
What is AI Computer Vision in Fashion Retail and E-commerce?
What is AI Vision (Computer Vision, Image Prediction)? Why Is Highly Trained AI Important In Fashion Retail? Think of AI
Our automated product content solution leverages the latest advancements in computer vision artificial intelligence and other technologies to create and distribute smart, engaging product-personalized descriptions, metadata and search tags to your online store’s product pages. Current product content management costs global fashion e-commerce billions each year, and throttles product availability. With Catecut, brands and marketplaces can achieve sales and searchability in seconds!Like our technology, the goal for Cut to the Blog is to share insights and best practices from the fashion e-comm profession, as well as helpful information and news from our team.
Like our technology, the goal for Cut to the Blog is to share insights and best practices from the wardrobe styling profession, as well as helpful information and news from our team.
What is AI Vision (Computer Vision, Image Prediction)? Why Is Highly Trained AI Important In Fashion Retail? Think of AI
Reykjavik, Iceland (14 April 2025) Catecut, an AI-powered platform that automates product tagging and SEO optimization for fashion e-commerce, announced
Discovering 1200+ Brands at CIFF 25: Key Insights on Fashion and Retail Trends from the show floor: many brands and retailers still manually input data or rely on basic descriptions provided with their Shopify setup.
This is where our custom AI models excel. Retailers send their product images via API or other methods, and our AI models analyze, tag, and categorize each item, sending this information back to retailers to enhance their product descriptions (in multiple languages!), boosting on-site filtering and search, as well as SEO/GEO to attract new traffic.
Heading to CIFF – Copenhagen International Fashion Fair? We are too! We are excited to head to CIFF- Copenhagen International
A sharp increase in returns management spending in 2024 means apparel returns are cutting more deeply into overall per-sale revenue. Current solutions aren’t solving the returns problem, and in fact, may be increasing the consumer behavior of bracketing. The biggest gap in solving the returns problem, is addressing the mismatch between a garment’s cut and fit, and the shopper’s body structure.
Bracketing occurs when shoppers order multiple sizes of the same garment, with the intention of returning the sizes that do not fit. Sizing inconsistencies leave shoppers feeling like bracketing is their only choice. This creates both a logistical headache for retailers and contributes to increasing garment waste in the fashion industry.