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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A step forward that could influence how smart contracts are designed and verified.
Updated
January 8, 2026 6:32 PM
ChainGPT's robot mascot. IMAGE: CHAINGPT
A new collaboration between ChainGPT, an AI company specialising in blockchain development tools and Secret Network, a privacy-focused blockchain platform, is redefining how developers can safely build smart contracts with artificial intelligence. Together, they’ve achieved a major industry first: an AI model trained exclusively to write and audit Solidity code is now running inside a Trusted Execution Environment (TEE). For the blockchain ecosystem, this marks a turning point in how AI, privacy and on-chain development can work together.
For years, smart-contract developers have faced a trade-off. AI assistants could speed up coding and security reviews, but only if developers uploaded their most sensitive source code to external servers. That meant exposing intellectual property, confidential logic and even potential vulnerabilities. In an industry where trust is everything, this risk held many teams back from using AI at all.
ChainGPT’s Solidity-LLM aims to solve that problem. It is a specialised large language model trained on over 650,000 curated Solidity contracts, giving it a deep understanding of how real smart contracts are structured, optimised and secured. And now, by running inside SecretVM, the Confidential Virtual Machine that powers Secret Network’s encrypted compute layer, the model can assist developers without ever revealing their code to outside parties.
“Confidential computing is no longer an abstract concept,” said Luke Bowman, COO of the Secret Network Foundation. “We've shown that you can run a complex AI model, purpose-built for Solidity, inside a fully encrypted environment and that every inference can be verified on-chain. This is a real milestone for both privacy and decentralised infrastructure”.
SecretVM makes this workflow possible by using hardware-backed encryption to protect all data while computations take place. Developers don’t interact with the underlying hardware or cryptography. Instead, they simply work inside a private, sealed environment where their code stays invisible to everyone except them—even node operators. For the first time, developers can generate, test and analyse smart contracts with AI while keeping every detail confidential.
This shift opens new possibilities for the broader blockchain community. Developers gain a private coding partner that can streamline contract logic or catch vulnerabilities without risking leaks. Auditors can rely on AI-assisted analysis while keeping sensitive audit material protected. Enterprises working in finance, healthcare or governance finally have a path to adopt AI-driven blockchain automation without raising compliance concerns. Even decentralised organisations can run smart-contract agents that make decisions privately, without exposing internal logic on a public chain.
The system also supports secure model training and fine-tuning on encrypted datasets. This enables collaborative AI development without forcing anyone to share raw data—a meaningful step toward decentralised and privacy-preserving AI at scale.
By combining specialised AI with confidential computing, ChainGPT and Secret Network are shifting the trust model of on-chain development. Instead of relying on centralised cloud AI services, developers now have a verifiable, encrypted environment where they keep full control of their code, their data and their workflow. It’s a practical solution to one of blockchain’s biggest challenges: using powerful AI tools without sacrificing privacy.
As the technology evolves, the roadmap includes confidential model fine-tuning, multi-agent AI systems and cross-chain use cases. But the core advancement is already clear: developers now have a way to use AI for smart contract development that is fast, private and verifiable—without compromising the security standards that decentralised systems rely on.