Deepin Intelligent Control

Deepin Intelligent Control, established in August 2018, is a service provider focused on deep energy conservation and digital intelligence. The company was founded by Dr. Li Hui, who possesses over two decades of experience in the energy efficiency control sector. His background includes work at Tsinghua University and the prestigious Lawrence Berkeley National Laboratory in the U.S. Dr. Li was motivated to create a more scalable and user-friendly solution after winning the AEE's "National Energy Efficiency Award" in the U.S. for a project at Dallas International Airport, which, while successful, required a level of expertise that was difficult to replicate.

The firm targets its solutions at the advanced manufacturing, data center, and public utility sectors, addressing the significant energy consumption of systems like HVAC and compressed air, which can account for 30% to 50% of a facility's total energy use. Its business model is centered on deploying its proprietary technology to help clients achieve substantial reductions in energy consumption and advance their digital transformation. The company has secured significant backing from top-tier investors, including Tencent, Sequoia China, Source Code Capital, and China Merchants Group, completing multiple funding rounds, including a Series A and A+ round in May 2023.

Deepin Intelligent Control's core offering is its "PhyAI" deep energy efficiency engine, a technology that merges physics-based principles with AI. This powers its main product lines: DeepSYS for optimizing central air conditioning and compressed air systems, and DeepOS, an integrated energy management platform. Unlike conventional methods, the company's technology creates high-precision models of a client's entire energy system. This allows for holistic, real-time optimization, identifying the most efficient operational path from hundreds of thousands of possibilities. This approach delivers an additional energy saving of 10-40% on top of existing energy-saving systems and provides functionalities such as predictive fault diagnosis and enhanced operational safety. The system is designed for non-intrusive deployment, significantly reducing installation time.

Keywords: energy efficiency, industrial AI, cleantech, intelligent control, energy management systems, HVAC optimization, compressed air systems, data center cooling, PhyAI, digital transformation, carbon neutrality, smart manufacturing, building automation, predictive maintenance, IoT energy management, deep energy saving, Nanjing, Li Hui, Tsinghua University, Lawrence Berkeley National Laboratory