Argenta Medical Group
A fraud detection system that cut chargebacks without over-flagging legitimate orders.
Where things stood before
Argenta Medical Group's biggest obstacle was administrative and clinical workflows that hadn't kept pace with the volume they were handling — something their team had tried to patch more than once without lasting success.
Their team suspected AI could help but weren't sure where to actually start.
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 fraud detection system that cut chargebacks without over-flagging legitimate orders, built specifically around what Argenta Medical Group needed.
- Built using Python and PyTorch for a stable, maintainable foundation
- Benchmarked against clear, agreed-upon success metrics from day one
- Designed around Argenta Medical Group's actual data and workflow, not a generic template
- Validated thoroughly before deployment to avoid production surprises
The impact, by the numbers
Built with
Brookhaven Capital
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