ChainGPT's robot mascot. IMAGE: CHAINGPT
A step forward that could influence how smart contracts are designed and verified.
Updated
November 27, 2025 3:26 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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Clinically grounded, game-based and always available — MIRDC’s AI system is redefining how children learn to communicate.
Updated
November 27, 2025 3:26 PM
A child practicing with a speech therapist. PHOTO: FREEPIK
Speech and language delays are common, yet access to therapy remains limited. In Taiwan, only about 2,200 licensed speech-language pathologists serve hundreds of thousands of children who need support—especially those with autism spectrum disorders or significant communication challenges. As a result, many children miss crucial periods of language development simply because help isn’t available soon enough.
MIRDC’s new AI-powered interactive speech therapy system aims to close that gap. Instead of focusing solely on articulation, it targets a wider range of language skills that many children struggle with: oral expression, comprehension, sentence building and conversational ability. This makes it a more complete tool for childhood speech and language development.
The system combines game-based learning, AI-driven guidance and automated language assessment into one platform that can be used both in clinics and at home. This integrated design helps children practice more consistently, providing therapists and parents with clearer insight into their progress.
The interactive game modules are built around clinically validated therapy methods. Imitation exercises, picture cards, storybooks and conversational prompts are turned into structured game levels, each aligned with a specific developmental goal. This step-by-step approach helps children move from simple naming tasks to more complex comprehension and response skills, all within a sequenced curriculum.
A key differentiator is the system’s real-time AI speech interpretation. As the child talks, the AI analyzes the response and generates tailored therapeutic cues—such as imitation, modeling, expansion or extension—based on the conversation. These are the same strategies used by speech-language pathologists, but now children can access them continuously, supporting more effective at-home practice and reducing long gaps between sessions.
After each session, the system automatically conducts a data-driven language assessment using 20 objective indicators across semantics, syntax and pragmatics. This provides clinicians and families with measurable, easy-to-understand reports that show how the child is progressing and which skills need more attention—something many traditional tools do not offer.
By offering a personalized, scalable and clinically grounded solution, MIRDC’s AI therapy system helps address the ongoing shortage of speech-language services. It doesn’t replace therapists; instead, it extends their reach, allows for more consistent practice and helps families support their child’s communication at home.
As an added recognition of its impact, the system recently earned two R&D 100 Awards, including the Silver Award for Corporate Social Responsibility. But at its core, the project remains focused on a simple mission: making high-quality speech therapy accessible to every child who needs a voice.