The CE approval opens Europe for Cornerstone Robotics as the company expands its global surgical robotics business
Updated
May 29, 2026 4:20 AM
A tray of surgical tools. PHOTO: UNSPLASH
As surgical robotics companies expand beyond domestic markets, regulatory approvals are becoming a critical part of global growth. Companies are no longer competing only on hardware and clinical performance. They are also competing on their ability to enter tightly regulated healthcare systems and build long-term hospital partnerships.
Hong Kong-based Cornerstone Robotics is now moving further into that phase of expansion after its Sentire Endoscopic Surgical System received CE Mark certification under the European Union’s Medical Device Regulation framework.
The approval allows the company to commercialize the system across European markets for minimally invasive procedures in general surgery, gynecology, thoracic surgery and urology. For surgical robotics companies, regulatory approvals often represent more than product validation. They also determine market access, hospital adoption opportunities and long-term commercial scale.
Cornerstone Robotics has already been building clinical operations in the UK ahead of the approval. Since 2025, the company has worked with Portsmouth Hospitals University NHS Trust on clinical investigations involving the Sentire Surgical System. According to the company, the system has been used across procedures involving urology, gynecology and gastrointestinal surgery. The company says the clinical investigation helped generate real-world data to support physician training, research and future adoption efforts.
Alongside the regulatory approval, Cornerstone Robotics is also expanding its local operations in Europe. The company established a UK subsidiary in 2025 and has been developing training, clinical support and after-sales service capabilities for hospitals using the system.
That operational buildout reflects a larger challenge inside surgical robotics. Hospitals adopting robotic systems often require ongoing clinical training, technical support and workflow integration alongside the hardware itself.
Cornerstone Robotics says its strategy centers around vertically integrated development across engineering, software, imaging and robotics systems. The company argues that this structure gives it greater control over product development, supply chain management and long-term operational stability.
Professor Samuel Au, Founder and CEO of Cornerstone Robotics, said: "Receiving CE Certification marks a major milestone in Cornerstone Robotics' evolution from a technology innovator to a global clinical solutions provider. From our first clinical investigation in Portsmouth, UK, to achieving European regulatory approval, each step of the journey reflects our commitment to proprietary innovation, product excellence, and clinical value. Looking ahead, we will continue expanding into key global markets and partnering with leading medical institutions to bring high-quality surgical robotic solutions to more physicians and patients worldwide."
The CE approval also comes several months after the company completed an oversubscribed financing round of approximately US$200 million in November 2025.
The funding and regulatory expansion together signal how surgical robotics companies are increasingly entering a more commercially focused stage of growth. Beyond research and development, companies are now investing more heavily in regulatory approvals, hospital partnerships, physician training and international operational infrastructure as competition expands across global healthcare markets.
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Huawei is betting that the future of AI infrastructure will depend as much on energy systems as on computing power
Updated
May 19, 2026 5:43 PM
Blue light painting with a lightbulb. PHOTO: UNSPLASH
As AI companies build larger models and deploy more AI agents, the industry is running into a new constraint: electricity. The challenge is no longer just about computing power. It is increasingly about how to supply, manage and sustain the energy needed to run AI infrastructure at scale.
That was the central argument behind Huawei’s latest AI data center strategy unveiled at its Global AIDC Industry Summit in Dongguan.
The company introduced what it calls a grid-interactive AIDC strategy, focused on redesigning AI data centers around power supply, cooling systems and energy management. AIDC refers to AI data centers built specifically for large-scale AI computing workloads.
The announcement reflects a broader shift happening across the industry. As AI systems grow larger, data centers are consuming more electricity and generating more heat than traditional computing infrastructure was designed to handle. Companies are now being forced to rethink not just chips and servers, but the physical systems supporting them.
Huawei argues that future AI infrastructure will need closer coordination between computing systems and energy grids. The company says traditional data center designs are struggling to keep up with fluctuating AI workloads, rising power density and the growing use of renewable energy sources.
Hou Jinlong, Director of the Board of Huawei and President of Huawei Digital Power, said: "The booming AI industry, widely adopted large models, and numerous AI agents are creating huge energy demands, set to boost the global AIDC capacity. Electricity is essential for computing; energy is the foundation for AI long-term development. Computing and electricity will deeply synergize and empower each other, progressively building an integrated framework that brings together new power systems and AI infrastructure."
A large part of Huawei’s strategy focuses on power architecture. AI workloads can create sudden spikes in electricity demand, especially in high-density computing environments. To manage that, Huawei says it plans to develop new power systems that combine grid-friendly UPS infrastructure with energy storage technologies.
Cooling is becoming another major pressure point. AI servers generate significantly more heat than traditional enterprise systems and Huawei says liquid cooling is now becoming essential for large-scale AI deployments. The company introduced a liquid cooling system designed to improve long-term thermal management inside high-density AI environments.
Huawei is also pushing modular construction methods to reduce deployment times for AI data centers. Instead of building infrastructure entirely onsite, parts of the system can be prefabricated and tested in factories before installation.
Bob He, Vice President of Huawei Digital Power, said: "The global AI industry is booming, and the token demand surges. As such, the AIDC industry is entering the Token era."
As part of that shift, Huawei introduced a proposed measurement system called the TokEnergy Index. The company says the metric is designed to measure the relationship between energy consumption and AI computing output, rather than relying only on traditional data center efficiency metrics such as PUE.
The broader message behind the strategy is that AI infrastructure is becoming an energy engineering problem as much as a computing problem. As global demand for AI continues to rise, companies across the sector are beginning to realise that the future of AI may depend not only on better models, but also on whether power grids and data centers can keep up with them.