raises $8 million led by Hillhouse to create AI-generated fashion models – TechCrunch

With breakthroughs in machine learning, it’s no longer uncommon to see algorithmically generated bodies that can move and talk authentically like real people. The question now is whether startups that offer such products can realize a sustainable business model. Some of them have demonstrated that potential and attracted investors.

Founded by a team of Chinese entrepreneurs who have studied and worked abroad for years, has just completed an $8 million Series A funding round led by Hillhouse Capital. GGV Capital and GSR Ventures also participated in the round.

The startup has found healthy demand from fashion e-commerce companies struggling to hire and pay models due to their growing number of inventory units (SKUs) or styles as consumer tastes become more volatile. Using the generative adversarial network (GAN), ZMO has created a piece of software to help them create virtual full models by defining simple parameters such as face, height, skin tone, body shape and pose.

“Traditionally, the entire clothing production cycle can take two to three months, from design, fabric selection, pattern making, modeling to actually hitting the shelves,” said Ella Zhang, ZMO’s CEO and co-founder, a former engineer at Google and Apple. .

“We are turning that process around and shortening it. [Customers] can now test a piece of clothing by putting it on a virtual model, which can be done on the website. Once the orders come in, the ecommerce customer can start producing,” she tells TechCrunch. “They can also test what type of people would fit a particular product by trying it out on different virtual models.”

Unsurprisingly, fashion ecommerce operators would find ZMO and its likes a cost-effective tool. Zhang says her company is initially in talks with fast fashion giant Shein, who rolls out 2,000-3,000 new products a day, about possible collaborations.

Screenshot of ZMO .’s AI-generated video

We’ve previously covered Surreal, a Sequoia-backed Shenzhen-based startup that is also working on synthetic media to replace people in lifestyle photos and other commercial scenarios. The company attracted a lot of interest as the COVID-19 pandemic hit Chinese e-commerce exporters, who struggled to find foreign models due to the country’s strict border controls.

In the future, ZMO also plans to adopt GPT-3, which uses big data and deep learning to imitate people’s natural language patterns, to make speeches for models. As spooky as it may sound, the feature would make it lighthearted for ecommerce companies to quickly and cheaply create TikTok videos for product promotion.

According to Roger Yin, who worked at Evernote and ran his own cross business, e-commerce companies spend an average of 3-5% of their annual gross commercial value (a rough measure of sales, usually excluding returns and refunds) on photo shoots. frontier e-commerce company before co-founding ZMO with Zhang.

“Images play a huge role in driving e-commerce sales. The problem is that the [sales] cycle is short, but the cost of images is high,” notes Yin, adding that the cost can be even higher for fashion companies with a fast turnover of styles. The goal of ZMO is to reduce the cost of photo shoots to 1% of the GMV.

At present, 80% of ZMO’s customers are based in China, but it is trying to attract more foreign users this year with the help of its new financial infusion. The startup has a team of 30 employees and has 30 “medium and large” customers, including Tencent-backed Chicv, one of Shein’s many challengers, and more than 100 “small and medium” customers, such as dropshipping sellers.

Other ZMO co-founders include Ma Liqian, a Ph.D. in computer vision who graduated from KU Leuven in Belgium, and Yang Han, who previously worked on AI-powered styling at Tencent and SenseTime.

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