Real cases

Industrial AI for coffee, culinary, snacks and foodservice groups

A food group that roasts coffee, cans vegetables, produces pasta and couscous and also supplies its own restaurants doesn't run one factory: it runs four technologically distinct processes under a single manufacturing directorate. Roasting, extrusion and drying, canning and retort, and central kitchen. Each with its own vocabulary, its own critical machines and its own failure modes.

When those plants have also been brought in through acquisition, in different countries and from different owners, the problem that defines the sub-sector appears: every plant explains itself in its own language. It measures waste, yield and cost per kilo on its own definitions, on its own ERP and with its own paper logs. The practical consequence is that the group's factories cannot be compared with each other, and every integration takes months to produce visibility.

These pages hold twelve real industrial AI cases applied to that reality: capturing what is lost today in each process without changing anyone's habits, stitching together the systems that already exist instead of replacing them, putting machine vision where the human eye can't keep up with line speed, and letting the audit evidence pack assemble itself. The final case coordinates all of them so the plants start speaking one operational language — without replacing a single ERP.