The funding highlights how service robotics is shifting from niche deployments to scaled commercial use across global markets
Updated
April 24, 2026 2:26 PM
An autonomous service robot with a cat face design standing inside a McDonalds restaurant. PHOTO: ADOBE STOCK
Pudu Robotics, a Shenzhen-based startup building robots for commercial environments, has raised nearly US$150 million in a new funding round, pushing its valuation past US$1.5 billion. The raise brings the company’s total funding to more than US$300 million.
The company focuses on service robotics across sectors such as delivery, cleaning and industrial logistics. Its systems are used in places like retail stores, warehouses and public venues where routine tasks can be automated. Over time, Pudu has expanded from single-purpose machines to a broader portfolio that combines hardware with AI-driven navigation and coordination.
The funding is expected to support several areas of growth. These include further development of its AI systems, expansion of its product range and continued international rollout. The company also plans to invest in manufacturing and supply chain capacity, suggesting a focus on scaling production alongside demand.
Pudu’s recent growth provides some context for the raise. The company reported a doubling of revenue by 2025, with its cleaning robots now accounting for the majority of its business. Its industrial delivery robots have also seen early traction, with thousands of units deployed within a year of launch.
Its products are already in use with large global retailers including Carrefour, Walmart and EDEKA. Industry estimates place Pudu among the largest players in commercial service robotics, with a leading share of the global market.
Technically, the company develops much of its core stack in-house, including navigation systems, multi-robot coordination software and motion control. This allows its robots to operate in complex real-world environments where multiple machines need to move and work together.
“This financial milestone is a powerful confirmation of Pudu’s industry leadership, the strength of its products and technology, its global brand, and its commercial infrastructure. With the support of our strategic investors and industry partners, Pudu will continue to push the boundaries of embedded AI and business service robotics. We remain committed to innovating with an inventor’s spirit and leveraging a global vision to accelerate robot adoption, thereby elevating the industry to new heights in the global value chain”. said Felix Zhang, founder and CEO of Pudu Robotics.
The funding round points to a broader shift in the sector. As service robotics moves from pilot deployments to wider adoption, companies are increasingly being judged on their ability to scale production and operate across markets, not just on the novelty of their technology.
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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.