Case Study: HerMin Textile achieves 25% faster design-to-market with Looker

HerMin Textile Competing in the fashion market using Google and TensorFlow

HerMin Textile, a Taiwan-based woven fabrics supplier for apparel brands worldwide, was struggling with an inefficient manual process for sharing textile designs and facing growing pressure from fast fashion and new designers. The company worked with Looker and Google Cloud services, including TensorFlow, to modernize how it organized, searched, and shared design patterns while improving collaboration among designers.

Looker helped HerMin Textile implement a machine learning system and mobile app that automated textile pattern recognition and made it easier to access and share design images. The solution is expected to help HerMin Textile create more than 10,000 new patterns in two years and reduce time to market for new designs by 25%, from about 12 months to 9 months.

HerMin Textile

Neil Lee

Consultant