Explainer
AI data privacy for regulated industries
Where public AI leaks data, and how an owned, in-perimeter model makes privacy structural.
In short
AI data privacy is about ensuring the data you put into an AI system isn't exposed, retained, or used to train someone else's model. Public AI APIs transmit your data to third parties; an owned model deployed inside your perimeter keeps data private by design, the safest approach for regulated industries.
Where data leaks with public AI
- Transmission: Prompts and documents are sent to the provider's servers.
- Retention: Inputs may be logged or stored under the provider's terms.
- Training reuse: Data can be absorbed into third-party model training unless explicitly excluded.
- Sub-processors: Your data may pass through parties you never chose.
Privacy by design with owned models
- In-perimeter inference: Data never leaves your environment, so there's nothing to transmit or retain externally.
- No third-party training: Your data is never used to improve someone else's model.
- Air-gap option: For the most sensitive data, run with no external connectivity at all.
- Owned & auditable: You hold the weights and logs, supporting privacy assurances.
What this looks like with Locai
Compliance is easier to evidence when the model, the data, and the logs are all things you actually own, not things a vendor describes in a whitepaper.
Locai Labs believes organisations should own their intelligence. Renting access to a general-purpose model that lives on someone else's servers is fine for low-stakes work; for the AI that touches your data, your customers and your decisions, the model itself should be yours. That is the bet behind everything we build.
It is also a bet that an expert model beats a generalist on the work that actually matters to your business. A smaller model trained on your data, your language, your workflows and your edge cases routinely outperforms much larger generalists on the tasks you care about, and it does so on infrastructure you control. The goal is not the biggest model; the goal is the right model for your business.
And it is deployed sovereignly: an owned model that runs inside your perimeter, on-prem via Locai One, in your private cloud tenant, in a UK sovereign cloud, or fully air-gapped, depending on your residency and security requirements. Your prompts, your documents and your outputs stay inside your environment, under UK jurisdiction, with a data path designed to fit GDPR and the procurement standards regulated organisations are held to.
Frequently asked questions
Is my data safe with AI?
It depends on the deployment. With a public API your data is sent to a third party; with an owned, in-perimeter model it never leaves your environment, the safest option.
Do AI providers train on my data?
Some may, unless you've explicitly opted out or have contractual exclusions. An owned model removes the question entirely, your data is never shared.
How do I keep AI private?
Run a model you control inside your perimeter, on-prem, in your cloud tenant, or air-gapped, so data is private by design.
What about air-gapped deployment?
Air-gapping fully isolates the model from external networks, giving the strongest privacy guarantee for the most sensitive data.
Book a sovereign AI briefing
A 30-minute session on owning your model: deployment options, the data path, and a clear cost range for your use case.