a fixed-scope proposal: EU hosting, permission-aware access, audit trail, and you own everything we build.