AC-Création / Your AI installed on your premises

We help business leaders make decisions that match their resources and their ambitions.

We support you from decision-making through to delivery. From the sole trader to the manufacturer with more than 100 employees.

Let's talk about your project See examples by profession

The starting point

One decision to make, one clear framework.

Your ambitions
What you want to change in the way your teams work.
Your resources
The time, the budget and the people actually available.
Your decisions
What stays with a person to decide, with a firm hand on the results.

AI transition support: decide, install on your premises, deliver with your teams.

01 / Use cases

What your AI prepares.
What you decide.

Your AI is not a chat bubble: it does a specific piece of work. It can search your documents, cross-reference information and prepare work for you to review. Its role and its limits are defined with the people who will use it.

Examples workshop

These scenarios are simulated. They do not describe client results. The texts are written in advance, with no call to an AI and no data sent.

Simulated example / Your fact-checking AI

Spot a contradiction between two documents.

Fictitious documents

A notice announces Saturday opening at the reception desk. The rules state opening from Monday to Friday.

Read the fact-checking example

Illustrated result

The documents contradict each other. Saturday opening still has to be confirmed with the department.

Human check

Check the dates and the sources, then contact the department before publishing a conclusion.

Simulated example / Your application-screening AI

Prepare the questions for an interview.

Fictitious profile

The job calls for project management and professional English. The profile mentions project coordination without stating an English level.

Read the recruitment example

Illustrated result

Project experience is picked out. The English level is to be confirmed at the interview.

Human check

The recruiter checks the background and talks with the person. This example neither ranks nor rules out any application.

Simulated example / Your customer follow-up AI

Prepare a reply from a procedure.

Fictitious procedure

A product return requires the manager's approval. A customer wants to send their product back without having obtained that approval.

Explore what your AI does by profession

Illustrated result

The procedure requires approval before the return. Prepare a reply and involve the manager.

Human check

The advisor checks the applicable procedure and approves the reply. This demonstration sends no message.

02 / On your premises

Your AI, installed on your premises or hosted.

Understand both options

Each project is built bespoke, for a specific job: your AI is installed on your premises — a custom-built machine or an off-the-shelf model such as the NVIDIA DGX Spark — or hosted. On-premises installation is the decisive advantage when the sensitivity of your data demands it; hosting is often enough to get started faster. The choice is made with you, according to your uses, your data and your resources.

Data that stays on your premises
Your information stays on your machine, under your control. Nothing leaves it by default; when a feature needs an outward connection, we tell you what leaves and you decide whether to accept it.
Readable work
One request, work prepared by your AI, then an identified validation step.
Defined access rights
Rights and permitted actions are set according to the team's roles.

Being on your own premises is not an obligation, it is a decision: when the sensitivity of your data allows it, hosting gets your AI into service faster and asks less upfront, and you can move on premises later, once the project has proven itself. The machine, the connections and the place of installation are chosen according to your uses, your data and your resources.

03 / The method

From the decision
through to delivery.

We start by helping you decide: how far the AI goes, where it stops, and what it can change in your professions. Then we install it and support your teams, keeping a human validation at every sensitive step.

See how a support engagement runs

  1. Clarify the decision

    Show you what the AI can do today and where it stops, so you can decide on an informed basis and with the stakes in mind: jobs, data, dependency, costs, resource use.

  2. Choose a scope

    Observe the current task, the available information and the decisions that must stay human. Define the acceptance criteria together.

  3. Install on your premises and connect your tools

    Install your AI on your server, connect the tools it needs, set the rights and check the validation steps before go-live.

  4. Support the team

    Train the users, explain how it works and plan follow-up on errors, costs and changes.

04 / Choosing with awareness

Staying in control is part of the project.

An AI can be wrong or can be missing information. We define its permissions, the checks to perform and the situations in which it must stop — and we discuss openly what its use changes for your teams and for society.

Human validation
Sensitive decisions and binding actions remain subject to a named person.
The data scope
Your data stays on your premises, on your server. The sources, the access rights and the retention rules are defined before any connection.
The limits of the result
Missing sources and uncertain information must be flagged, then checked.
The option to stop
Plan for a manual fallback and for suspending your AI when a check reveals a problem.
How far the AI goes: the questions that decide

The next step

What task would you like to hand over to your AI?

Describe the current work, your tools and what is blocking you. We can then frame a first use case and the questions to answer before we build it — through to installing your AI on your premises.

Describe my project

You do not need to have chosen a technology yet. What matters is knowing which decision you want clarity on.