Why we chose private AI, and nothing else.

Since spring 2026, we spent weeks in the field. Long-standing clients, but also companies simply curious about AI, wanting to understand before deciding. We came back with notebooks full of notes, and three findings that settled our course.

First finding: everyone is already using AI. Everywhere, in every company we visited, without exception. But often with no framework at all: well-meaning employees, from personal accounts, with whatever consumer tool comes to hand. And almost always without grasping one simple fact: what leaves for inference servers, in Europe or the United States, never comes back. A contract excerpt pasted into a chat window, a client list submitted for sorting, a strategy summarised to generate a presentation: each of these pieces of information has left the company, permanently, with no receipt and no way back.

Second finding: nobody understands the jargon, and nobody bothers to explain it. Model, inference, RAG, agent, context window: behind these terms lie realities that are often very simple. But confusion reigns, over the words as much as over the very structure of an AI. And this confusion is not always innocent: a client who does not understand what they are buying is a client who can neither compare, nor challenge, nor leave. We have seen too many decisions made in the fog to believe that fog is accidental.

AI is only taking its first steps, and yet it is already a backbone: everything runs through it, data, strategy, know-how, clients.

Third finding, the most striking: the lucidity is there. In almost all our conversations, a real awareness that AI is only at its very beginning, its first cries. And yet, even at this stage, it is already becoming, for many, a new backbone of the company. What runs through it is not trivial: the data, the strategy, the know-how, the clients’ names and all their particularities. This flow is not mere technical traffic. It is the company’s capital, in its most concentrated form.

The decision these visits imposed

From these weeks in the field, we drew a single conclusion: we will do nothing but private AI, on hardware that belongs to the client. Not as a premium option in a catalogue, not as a variant for demanding clients. As our only model.

This choice settles two questions at once. Confidentiality first: it is no longer a matter for discussion, a contract clause or a vendor’s promise. It is extreme by design, because nothing leaves. The model runs on a machine that is yours, on your premises or on a dedicated server you own: the question “where does my data go?” simply no longer arises, since it goes nowhere.

The economic model next: you step out of usage-based billing. No meter running with every question asked, no subscription whose price tracks your dependency. One server, one investment, one piece of infrastructure on your balance sheet that gains value as your teams adopt it. Sovereignty is total, and it shows even in the accounting.

And if we can offer this model at a price that holds up, it is no conjuring trick. It is our sister company, FSYS Informatique, whose name is no accident: their trade is to supply servers, and nothing else. It is they who let us build high-performance configurations without spending a fortune, sized precisely for each company’s real workload. Two houses, two trades, one single chain: the hardware on one side, the intelligence on the other, and your data leaving neither.

We invented nothing this spring. We simply listened, a great deal, and took seriously what we heard. If AI is to become the backbone of your company, then it must belong to you. Everything else follows from that.