DeepCtrls Secured Funding for Physical AI Development
The robotics firm completed a Series B+ financing round led by CATL to bridge the gap between AI and the physical world.
Updated on Sept. 25, 2026 in Robotics
Live Poll
Do you believe integrating AI into physical infrastructure will improve industrial efficiency and energy management?
DeepCtrls has successfully closed a Series B+ financing round led by CATL. The investment will support the company's efforts to integrate its proprietary AI engine into industrial systems.
Why it matters
The funding supports the broader transition of artificial intelligence from digital applications into real-time control of physical hardware. This shift is critical for sectors like manufacturing and energy that require precise, AI-driven physical coordination.
DeepCtrls, founded in 2018, utilizes its proprietary PhyAI Physical AI Engine to manage complex systems. The company specializes in intelligent liquid cooling and computing-energy coordination for industrial applications.
The players
DeepCtrls
An industrial technology company founded in 2018 that develops physical AI engines for real-time systems control.
CATL
A global leader in battery manufacturing and energy storage technology that led the recent investment round.
Aramco Ventures
The venture capital arm of the global energy and chemicals producer Saudi Aramco.
The details
DeepCtrls serves customers across the semiconductor, new energy, and data center industries by applying its AI engine to real-world physical systems. The company plans to leverage this new capital to extend its Physical AI capabilities into AI infrastructure.
Timeline
DeepCtrls was founded in 2018.
The company completed its Series B+ financing round in September 2026.
The Tech Race
The integration of the PhyAI Physical AI Engine into infrastructure marks a pivotal move toward cyber-physical convergence. This trajectory positions the firm against traditional automation providers by prioritizing active system management over passive data monitoring.
The firm's work on intelligent liquid cooling and energy coordination directly impacts data center efficiency and advanced manufacturing costs. Users in these sectors may see improved hardware longevity and reduced energy overhead as these AI solutions scale.
The takeaway
The move signifies that the most valuable AI applications are increasingly shifting from digital chatbots to physical industrial control. Industry leaders should monitor how this hardware-software integration affects efficiency standards in energy and manufacturing.
Further reading
For more information on the evolving landscape of automated systems, visit our Robotics section.
More information
Learn more about the company's technical solutions at the DeepCtrls official website.
Source note: This article includes information reported by Antara News.
Live Poll
Do you believe integrating AI into physical infrastructure will improve industrial efficiency and energy management?
