Most AI projects fail because they answer the wrong question. We start with the right ones: where is the friction? Which process consumes skilled time? Which gain is measurable within the first week?
Before proposing a solution, we map. Where is the friction? Which task consumes skilled time? Which gain is measurable within the first week? Most AI projects fail because they answer the wrong question.
A workflow that saves 20 h a week is worth more than a flashy AI agent nobody uses. We say no to the wrong ideas — including the ones that make great slides.
Two-week sprints, deliverables tested in real conditions. No big bang at the end of the quarter. Every increment is observable, measurable, and already in production.
Accessible code, up-to-date documentation, team training. By the end of the project, you keep control: of the code, the workflows, the data. No hidden lock-in.
We map your processes — the real ones, the ones running in Notion, in Excel, in Marie-Claire’s head. We identify the value pockets: volumes, time spent, error rate, friction. Deliverable: a map of possible projects, costed and ranked by gain.
1 to 2 weeksWe rank the projects by ROI and feasibility. We make the technology calls (n8n vs custom code, GPT vs Claude vs local model, sovereign hosting or not). Deliverable: a costed roadmap, an iterative delivery plan, an honest budget.
1 weekTwo-week sprints, every increment tested in real conditions with your teams. You get repo access from day 1, a shared Slack, a weekly check-in. No tunnel, no surprises. Deliverable: a workflow or product in production, observable and editable.
4 to 12 weeksBusiness metrics, no vanity. We look at what works, what gets stuck, what deserves to be extended. We adjust, we document, we hand over. Your teams take over and we stay available for the next step.
Ongoing30 minutes to understand your goals. No commitment.
