Gaorong Capital, CMBI to co-lead a $26m funding for Chinese AI startup
In an announcement made by Tianrang, the Chinese AI startup confirmed that Gaorong Capital and CMB International (CMBI) will jointly lead a RMB 180 million (USD 26 million) Series A funding round for investing in the company. Ziniu Fund and China-based fintech company Wacai were the other entities who participated in the round, Tianrang informed in the announcement.
For the record, Tianrang was established in 2016 by the former director of Alibaba’s Ali Cloud and Chief Scientist of its cloud platform Alimama, Xu Guirong. The company had initially raised investments through an angel round that was led by Chinese venture capital firm Gaorong Capital, while Shanghai Jindi Investment Management Ltd was the other key participant.
Reportedly, the company offers data analysis and smart solutions for businesses derived from deep learning and other AI technology. Citing a user application, Tianrang’s technology can automatically gather data related to marketing trends and purchase information on Alibaba’s e-commerce platform, then analyze this data and help vendors in making smarter marketing decisions.
Wang Hongbo, the Chief Investment Officer for CMB International Capital, made a statement saying Tianrang decreases the requirements of complex machine decision-making using algorithm and artificial intelligence, making it accessible and scalable for commercial purposes. He added that machine decision-making intelligence has the ability to solve more complex and more frequent problems instead of just replacing simple human decisions, thus extending the scope of AI.
Reliable sources at the Chinese startup further mentioned that the company is planning to set up a city brain lab for accelerating the application of machine learning in urban development. Jessie Li, a noted professor at the College of Information Sciences and Technology at the Pennsylvania State University, will be leading the city brain lab, the sources revealed. As per records, Li’s research is focused on data mining with a special emphasis on mining spatial-temporal data.
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