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.
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METiS TechBio’s blockbuster IPO signals rising investor interest in AI startups focused on how drugs are delivered inside the body
Updated
May 14, 2026 3:02 PM

HIV-1 virus particles, coloured red. PHOTO: UNSPLASH
Investors are beginning to place bigger bets on AI startups focused on drug delivery infrastructure rather than drug discovery alone. That shift was on display this week after METiS TechBio, a Hong Kong tech-bio startup focused on AI-powered drug delivery systems, debuted on the Hong Kong Stock Exchange.
The listing made METiS TechBio the world’s first publicly traded AI-powered drug delivery startup and the first AI-powered large-molecule biopharmaceutical startup listed in Hong Kong. The startup raised more than HKD 2.1 billion through its IPO, making it the largest healthcare listing in Hong Kong so far in 2026.
Investor demand was unusually strong. The Hong Kong public offering was oversubscribed by more than 6,900 times while the international tranche recorded 82 times oversubscription. More than 280 institutional investors participated in the international placing.
The strong demand reflects a wider shift in AI biotech. Over the past few years, much of the sector’s attention has focused on using AI to discover new drugs or molecules. METiS is taking a different approach. The startup focuses on how medicines are delivered inside the body after they are developed.
That challenge is becoming harder to ignore in biotech. Designing a therapy is only one part of the process. Delivering it precisely to specific organs, tissues or cells remains a major hurdle, especially for newer therapies involving RNA, proteins and large-molecule drugs.
METiS is trying to solve that problem through its proprietary NanoForge platform. The system uses AI to design and test nanodelivery systems that help medicines reach targeted areas inside the body more efficiently. The platform combines AI models, simulation systems and high-throughput screening tools to speed up formulation development and improve delivery precision.
The startup says it has already achieved targeted delivery across eight organs and tissue systems including the liver, lungs, heart, muscles and central nervous system.
One of its lead programs, MTS-004, became China’s first AI-enabled formulation drug to complete a Phase III clinical trial. The drug is being developed for pseudobulbar affect, a neurological condition that affects emotional expression. According to the startup, AI tools helped reduce preclinical formulation development time from up to two years to less than three months.
Investor interest in the IPO also came from some of the world’s largest asset managers and healthcare funds. BlackRock led the cornerstone investments with a USD 50 million subscription. Other participating investors included UBS Asset Management Singapore, Mirae Asset, ORIX Corporation, Deerfield, RTW, Hillhouse Capital and IDG Capital.
METiS is also building what it describes as a “platform collaboration + product partnership” business model. The startup currently works with more than 30 pharmaceutical and biotechnology partners globally, including large pharmaceutical companies and medical research institutions.
The company reported RMB 105 million in revenue in 2025, largely tied to upfront payments connected to its MTS-004 partnership agreements. It also said some platform collaboration contracts could reach milestone values of up to USD 109 million.
Chris Lai said: "The future of biomedicine will no longer be simply about 'taking medicine when one falls ill.' METiS TechBio's ambition is to harness AI to build nano-rockets that can navigate with precision through the inner space of the human body's 30 trillion cells, write the code of nucleic acids and proteins into cells, and reprogram diseased and aging cells into healthy cells. This was our founding aspiration, and it is the mission to which we will dedicate our lives. The IPO marks a new starting point for us to accelerate forward, and we will strive to live up to the support and trust we have received from all sectors."
The IPO also highlights how Hong Kong is increasingly positioning itself as a hub for next-generation biotech and AI healthcare startups. While investor excitement around AI drug discovery has cooled in parts of the market, startups focused on delivery systems and biotech infrastructure are beginning to attract stronger institutional backing.
For METiS, the challenge now will be turning that investor confidence into commercially viable therapies and long-term partnerships. But the listing suggests that AI-driven drug delivery is starting to emerge as a category investors are willing to treat as core biotech infrastructure rather than a niche research experiment.