Logistics Case Study
Juniper Bend Group
A delay-prediction system that flagged supplier risk weeks before shipment dates.
-27%Dispatch Time
The Challenge
Where things stood before
Juniper Bend Group's biggest obstacle was no early warning system for disruptions until a shipment was already late — something their team had tried to patch more than once without lasting success.
The problem was quietly getting more expensive to ignore every month it went unaddressed.
The Solution
What we built
Our approach focused on the root cause rather than the most visible symptom.
What we ultimately delivered was a delay-prediction system that flagged supplier risk weeks before shipment dates, built specifically around what Juniper Bend Group needed.
- Designed around Juniper Bend Group's actual workflow, not a generic template
- Tested thoroughly before launch to avoid post-launch surprises
- Built using Python and Node.js for a stable, maintainable foundation
- Delivered within a 8-week timeline without cutting scope
Results
The impact, by the numbers
-27%
Dispatch Time
+42%
On-Time Delivery
-19%
Picking Time
95.6%
Fleet Visibility
Tech Stack
Built with
PythonNode.jsPostgreSQLMQTT
Kestral Bay Group
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