We eat what we cook. Daily.

The distinction matters. Presenting Cockpit as “our product” would invite a fair question: why not just sell it to us directly, instead of building something bespoke? That question would contradict our entire positioning — we are not a vendor of generic software, we build a different system for each precise process. Framed as a laboratory, on the other hand, Cockpit becomes the proof that we practise what we sell: a real system, not a theoretical methodology.

No conventional AI consultancy can show you this. It is the argument itself, not the dressing on a weaker one.

If we had to describe it with the software categories every executive knows: our laboratory is at once a CRM (customer relationship management and a B2B sales prospecting pipeline), a management tool (reconciling cash-flow movements, tracking payment terms) and an operations dashboard (live views for the whole team). Except no off-the-shelf package did all three on our own processes — which is precisely why it exists.

On the sales side: targeting prospects, sending mailing campaigns rotated across several inboxes, qualifying replies and entering them into the pipeline all run without manual intervention — the sales team steps in only when a reply deserves a human pitch. Neither generic marketing automation nor forms to configure: measurable sales efficiency, serving real commercial and marketing work. On the finance side: digitising paper archives (scanned then read by OCR) feeds the automatic reconciliation against bank and invoices. And because prospecting handles personal data, compliance is part of the design, not an afterthought.

The time saved is the real deliverable: hours returned each week on tasks no one will miss — plus a reading of the data that serves sales performance and day-to-day management alike, exports included. No configuration of a generic solution would have produced this: it is the difference between bending your process to fit a SaaS package and doing real software development around the process, integrations included.

Before: sorting inbound requests (prospecting, client emails) was done by hand, with no reliable classification or prioritisation — repetitive work, prone to human error the moment volume climbs.

After: a qualification engine sorts and prioritises every inbound request automatically, with a classifier calibrated on nuanced French vocabulary — not a simple keyword filter. Measured result: several hundred emails processed per day, with no reported error since going into production.

This is exactly the kind of transformation — one precise, measurable process, never “the whole company automated at once” — that we rebuild for every engagement. The detail of this system is on the qualification engine page.

The most telling thing is not a figure, it is an ordinary day. Before anyone opens their inbox, whatever arrived overnight is already read, sorted, prioritised — serious requests at the top, noise at the bottom. The day’s prospecting campaigns go out on schedule, inbox after inbox, and every reply enriches the pipeline without anyone re-keying it anywhere. Meanwhile, the previous day’s bank movements have found their invoices, and the discrepancies — there are always some — wait, listed, for a human to decide.

That is our conviction about what “AI in the business” actually means: nothing spectacular on screen, and hours returned every week. A system that works while no one is watching it — which is exactly what a demo can never show.

A system in production goes through incidents — ours too. What sets a serious practice apart is not their absence, it is what you do with them. With us, every incident ends up in a dated log, every lesson becomes a permanent written decision, and every decision applies to the releases that follow. In practice, today’s system is better than last month’s for documented reasons, not by magic.

That discipline travels with us: more than the code itself, it is what we bring to an engagement. A client inherits a log, written rules, a history of fixes — not a black box dropped off on a Friday evening.