Private AI infrastructure for brands whose data has to stay home.
For brands whose data, models and brand DNA must not leave a sphere they control.
The problem
Most generative pipelines run on vendor clouds. Prompts, product data, likenesses and fine-tuned models end up with a third party, under terms that change. For a regulated or global brand that is a risk, not a feature.
The approach
We build the stack the other way round: open-weight models on an on-premise core, confidential cloud for peaks, brand-specific fine-tunes that remain the customer's property. Logs, telemetry and model weights stay with the customer.
Compliance
Designed against GDPR, the EU AI Act and NIS2, with labelling, documentation and data handling that an audit can follow. Sector standards are mapped per project.
Let's talk under NDA
If this is your situation, we talk under NDA and show the detail: architecture, operating model, economics. The one-pager has the outline.
Questions and answers
How do you handle the EU AI Act?
AI-generated content is labelled where the law requires it, and we document which parts of a film were generated. Real people appear only with a signed release. See how a job runs.
What happens to our data and product material?
Briefs, products, likenesses and references are used only for your job and do not train public models. Delivery runs over a European CDN. Brands that need everything on their own infrastructure get a private, open-source-based AI stack: see Enterprise.
What is the enterprise stack?
A private AI content stack for global, regulated brands: open-weight models on an on-premise core, confidential cloud for peaks, brand-specific fine-tunes that stay yours, designed against GDPR, EU AI Act, NIS2 and sector standards. See Enterprise.
Briefing
NDA on request.