How many AI courses have you already paid for with nothing to show for it? It's a pointed question, but a fair one. “We trained two people. Nothing changed.” We hear that at every first meeting.
And it says it all: the problem is almost never the tool. It's the gap between what gets taught and the work people actually do. Our AI training starts at the other end. Your documents. Your case files. Your processes. We train your teams on their real use cases, then check that they can do it again without us. An AI agency that teaches, not a training provider running through a generic catalogue.
Three audiences: leaders (“decide”), business teams (“do”), technical teams (“build”).
Three formats: on site, remotely, or in-house. In-house training takes place at your offices, using your data and tools.
A promise we can keep: every participant leaves with a method applied to a real case, not notes and a satisfaction survey.
Your trainer deploys AI every day. What they show in the morning, they put into production the week before.
Three reasons, in order.
In 2025, 18% of French companies with 10 or more employees reported using at least one AI technology, three times as many as in 2023. But 54% of those not using it cite a lack of expertise. And 53% of those using it say exactly the same thing. In other words, we're deploying AI faster than we're training people. That's the gap holding things back.
Since 27 July 2026, Article 4 of the AI Act, as amended by Regulation (EU) 2026/1744, requires providers and deployers of AI systems to take measures to promote AI literacy among their staff, without imposing a specific level. Training can be one of these measures, but it is not mandatory in itself. The details are summarized in the European Commission's AI literacy FAQ.
Learning to use AI today is above all about knowing how to choose: what works with your data, what doesn't, and what would cost more than doing nothing.
AI training for businesses should not be designed for a generic “audience”; it should be designed for a role. A leader doesn't need the same training as a case manager or a developer.
Half a day (3 to 4 hours), in a small group.
Deliverable: a prioritization grid filled in with your own use cases.
1 day (6 to 7 hours), 6 to 12 people, working with your documents.
Deliverable: a usage guide written during the session, ready for the team to reuse.
2 days, groups of 4 to 8.
Deliverable: a working prototype connected to a test dataset.
One thing in common: AI training for a business is pointless if the use cases aren't selected before anyone enters the room. That's what the scoping phase is for.
For accounting firms: the business teams' training day is built around your files (client documents, follow-ups, engagement letters, summaries for your clients), with extra focus on professional confidentiality and on what can, or cannot, leave the firm.
For law firms: a day working with anonymized case files from your firm, with a section dedicated to professional secrecy.
We come to you. Ideal for business teams: we work with your files, in your environment, with your network constraints. Based in the PACA region (Marseille, Aix-en-Provence, Toulon, Avignon), we work throughout France.
By video call, in half-day sessions to avoid overload. Useful for teams spread across locations, or as a first introduction to AI before a more intensive in-person session.
The most requested format for AI training in a business: the session is built for you, closed to others, with no content shared with other organizations. Your use cases, your data, your tools. The examples are real, so the questions are too.
Unsure whether to choose on-site or remote training? We decide based on the use case, not our logistical preferences.
Four stages. Each with a verifiable deliverable.
1 to 2 weeks before the session
Three to five real use cases collected from participants, available data checked, and the group's level assessed.
Deliverable: a tailored program and a set of use cases.
According to the program
70% hands-on practice, 30% theory. We open the tools in the first hour.
2 to 4 weeks later
Each participant applies the method to a case file from their everyday work. A one-hour group follow-up.
1 to 3 months
We address real obstacles, formalize the usage guide, and identify what is worth automating — and what is not.
Our rule: “no vague promises.” A program, a date, deliverables. If scoping shows that training isn't the right answer, we say so too.
At the end, we don't measure satisfaction. We measure capability.
The last point is the real indicator. When a team comes to a meeting with three use cases it has identified on its own, the training has worked.