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 closer look at how machine intelligence is helping doctors see cancer in an entirely new light.
Updated
January 8, 2026 6:33 PM
Serratia marcescens colonies on BTB agar medium. PHOTO: UNSPLASH
Artificial intelligence is beginning to change how scientists understand cancer at the cellular level. In a new collaboration, Bio-Techne Corporation, a global life sciences tools provider, and Nucleai, an AI company specializing in spatial biology for precision medicine, have unveiled data from the SECOMBIT clinical trial that could reshape how doctors predict cancer treatment outcomes. The results, presented at the Society for Immunotherapy of Cancer (SITC) 2025 Annual Meeting, highlight how AI-powered analysis of tumor environments can reveal which patients are more likely to benefit from specific therapies.
Led in collaboration with Professor Paolo Ascierto of the University of Napoli Federico II and Istituto Nazionale Tumori IRCCS Fondazione Pascale, the study explores how spatial biology — the science of mapping where and how cells interact within tissue — can uncover subtle immune behaviors linked to survival in melanoma patients.
Using Bio-Techne’s COMET platform and a 28-plex multiplex immunofluorescence panel, researchers analyzed 42 pre-treatment biopsies from patients with metastatic melanoma, an advanced stage of skin cancer. Nucleai’s multimodal AI platform integrated these imaging results with pathology and clinical data to trace patterns of immune cell interactions inside tumors.
The findings revealed that therapy sequencing significantly influences immune activity and patient outcomes. Patients who received targeted therapy followed by immunotherapy showed stronger immune activation, marked by higher levels of PD-L1+ CD8 T-cells and ICOS+ CD4 T-cells. Those who began with immunotherapy benefited most when PD-1+ CD8 T-cells engaged closely with PD-L1+ CD4 T-cells along the tumor’s invasive edge. Meanwhile, in patients alternating between targeted and immune treatments, beneficial antigen-presenting cell (APC) and T-cell interactions appeared near tumor margins, whereas macrophage activity in the outer tumor environment pointed to poorer prognosis.
“This study exemplifies how our innovative spatial imaging and analysis workflow can be applied broadly to clinical research to ultimately transform clinical decision-making in immuno-oncology”, said Matt McManus, President of the Diagnostics and Spatial Biology Segment at Bio-Techne.
The collaboration between the two companies underscores how AI and high-plex imaging together can help decode complex biological systems. As Avi Veidman, CEO of Nucleai, explained, “Our multimodal spatial operating system enables integration of high-plex imaging, data and clinical information to identify predictive biomarkers in clinical settings. This collaboration shows how precision medicine products can become more accurate, explainable and differentiated when powered by high-plex spatial proteomics – not limited by low-plex or H&E data alone”.
Dr. Ascierto described the SECOMBIT trial as “a milestone in demonstrating the possible predictive power of spatial biomarkers in patients enrolled in a clinical study”.
The study’s broader message is clear: understanding where immune cells are and how they interact inside a tumor could become just as important as knowing what they are. As AI continues to map these microscopic landscapes, oncology may move closer to genuinely personalized treatment — one patient, and one immune network, at a time.