private AI infrastructure

AI works. Until they change the terms.

Build your business on models you can own.

Not your model, not your knowledge.

Vendors retire models on their schedule. The prompt chains you built and tuned stop working. No migration path, no warning.

Governments and vendors decide who gets which model. One policy shift and your team loses the capability it was built around.

Every API call sends context to servers you cannot audit. For regulated industries, that is a compliance problem waiting to happen.

Fine-tuning on a vendor platform feeds your data into their ecosystem. The model gets smarter. You get a bigger invoice.

Open-source models on your GPUs. Cloud APIs for the quick stuff.

GPU servers, storage, networking, monitoring, backups.

vLLM, Ollama, retrieval, routing, privacy controls.

Dashboards, APIs, chat interfaces, automations, handover docs.

A local PII filter for AI code editors. Sensitive data is tokenized before a prompt leaves the machine.

Forward deployment work on AI systems and privacy-aware LLM tooling for Dutch enterprises.

Mixed-reality coding on Meta Quest 3, built in 24 hours at the Mistral AI Worldwide Hackathon Paris.

Tell me what you need.