Working with us: hardware, process, data and quotes
Which machine you need, how the work runs from the call to the handover, what happens to your data and how a quote is made.
What hardware do I need to run AI locally?
It depends on the model, not the brand: what matters is GPU memory (or unified memory) against the size of the loaded model. On our NVIDIA DGX Spark, llama3.1:8b took 9.2 GB loaded and gemma4:26b 17 GB, measured on 4 October 2026.
The loaded size includes the quantised weights and the context memory, so it grows with long conversations. Before recommending a machine we measure the model on your tasks. The VRAM explorer and the hardware guide give you a first idea.
Do you sell us the hardware?
No. We help you choose it and you buy it, from whichever supplier you like. The machine is yours from day one, and so is what we install on it.
Some product pages carry affiliate links, marked as such; they do not change what we recommend. If you already have a server or a GPU machine, we start by measuring what you have.
What is the process, from start to finish?
Four steps: a 15-minute call, a written scope with a fixed quote, the deployment on your hardware measured on your tasks, and the handover with documentation and training.
Nothing starts without the signed scope: what is delivered, with which data, who on your team takes part and on which dates. If something changes halfway, it changes in writing before we continue.
What happens on the 15-minute call?
You tell us what you want to solve and we tell you whether we can help, or whether you do not need to hire us. It costs nothing and it is not a sales demo.
If it fits, after the call we send you the scope in writing. If your case involves personal data, you do not need to share any on the call: describing the kind of data is enough.
How much does it cost? How is it quoted?
By scope: a fixed quote, in writing and before we start. We do not publish rates because the price depends on what is delivered, not on a table.
What weighs most: how many use cases, how many integrations with your systems, whether the hardware already exists and how much training is needed. Later support is optional and quoted separately. For the AI Act there is an entry offer with fixed deliverables, also quoted after the call.
Does my data leave my network?
No, in a local installation: the model runs on your machine and the prompts, documents and logs stay on it. There is no outside AI provider receiving them.
Your company remains the controller. As no data goes to a third-party service, there is no international transfer to justify (GDPR Chapter V). The impact assessment (Art. 35), if your processing requires one, is still yours; we give you the technical description it needs.
Do you need access to my systems or my data?
Only during installation and, if you contract it, support, through the channel you authorise. If that access lets us see personal data, we sign a processor agreement first (GDPR Art. 28).
To measure the model we prefer test or anonymised data. Remote access is opened for a specific task and closed afterwards.
Does it work without an internet connection?
Yes. Once installed, the model answers with no connection. The internet is only needed to bring in a new model or an update, and you decide when.
The model weights are copied once and checked against their hash before loading. Where full isolation is required, as in the public sector, updates come in on controlled media.
Which models do you use?
Open-weight models such as Llama, Qwen, Gemma or Mistral, chosen for each use case and measured on your tasks. We do not send your data to any model provider.
Each model has its own licence, and they do not all allow the same: Llama's, for example, has its own conditions. We review it with you before using it in production.
Is a local model as good as a cloud one?
Not always. An open model on your machine handles many bounded tasks well, such as summarising, classifying or searching your documents, but not everything. That is why we measure on your tasks before recommending anything.
If the case needs the largest model on the market, or a cloud service already solves the problem with the guarantees you need, we tell you on the call.
What happens after the handover?
You keep everything: the machine, the installed software, the documentation and your team's training. Later support is optional, by the month, and you can run it yourself or with another supplier.
The software we use is open and documented, so you do not depend on us to carry on. The training covers what Art. 4 of the AI Act asks for the people who will use it.
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