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Home/AI for Retail & eCommerce/Brookhaven Capital
Finance Case Study

Brookhaven Capital

A visual search feature that improved product discovery on mobile.

-16%False Positives
Brookhaven Capital digitallyscaled
ClientBrookhaven Capital
IndustryFinance / Fintech
Timeline10 weeks
ServicesAI for Retail & eCommerce
The Challenge

Where things stood before

Before working with us, Brookhaven Capital was dealing with manual review processes that were both slow and inconsistent, and it was starting to cost them real business.

It was the kind of issue that showed up in day-to-day frustration long before it showed up in a report.

The Solution

What we built

Our approach focused on the root cause rather than the most visible symptom.

What we ultimately delivered was a visual search feature that improved product discovery on mobile, built specifically around what Brookhaven Capital needed.

  • Validated thoroughly before deployment to avoid production surprises
  • Designed around Brookhaven Capital's actual data and workflow, not a generic template
  • Benchmarked against clear, agreed-upon success metrics from day one
  • Delivered within a 10-week timeline without cutting scope
Results

The impact, by the numbers

-16%
False Positives
-22%
Review Time
+26%
Detection Accuracy
99.2%
Model Explainability Score
Tech Stack

Built with

PythonPyTorchBigQueryRedis

“What stood out was how grounded the whole approach was, not just chasing what's trendy. -16% false positives within a few months, and that's held up months later.”

JC
Januario Cavendish

COO, Brookhaven Capital

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