Robotics

Service Robotics Startup Pudu Raises US$150 Million, Crosses US$1.5 Billion Valuation

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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Artificial Intelligence

How Analog Devices Is Turning Hardware Into Intelligence?

The upgraded CodeFusion Studio 2.0 simplifies how developers design, test and deploy AI on embedded systems.

Updated

January 8, 2026 6:34 PM

Illustration of CodeFusion Studio™ 2.0 showing AI, code and chip icons. PHOTO: ANALOG DEVICES, INC.

Analog Devices (ADI), a global semiconductor company, launched CodeFusion Studio™ 2.0 on November 3, 2025. The new version of its open-source development platform is designed to make it easier and faster for developers to build AI-powered embedded systems that run on ADI’s processors and microcontrollers.

“The next era of embedded intelligence requires removing friction from AI development”, said Rob Oshana, Senior Vice President of the Software and Digital Platforms group at ADI. “CodeFusion Studio 2.0 transforms the developer experience by unifying fragmented AI workflows into a seamless process, empowering developers to leverage the full potential of ADI's cutting-edge products with ease so they can focus on innovating and accelerating time to market”.

The upgraded platform introduces new tools for hardware abstraction, AI integration and automation. These help developers move more easily from early design to deployment.

CodeFusion Studio 2.0 enables complete AI workflows, allowing teams to use their own models and deploy them on everything from low-power edge devices to advanced digital signal processors (DSPs).

Built on Microsoft Visual Studio Code, the new CodeFusion Studio offers built-in checks for model compatibility, along with performance testing and optimization tools that help reduce development time. Building on these capabilities, a new modular framework based on Zephyr OS lets developers test and monitor how AI and machine learning models perform in real time. This gives clearer insight into how each part of a model behaves during operation and helps fine-tune performance across different hardware setups.

Additionally, the CodeFusion Studio System Planner has also been redesigned to handle more device types and complex, multi-core applications. With new built-in diagnostic and debugging features — like integrated memory analysis and visual error tracking — developers can now troubleshoot problems faster and keep their systems running more efficiently.

This launch marks a deeper pivot for ADI. Long known for high-precision analog chips and converters, the company is expanding its edge-AI and software capabilities to enable what it calls Physical Intelligence — systems that can perceive, reason, and act locally.  

“Companies that deliver physically aware AI solutions are poised to transform industries and create new, industry-leading opportunities. That's why we're creating an ecosystem that enables developers to optimize, deploy and evaluate AI models seamlessly on ADI hardware, even without physical access to a board”, said Paul Golding, Vice President of Edge AI and Robotics at ADI. “CodeFusion Studio 2.0 is just one step we're taking to deliver Physical Intelligence to our customers, ultimately enabling them to create systems that perceive, reason and act locally, all within the constraints of real-world physics”.