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ML + Retail•2024

E-commerce AI

We engineered a deep-learning recommendation engine that analyzes behavioral patterns in real-time to deliver hyper-personalized shopping experiences.

Client

Global Retail Solutions

Service

Full-Stack Development

E-commerce AI

The Challenge

Conversion rates were stagnant due to generic product suggestions that didn't resonate with individual user behavior.

The Results

  • 30% increase in average order value

  • 25% higher product click-through rate

  • Real-time personalization at scale

Tech Stack

Next.js
Python
PyTorch
Supabase