Local AI Solutions: Why Companies Adopt GDPR-Compliant AI
Learn how to run AI models locally while staying GDPR-compliant. With Ollama and open-source LLMs you keep full control over your data.
Artificial intelligence is a competitive advantage for many companies — but data protection often gets in the way. Especially in the DACH region, where the GDPR is strictly enforced, companies face the question: How do we use AI without handing sensitive data to third parties?
The answer: local AI models running entirely on your own infrastructure.
What are local AI solutions?
Local AI means running language models (LLMs) directly on your own servers — no cloud dependency, no data transfer to external providers. Tools like Ollama make it straightforward to deploy open-source models like Llama, Mistral, or Gemma locally.
Advantages over cloud AI
| Criterion | Cloud AI (GPT, Claude) | Local AI (Ollama) |
|---|---|---|
| Data protection | Data leaves your network | Data stays with you |
| GDPR compliance | Data processing agreement required | Full control |
| Cost | Pay-per-token | Predictable hardware cost |
| Latency | Depends on the provider | Low within your own network |
| Availability | Depends on the provider | Your own infrastructure |
When does local AI make sense?
Local AI is especially worthwhile when:
- You work with sensitive customer data (health, finance, HR)
- Your compliance department does not approve cloud AI services
- You prefer predictable costs over usage-based billing
- You want no internet dependency for AI features
How schnaq supports you
At schnaq we help you pick the right model, install and configure Ollama on your infrastructure, and build tailored applications that wire local AI into your business processes. From the first consultation to production rollout.
Interested? Get in touch for a free initial conversation.