SaaS Case Study
Meridian Technologies
A demand forecasting model that reduced both stockouts and overstock.
+25%Feature Adoption
The Challenge
Where things stood before
Meridian Technologies came to us with a problem that had been building for a while: a product experience that couldn't personalize or scale the way the market expected.
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 demand forecasting model that reduced both stockouts and overstock, built specifically around what Meridian Technologies needed.
- Structured so Meridian Technologies's own team could monitor and maintain it going forward
- Built using Python and PyTorch for a stable, maintainable foundation
- Delivered within a 9-week timeline without cutting scope
- Designed around Meridian Technologies's actual data and workflow, not a generic template
Results
The impact, by the numbers
+25%
Feature Adoption
98.0%
Model Accuracy
-25%
Support Tickets
94.3%
Uptime
Tech Stack
Built with
PythonPyTorchBigQueryRedis
Argenta Medical Group
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