Predicting machine failures before they happen — saving £2M+ annually
The challenge
A major manufacturer was losing millions every year when machines broke down unexpectedly. They had no early-warning system — failures came as a surprise and lines went down.
What we built
We connected 800+ sensors across their plants, built a predictive ML model that watches signals in real time, and shipped dashboards that warn operations 7–14 days before equipment fails.
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Results delivered
We used to learn about failures from the shop floor. Now we know two weeks in advance — it's transformed how we run the plant.