Series B Funding Round Raises 100 Million Yuan For Chinese Startup

Sun claims that the business improves the effectiveness of energy systems. Additionally, it aids in filling important management, administrative, and engineering positions at the plant.

Series B Funding Round Raises 100 Million Yuan For Chinese Startup

A Series B funding round led by Xinshang Capital, a division of the Wuxi Municipal State-owned Assets Supervision and Administration Commission, raised nearly 100 million yuan ($14.5 million) for the Chinese startup Extreme Entropy Technology, which offers energy services driven by artificial intelligence (AI).

The “double carbon” policy of the nation, which aims to cap carbon dioxide emissions before 2030 and achieve carbon neutrality before 2060, is the focus of Extreme Entropy Technology, an AI-driven energy asset management company founded in 2014.

The business offers energy asset life cycle driven by AI services, energy consulting, smart system management, algorithms, and optimal management to its clients. Over the past few decades, factories and industrial parks in China have benefited the country’s society and economy.

Industrial parks and manufacturers have emerged as key players in the development of intelligent, low-carbon energy systems as the country’s structural reforms in the energy sector approach a crucial phase.

Since 2010, the Chinese government has pushed for numerous pilot programmes and implemented several policies to aid in the development of green and low-carbon industrial parks, with the associated market now totaling about 300 billion yuan.

According to founder and CEO Sun Donglai, “data is essential to the low-carbonization of industrial parks and manufacturers, and our company was founded to analyse a sizable amount of unstructured data created every day and manage values.”

With the help of cloud-based data collection and analysis, the company’s energy management services primarily focus on electrical systems for industrial parks and businesses, offering operational support and predictive features.

Sun claims that the business improves the effectiveness of energy systems. Additionally, it aids in filling important management, administrative, and engineering positions at the plant.

As a result of the company’s experience and multi-module management developed over the years, Sun also mentioned that it has already accumulated a sizable amount of production data and algorithm models.

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