Manufacturing Case Study
Yieldline Industries
A cost-optimization review that reduced inference spend without hurting accuracy.
-46%Downtime
The Challenge
Where things stood before
Yieldline Industries's biggest obstacle was limited visibility into production issues until they'd already become expensive — something their team had tried to patch more than once without lasting success.
Competitors and peers seemed to have this figured out already, which only made it more frustrating.
The Solution
What we built
Our approach focused on the root cause rather than the most visible symptom.
The result was straightforward: a cost-optimization review that reduced inference spend without hurting accuracy, built specifically around what Yieldline Industries needed.
- Delivered within a 5-week timeline without cutting scope
- Benchmarked against clear, agreed-upon success metrics from day one
- Built using Grafana and Prometheus for a stable, maintainable foundation
- Designed around Yieldline Industries's actual data and workflow, not a generic template
Results
The impact, by the numbers
-46%
Downtime
+34%
Defect Detection Rate
-17%
Inspection Time
+21%
Throughput
Tech Stack
Built with
GrafanaPrometheusMLflowPython
Undermark Software
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