The challenge

An e-commerce brand managed product information across its storefront, inventory system, and marketplace channels. New items were classified and described by hand, which slowed launches and created inconsistent categories, attributes, and stock data.

The team needed one reliable catalog workflow that could speed up updates while preserving editorial control.

Our strategy

We built an AI-assisted catalog pipeline that turns raw supplier data into structured, review-ready product records and keeps approved changes synchronized across platforms.

The workflow included:

• classifying products into the brand’s existing taxonomy
• normalizing sizes, materials, colors, and other product attributes
• drafting accurate, SEO-ready titles and descriptions from source data
• flagging incomplete or low-confidence records for human review
• synchronizing approved product and inventory updates across connected channels

The results

• 5× faster product updates
• Unified catalog data across the storefront, inventory system, and marketplaces
• Better SEO-ready descriptions with consistent product structure and language

The merchandising team could launch and maintain a larger catalog without adding repetitive manual work or losing control over product quality.