DeepCtrls Secured Series B+ Funding for Physical AI
The startup plans to expand its industrial AI control systems into global data center infrastructure.
Updated on Sept. 25, 2026 in Robotics
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DeepCtrls has completed a Series B+ financing round led by CATL to scale its proprietary Physical AI Engine. The platform integrates AI with physical principles to automate real-time control in energy and manufacturing sectors.
Why it matters
This capital injection supports the transition of AI from digital-only tasks into the physical world, focusing on infrastructure optimization. The funding enables the company to pivot its industrial energy technology toward broader AI data center applications.
The PhyAI Physical AI Engine integrates AI models with real-time physical principles to manage complex industrial systems. While the company provides solutions like intelligent liquid cooling, the specific performance benchmarks for power efficiency gains relative to traditional controllers remain unreleased.
The players
DeepCtrls
A developer of Physical AI engines that integrate software control with mechanical systems for industrial and data center applications.
CATL
A global leader in lithium-ion battery technology and energy storage systems that led the current investment round.
Aramco Ventures
The venture capital subsidiary of the global energy and chemicals corporation that participated in the investment.
The details
The PhyAI Physical AI Engine works by coupling algorithmic AI decision-making with the mechanical and thermal constraints of physical hardware. This integration allows for autonomous real-time control of systems like intelligent liquid cooling loops and computing-energy coordination. The startup uses this method to optimize performance in semiconductor manufacturing, new energy systems, and high-performance data centers across Asia, the Middle East, Europe, and North America.
Timeline
2018: DeepCtrls was founded.
September 2026: DeepCtrls completed its Series B+ financing round.
The Tech Race
The financing signals a move to scale AI control beyond existing niche energy applications and into the rapidly expanding AI infrastructure market. This expansion places DeepCtrls in direct competition with legacy building management and automation systems attempting to adopt machine learning at scale.
Users in the semiconductor, data center, and advanced manufacturing sectors will likely see these control systems integrated into future energy-management workflows. The specific timeline for deployment in individual data centers remains unannounced following this funding round.
The takeaway
The pivot from industrial energy systems into AI infrastructure suggests a growing demand for software-defined physical controls in data centers. Observers should track subsequent pilot projects in AI infrastructure to see if the firm's Physical AI benchmarks hold up at scale.
Further reading
For more on how software is increasingly governing the mechanical world, see our latest coverage in Robotics.
More information
Learn more about the proprietary control technology on the DeepCtrls official website.
Source note: This article includes information reported by Antara News.
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