DeepCtrls, a company focused on Physical AI for energy and computing infrastructure, has completed a Series B+ funding round valued at hundreds of millions of yuan. The round was led by CATL and included a strategic investment from Aramco Ventures. The announcement highlights growing investor interest in artificial intelligence systems that can directly control physical operations rather than only analyze data.
Strategic investors and round participants
CATL led the new financing round, while Aramco Ventures joined as a strategic investor with a clear focus on energy and industrial applications. Taiping Innovation Investment, GF Xinde Investment Management, and Fosun Capital also participated in the round. Existing backers Source Code Capital and Forebright Capital increased their commitments, signaling continued confidence in DeepCtrls and its Physical AI capabilities.
Aramco Ventures and Middle East relevance
Aramco Ventures joins the round as a strategic investor, linking DeepCtrls to energy and industrial opportunities in the Middle East. The Saudi Aramco investment arm focuses on areas such as artificial intelligence, analytics, energy efficiency, automation, and robotics. The deal highlights the potential for Physical AI to support complex energy systems and infrastructure in the region.
Technology focus on Physical AI
DeepCtrls develops a control layer for Physical AI by combining artificial intelligence models with the physical rules of the systems they manage. Its proprietary PhyAI engine enables complex physical systems to predict performance, optimize operations, and act autonomously. This approach moves beyond data analysis to real time control in energy systems, cooling, industrial equipment, and data center infrastructure.
From industrial automation to autonomous operation
The company is targeting a shift beyond traditional automation that relies on predefined rules and fixed operating parameters. Its systems analyze relationships among equipment and continuously determine the most efficient settings for changing conditions. This allows industrial facilities and data centers to respond dynamically to variations in loads, temperatures, and energy consumption.
Energy and computing infrastructure expansion
DeepCtrls is expanding from traditional industrial applications into computing infrastructure, where energy demand and cooling requirements are rising quickly. The company is developing solutions for liquid cooling control and coordination between computing and power systems. These applications are becoming more important as data centers running advanced AI models face growing pressure to manage electricity use and thermal loads efficiently.
CATL and a proven operational relationship
CATL's leadership role carries particular significance because the companies already have an operational relationship. CATL uses DeepCtrls technologies in multiple facilities, starting with a pilot project in an air conditioning station and later expanding to more than ten sites. This progression illustrates how a corporate user can become a strategic investor after validating a technology in real industrial conditions.
Global customers and deployment
DeepCtrls says it serves hundreds of enterprise customers worldwide, including Tencent, ByteDance, NVIDIA, TSMC, LG, and PTT. Its deployments span Asia, the Middle East, Europe, and North America across factories, data centers, and energy infrastructure. The company uses these varied applications to scale solutions from pilot projects to standardized products.
Investor momentum and strategic industrial participation
The Series B+ round follows a rapid series of funding activities, with three rounds closed within two months. The participation of CATL and Aramco Ventures reflects a broader shift in which large industrial companies become strategic investors after testing technologies in real environments. This model gives startups access to large scale facilities and supports the transition from commercial pilots to broader deployments.
The new funding will support DeepCtrls as it works to apply Physical AI more widely across energy and computing systems. As AI infrastructure requires more electricity and cooling, intelligent control of physical operations is becoming central to cost and efficiency. The company aims to position its technology as a key layer for the next phase of AI infrastructure development.