When Is Closed AI Not Enough?
When companies choose an AI strategy, the temptation to use closed APIs is strong. It's easy, requires no infrastructure, and gets you up and running fast. But as a new guide from ThePlanetTools.ai points out, there are critical situations where closed models simply won't do. If it's unacceptable for even a single prompt to leave your network, self-hosting open-weight models is often the only solution that meets the requirements. This applies especially to:
- Patient records and health data
- Sensitive financial data
- Classified material
- Strict data residency requirements
Here, you're trading convenience for physical control.
The API's Blind Spot
The problem with closed models is obvious: call a proprietary API, and the model maker's cloud sees every single prompt. That's a fundamental breach of data protection that many Danish companies simply can't accept. As Infercom puts it in their definition of open-weight models: when you run an open-weight model, the creator has only published the weights and has no insight into how it's run. Your data stays on your own infrastructure.
The European Advantage
For European and Danish companies, this choice becomes even sharper. With stricter data residency requirements and compliance obligations like the EU AI Act, open-weight models on your own infrastructure aren't just a technology choice — they're a legal one. Davies Meyer notes that legal teams use open-weight models to meet EU AI Act requirements, because the model's weights are publicly available and enable self-hosting.
When the choice comes down to closed versus open AI in 2026, the answer depends on your data. For anything requiring absolute confidentiality, open weights on your own infrastructure is the way forward. At Liviate, we help you get open-weight models into production on European infrastructure, so you can retain full control over your data.