Their manufacturing facilities handle dozens of different shampoo formulations, each with its own bottle design, label variations, and packaging requirements – all running on the same production lines.
But with 89 different shampoo SKUs across five product families and frequent label design changes, Unilever's Quality Control team hit a roadblock. Traditional vision inspection systems weren't cutting it – they needed separate inspection jobs for each SKU, causing production delays and missing critical defects when bottles weren't perfectly oriented for inspection.
That's when Elementary stepped in with a game-changing solution.
Elementary's AI-powered system reduced Unilever's required AI models from 356 to only 20 across their shampoo product lines. The system could spot defects regardless of bottle orientation – from dents and scratches to label misprints and underfilled bottles.
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