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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Quantara AI launches a continuous platform designed to estimate the financial impact of cyber risk as companies move beyond periodic assessments
Updated
March 17, 2026 1:02 AM
A person tightrope walking between two cliffs. PHOTO: UNSPLASH
Cyber risk is increasingly treated as a financial issue. Boards want to know how much a cyber incident could cost the company, how it could affect earnings, and whether current security spending is justified.
Yet many organizations still measure cyber risk through periodic reviews. These assessments are often conducted once or twice a year, supported by consultants and spreadsheet models. By the time the report reaches senior leadership, the company’s systems may have changed and new threats may have emerged. The way risk is measured does not always match how quickly it evolves.
This gap is where Quantara AI is positioning its new platform. Quantara AI, a Boise-based cybersecurity startup, has introduced what it describes as the industry’s first persistent AI-powered cyber risk solution. The system is designed to run continuously rather than rely on occasional assessments.
The company’s core argument is straightforward: not every security weakness carries the same financial consequence. Instead of ranking issues only by technical severity, the platform analyzes active threats, identifies which company systems are exposed, and estimates how much money a successful attack could cost. It uses statistical models, including Value at Risk (VaR), to calculate potential losses. It also estimates how specific security improvements could reduce that projected loss.
The timing aligns with a broader market shift. International Data Corporation (IDC) projects that by 2028, 40% of enterprises will adopt AI-based cyber risk quantification platforms. These tools convert security data into financial estimates that can guide budgeting and investment decisions. The forecast reflects growing pressure on security leaders to present risk in terms that boards and regulators understand.
Traditional compliance and risk management systems often focus on meeting regulatory standards. Vulnerability management programs typically score weaknesses based on technical characteristics. Consultant-led risk studies provide detailed analysis, but they are usually performed at set intervals. In fast-changing threat environments, that model can leave decision-makers working with outdated information.
Quantara’s platform attempts to replace that periodic process with continuous measurement. It brings together threat data, internal system information and financial modeling in one system. The goal is to show, at any given time, which specific weaknesses could lead to the largest financial losses.
Cyber risk quantification as a concept is not new. What is changing is the expectation that these calculations be updated regularly and tied directly to financial decision-making. As cyber incidents carry clearer monetary consequences, companies are looking for ways to measure exposure with greater precision.
The broader question is whether enterprises will shift fully toward continuous, AI-driven risk analysis or continue relying on periodic external assessments. What is clear is that cybersecurity discussions are moving closer to financial reporting — and tools that estimate potential loss in dollar terms are becoming central to that shift.