Run AI on infrastructure you control.

Why Private AI now?

For a German Mittelstand pharmacy, a Bavarian law firm, or a Munich engineering company, sending sensitive data through OpenAI or Anthropic is often a non-starter — even with enterprise contracts. The EU AI Act, GDPR, and individual industry regulators all push in the same direction: know where your data lives, who can access it, and how to prove it.

The good news is that Private AI is genuinely production-ready. Modern open-weight models (Llama, Mistral, Qwen, and newer releases) are capable enough for the majority of enterprise tasks. They run on hardware that fits in a single server and stop the linear-with-usage token bill that hosted APIs impose. Capability improves with every release.

What we deliver

Our Private AI engagements typically include:

• LLM evaluation & selection — Llama 3, Mistral, Qwen, plus newer open-weight options. We benchmark against your actual use cases, not generic leaderboards.
• On-prem architecture design — inference server topology, GPU sizing, networking, observability. Built to be operable by a regular IT team.
• RAG pipeline for your own documents — SharePoint, Confluence, file shares, ERP exports. Embeddings, vector store, retrieval logic.
• Vendor-neutral hardware shortlist — we don’t resell anything, so the recommendation reflects your actual constraints (budget, rack space, support contract, residency requirements).
• Data-sovereignty review — what stays on-prem, what can leave, where every model artefact lives. Mapped to GDPR and EU AI Act obligations.
• Deployment blueprint — concrete plan including timeline, cost model, change-management notes, and runbook structure.

What this looks like in practice

One useful reference architecture: our own AI Product Assistant plugin for WooCommerce. The plugin is designed to talk to either a hosted LLM API or a local AI server you run on-prem — same code, different endpoint. A small online shop on the free tier uses an API key; a larger Mittelstand e-commerce operation can run their entire product catalogue, search index, and customer Q&A through their own Llama 3 server, paying once for hardware instead of per-token forever. That same pattern — one plugin, configurable endpoint, optional Private AI — is how we design most Private AI deployments.

Who this fits

• Legal & tax advisors processing confidential client material
• Healthcare and pharmaceutical organisations dealing with patient or research data
• Manufacturing with proprietary technical documentation and supplier data
• Mittelstand financial services with regulatory residency requirements
• Public-sector adjacent organisations with sovereignty mandates

Where we start

Most Private AI engagements begin with our Private AI & Infrastructure package (from €5,000, 6–10 weeks). For organisations still figuring out whether Private AI even makes sense, the AI Readiness Assessment explicitly compares public-AI vs Private AI for your specific data and use cases.