Sovereign AI systems · built, proven, in-house
Your knowledge stays in-house.
We build and run AI systems that keep your company knowledge physically in-house — on your own servers. We start small on a single machine (Mac Studio) and grow with you to a full server estate (NVIDIA cluster). Every material statement is verifiably and repeatably substantiated or honestly marked as an open gap. Your data does not leave the building — nothing runs through US clouds or third-party systems (third-party stacks).
Outcome, not tool · On-premise, not US cloud · ISO 27001 certified · Based in Germany
The problem
“German hosting” does not protect you from the CLOUD Act.
Every question your staff put to a cloud LLM is a log entry on someone else's infrastructure. For three kinds of company, that is not a compliance tick-box but a business risk:
Finance & insurance
Customer data must not leave the sphere of control. US cloud + CLOUD Act = a knockout criterion. Triggers: DORA, EU AI Act, MaRisk/BAIT.
Healthcare & pharma
Health data (Art. 9 GDPR, §203 StGB) must not flow through third-party stacks. Triggers: NIS2, KRITIS (German critical infrastructure) audits, §75c SGB V.
Industrial mid-sized companies
Engineering and process knowledge is the competitive advantage — feeding it into a US LLM means giving it away.
Why on-premise rather than cloud
Four reasons that can be proven technically — not merely claimed.
Knowledge leakage
Your engineering, customer or patient knowledge is your competitive advantage. Feed it into a third-party AI service (a so-called LLM) and it leaves your sphere of control irrevocably.
CLOUD Act
US providers are subject to US law — even with a data centre in Frankfurt. “EU region” on the invoice is not sovereignty. Physical data control in-house is the only reliable answer.
Costs
No cloud bill that keeps growing with every use and every employee. On your own servers, it becomes a plannable, calculable investment.
Control
No provider can switch off an interface overnight (API deprecation) or swap out the AI model — such changes happen only with your consent. You can trace what the system does at any time (full audit access). And nobody but you can switch it off or read it out.
Offer
From a single Mac Studio to an H200 cluster.
A staged entry — each stage with an outcome, not a feature list. The hardware grows with the use case.
Stage 0
Architecture assessment
A senior engineer reviews one concrete use case and its data path — no sales pitch.
Outcome: A clear answer on whether and how the use case can be implemented sovereignly, including a data-flow diagram and a rough cost range.
Stage 1
Sovereign pilot on Apple Silicon
A first working version that uses your company knowledge and documents — a small start on a single machine (Mac Studio / M4 class). The AI runs entirely on your premises (local models); not a byte leaves the building.
Outcome: One departmental use case running verifiably on-premise — in weeks, not quarters.
Stage 2
On-premise production system
Runs in your own data centre (Mac Studio cluster or NVIDIA setup); uses your company knowledge and understands your documents, automates with AI agents, technically secured (hardened) and traceably logged.
Outcome: Production-grade, auditable AI for one domain — NIS2/DORA/EU AI Act built into the architecture, not retrofitted.
Stage 3
Scaled sovereign AI infrastructure
Across the whole company and multiple business units (domains): on high-performance servers, with AI agents that steer processes autonomously, and company knowledge whose statements can be traced back to the source at any time.
Outcome: Company-wide AI that invents no facts and substantiates its statements (cryptographically traceable) — every material statement is either backed by a source or honestly marked as a knowledge gap.
Plain speaking: we have proven operation on a small start and in a German sovereign cloud (STACKIT, on Kubernetes/k8s). Larger servers for higher loads (NVIDIA Spark/Station/H200/B300) we build with the same security and traceability (hardening and signing) — as an offer, not as a marketing case.
Evidence, not claims
We show systems we have built — outcome and principle, never your architecture.
Verifact · Flagship
AI that admits when it does not know something.
Every answer comes from a cryptographically signed knowledge store on your own servers, in which subsequent changes remain detectable — not from the AI's trained memory. The language model (LLM) may only pull out (extract) substantiated facts from this store. If evidence is missing, the system honestly shows this as a gap instead of inventing an answer (hallucination).
OneLog · KRITIS
1 platform instead of 5–8 tools.
A platform for remote monitoring and management of your IT (RMM), with NIS2 requirements built in from the start and operated on a sovereign cloud — your data stays in the EU. A log of all access whose entries cannot be altered unnoticed after the fact, signed with cryptography intended to withstand future attacks by quantum computers. A first proof of concept for critical infrastructure in healthcare (KRITIS proof of concept, §75c SGB V). USD 0 paid to large US cloud corporations (US hyperscalers).
TMT MentalTech · Velocity
17 days to go-live — without US cloud.
From the first sketch to production launch (go-live) in 17 days, with data protection built in from the start (privacy-first): no third-party building blocks from other vendors (external SDKs), consent for especially sensitive data (Art. 9 GDPR consent) integrated, 26 identified security findings resolved.
PioneerDesk is ISO 27001 certified as a GmbH — our own certification, not the hosting partner's. The foundation behind it: over 25 years of enterprise and KRITIS IT. More about us →
Getting started
Sovereignty Compass — the workshop that resets the thinking.
We do not bombard your team with tools. In one to two days we bring management and process owners on board, turn the question from “which tool” to “which outcome” — and work out two to three genuine use cases from your company, prioritised by benefit and by how well they can be implemented in-house (sovereignty).
Compass · 1 day
€890–1,200 / participant
Mindset reset + 2 identified use cases + sovereignty map. For management teams that want clarity quickly.
Deep dive · 2 days
€1,500–1,900 / participant
Additionally, a data-path analysis per use case and a concrete roadmap to a sovereign pilot. Group of 6–12 participants.
The fee counts. If you subsequently commission a sovereign pilot (Stage 1), we credit the workshop fee in full. The workshop is an investment in your use-case map — not a cost item.
You take away: a prioritised use-case map, a data-path sketch and an honest recommendation of what is feasible sovereignly — and what is not.
On-premise AI readiness
Six questions we clarify with you in the intro call.
No form funnel, no download gate. Go through the questions — if more than two of them give you pause, an architecture assessment is worth it.
- Which data would the use case process — and would that data be allowed to leave your building?
- Are you subject to NIS2, DORA, §75c SGB V or Art. 9 GDPR?
- What hardware is available (servers, GPUs, Mac devices)?
- Is the use case intended for one department or the whole company?
- Is a cloud AI service already in use today — and where do its prompts go?
- How mature is the use case: idea, prototype or planned for production?