Ultrain, a promising blockchain platform, has announced that it has raised $20 million from venture capital firms such as Danhua Capital (DHVC), Arrington XPR Capital, OK Gang Fund, Evolution Capital, Consensus lab and CDC Capital.
— Ultrain Community (@UltrainB) July 30, 2018
Ulltrain was founded by Ray Guo, Emma LIAO and William Li in 2017. Guo and Li previously worked at Chinese e-commerce giant Alibaba, as the ex-director of the security unit and Ant Financial blockchain’s ex-technical director and chief architect, respectively.
Ultrain is committed to resolving blockchain bottlenecks both from the consensus layer and the smart contract layer, in order to support tangible and real business applications as a trust computing infrastructure.
Earlier this month, Ultrain launched a product that allows the platform to process over 3,000 Transactions Per Second (TPS) within 10 seconds. In a conversation with Coindesk, Gou said, “Alipay has 150 million daily active users, its peak TPS on normal days is around 4,000 to 5,000. The next step for dapps is breaking 1 million daily active users. Therefore a public blockchain with 3,000 TPS will be enough for dapps for at least two years.”
Last week, Ultrain was named the “The Rising Star of Blockchain 2018” at the China-US Entrepreneur & Investment Summit held at Silicon Valley.
Ultrain’s roadmap uses stars and black holes to explain its various phases. The ‘Nova’ phase was completed last month with the launch of the internal testnet, smart contract and Robin frameworks. The second phase, known as ‘Supernova’, will launch a public testnet on September 2018. The third phase ‘Black Hole’ will take place on January 2019 with a proper blockchain OS core structure. It will be followed by ‘White Hole’, where Ultrain will have an operation public network and sharding. In April 2020, ‘Big Bang’ will bring the AI machine learning platform. The last event, with no date set so far, is titled ‘Singularity’ and will result in a collaboration between machine learning platforms, IOT and deep belief networks.