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Cutting costs in the fashion industry through virtual fabric samples: Inside China’s Startups


Technology has been revolutionizing the world of garments and the fashion industry, with tech startups tapping new verticals amid the COVID-19 pandemic. Beijing-based fashion tech startup HeartDub is one of them. The company digitizes textiles via artificial intelligence (AI) to facilitate transactions between textile manufacturers and their customers.


Founded in 2018, the company’s software simulates how clothes could look on a human body, simplifying the costly and time-consuming negotiation process between manufacturers and buyers, which often involves shipments of samples before closing a contract.


“The effect generated by our system is very genuine and can be applied to different fabrics, patterns, and sizes,” said Huang Jingshi, CEO and co-founder of HeartDub to KrASIA. He launched the company together with Zhou Jiaxuan, currently the company’s chief operating officer, and Li Ruohao, its chief technology officer. HeartDub currently a group of about 30 employees scattered around Beijing in China, Seattle in the US, and Manchester in the UK. Most of its technical team members studied at the Massachusetts Institute of Technology. 


Huang said that the company wants to solve a specific pain point in the industry. “Because of the diversity and complexity of fabrics, before a garment manufacturer makes a purchase, it has to touch the real thing and has to make clothes out of sample fabrics to make sure it is what they want.” The back-and-forth process could take weeks and also generate waste along the way. When it comes to cross-border deals, the delivery time could be even longer, Huang explained.


The company has therefore developed a system that allows its clients to match textiles with a variety of colors, clothing designs, patterns, and virtual model’s movements, within a few clicks. HeartDub’s solution is able to cut development production costs by 50%, while shortening sample delivery time by 90%, according to Huang.


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