Retail Case Study
Cyphergate Commerce
A predictive maintenance system that flagged equipment failure risk weeks early.
+24%Conversion Rate
The Challenge
Where things stood before
Cyphergate Commerce came to us with a problem that had been building for a while: manual processes that couldn't scale with a growing catalog and customer base.
It wasn't a small fix — the underlying approach needed to change, not just the surface.
The Solution
What we built
We started by getting a clear picture of exactly where things were breaking down before proposing anything.
From there, a predictive maintenance system that flagged equipment failure risk weeks early, built specifically around what Cyphergate Commerce needed.
- Delivered within a 9-week timeline without cutting scope
- Validated thoroughly before deployment to avoid production surprises
- Designed around Cyphergate Commerce's actual data and workflow, not a generic template
- Structured so Cyphergate Commerce's own team could monitor and maintain it going forward
Results
The impact, by the numbers
+24%
Conversion Rate
+57%
Forecast Accuracy
-38%
Manual Review Time
+32%
Revenue Lift
Tech Stack
Built with
PythonPyTorchOpenCVMQTT
Duskwood Technologies
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