Fintech Case Study
Farrowline Financial
A GPU infrastructure setup built for a demanding model training schedule.
-27%False Positives
The Challenge
Where things stood before
Farrowline Financial came to us with a problem that had been building for a while: manual review processes that were both slow and inconsistent.
The problem was quietly getting more expensive to ignore every month it went unaddressed.
The Solution
What we built
Rather than jumping straight to a model, we spent time understanding the specific shape of the problem first.
The result was straightforward: a GPU infrastructure setup built for a demanding model training schedule, built specifically around what Farrowline Financial needed.
- Built using AWS and GCP for a stable, maintainable foundation
- Validated thoroughly before deployment to avoid production surprises
- Delivered within a 9-week timeline without cutting scope
- Benchmarked against clear, agreed-upon success metrics from day one
Results
The impact, by the numbers
-27%
False Positives
-43%
Review Time
+35%
Detection Accuracy
92.3%
Model Explainability Score
Tech Stack
Built with
AWSGCPKubernetesTerraform
Greywick Retail Group
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