Overview

Engagement overview

Fashionphile sought to streamline the procurement process for luxury resale products by automating product identification and pricing. The organization worked with TO THE NEW to implement an AI-based solution on AWS that supported image quality validation, image orientation correction, style classification, and product price prediction. The initiative reduced manual intervention across the procurement workflow, improved image processing, and enabled faster product evaluation while supporting pricing decisions based on historical trends and customer demand.

Our client

E-commerce
 USA

FashionPhile is one of the largest and most trusted recommerce platforms specializing in ultra-luxury handbags, jewelry, watches, shoes, and accessories. The company combines digital and omnichannel experiences with luxury in-person services, enabling customers to buy and sell authenticated luxury products through a seamless resale marketplace.

FashionPhile

Business objective

Fashionphile aimed to automate key procurement activities to improve operational efficiency and accelerate product evaluation.

01

Minimize manual intervention across the procurement process

02

Automate image quality validation and image orientation correction

03

Improve product style identification through automated image classification

04

Optimize product pricing using historical trends and demand patterns

05

Accelerate the go-to-market process for resale products

Business solution

TO THE NEW worked with FashionPhile to implement an AI-powered solution using AWS services that automated image processing, pricing, and demand forecasting across the procurement workflow.

  • Used AWS SageMaker Image Classification to identify and remove low-quality product images

  • Introduced automated image orientation correction before downstream processing

  • Classified product images into their respective styles using image classification models

  • Used AWS Forecast to identify demand trends and seasonal purchasing patterns

  • Applied forecasting models to support product price optimization

  • Supported inventory planning using predicted demand across brands and product styles

  • Used price elasticity models to estimate product demand and expected selling time

Business impact

The AI-powered solution improved procurement efficiency by automating image processing, pricing, and demand forecasting across the resale workflow.

Automated image quality validation, orientation correction, and style classification

AI models identified the most relevant product style from submitted images

Improved understanding of customer purchase trends for business planning

Optimized product pricing using historical sales behavior and demand patterns

Enabled real-time sale price estimation for products submitted for resale

Reduced the overall time required to sell resale products