Pillar 02
Sovereign AI
The first question in a mid-sized company is almost never "what can AI do?". It is "where does our data end up?" There is a better answer to that than a clause in a contract.
Why this matters
Some data cannot leave the building
Design data, costings, personnel files, customer contracts, formulations, source code. When an agent needs access to this information in order to be useful at all, the architecture decides whether the project can happen.
No accidental leakage
If the model runs on your hardware, no document and no query leaves your network. That is not a promise in a contract — it is a property of how the system is built.
Independent of vendors
Prices change, models get retired, terms get revised. If you control the layer underneath, you can swap the model without rebuilding the application.
Predictable cost
Usage-based billing is hard to plan for when an agent works all day. Your own hardware costs once — and very little that is hard to predict afterwards.
Able to account for itself
Who saw which information, when and by which route can be logged properly in your own environment. That makes every conversation with data protection and audit considerably easier.
What we build
The layer beneath the agents
Local language models
Selecting, running and tuning open models on your hardware — matched to the task rather than "the biggest one that fits".
GPU infrastructure
Sizing, procurement and setup of the servers. Dimensioned against real load, not against datasheet numbers.
Local knowledge systems
Making your documents searchable, including permissions and sources — without a single document leaving your network.
Hybrid architectures
Sensitive material stays local, uncritical material may go to the cloud. You draw the line — we make sure it holds technically.
Operations and monitoring
Availability, updates, logging, cost control. So the infrastructure does not become IT’s problem six months later.
Migration paths
Bringing existing cloud solutions back in house step by step, without stopping day-to-day operations.
What we will say openly about this
Local is not automatically better. Your own hardware costs money and needs to be operated, and the largest models still run in the cloud. For many use cases a hybrid setup is the more sensible choice. Which path is right for you depends on how sensitive your data really is, how much load you generate and what your IT can and wants to carry. That is exactly what we settle before anybody orders hardware.
How sovereign do you need to be?
We look together at which of your data really has to stay in house — and what that means for the architecture.