Nomagic secures €8.3 million Series B extension
Nomagic, a Warsaw-based warehouse robotics company building general-purpose Physical AI for logistics operations, announced a €8.3 million ($10 million) Series B extension to speed up commercial expansion in the United States. The round was led by Cogito Capital Partners, taking the company’s total funding to more than €70 million ($84 million).
The financing comes as warehouse operators increasingly look to automation to address labor shortages, rising fulfillment expectations, and the complexity of handling ever-larger product catalogs. Nomagic positions its technology as a bridge between software-driven optimization and real-world execution, using robots that can operate continuously in production environments.
What the funding will support
According to the company, the fresh capital will be used primarily to accelerate its U.S. commercial push and to expand development of its next-generation VLA (visual language action) models in 2026. These models are designed to help robots interpret what they “see,” connect it with task instructions, and execute actions—an approach that has gained attention across the robotics sector as AI models become more capable in unstructured settings.
Kacper Nowicki, CEO and co-founder of Nomagic, said the investment validates the company’s strategy of bringing Physical AI deeper into warehouse and logistics workflows. He described the goal as enabling intelligent autonomous systems to close the gap between digital planning and physical operations on the warehouse floor.
Investor view: scaling intelligent automation
Sylwester Janik, managing partner at Cogito Capital Partners, said the firm sees Nomagic as addressing a major transformation need in logistics: adaptable automation that can handle variability in real facilities. He added that the investment reflects confidence in both the company’s technology direction and its leadership team, framing Nomagic as a potential category leader with global ambitions.
How Nomagic says its robots learn
Founded in 2017, Nomagic says its robots learn from large volumes of operational data generated by warehouse work performed around the clock. The company reports that its platform has been trained on millions of real tasks, enabling robots to improve performance over time and adapt to different workflows.
The company also claims its VLA models can integrate automatically into an existing fleet of AI-powered robots, with the aim of reducing deployment time and improving autonomy. In warehouse robotics, faster deployment can be a commercial differentiator, as operators typically want automation that can be rolled out with minimal disruption and quickly demonstrate return on investment.
Context: European funding momentum in warehouse robotics
Nomagic’s Series B extension also lands amid continued investor interest in European robotics, Physical AI, and warehouse automation. In early 2025, Nomagic raised €41.5 million to scale AI-driven robot deployments across Europe.
Other funding rounds in the broader ecosystem during 2025 included:
- Neuracore, which raised €2.5 million to develop unified robot-learning infrastructure intended to standardize data and training pipelines for robotics teams.
- Filics, which raised €13.5 million to expand its omnidirectional pallet-handling robot platform and prepare for broader European rollout.
Collectively, these disclosed rounds indicate roughly €65–70 million of capital flowing into closely related European segments over the year, underscoring the competitive pace of development in automation and AI-enabled robotics.
Why Physical AI matters for warehouses
The company argues that Physical AI is an evolutionary step in AI adoption, combining advanced computing with machines—such as robots—to solve physical problems rather than purely digital ones. In warehouses, one of the most persistent challenges is reliable object manipulation: picking, sorting, and handling a wide variety of items with different shapes, packaging materials, and orientations.
As fulfillment networks become more complex, operators are looking for systems that can handle variability without extensive reprogramming. Solutions that improve adaptability and reduce setup time can help warehouses scale automation beyond narrowly defined tasks.
What comes next
With the new funding, Nomagic says it will build on commercial traction and technical progress achieved in 2025, with a particular focus on expanding in the U.S. market while continuing to invest in VLA model development. The company’s strategy reflects a broader industry shift toward more generalized robotics capabilities, where AI models are expected to make robots more flexible and economically viable across a wider range of warehouse operations.
For Nomagic, the Series B extension signals both investor confidence and heightened expectations: scaling deployments in the U.S. will test how well its approach to Physical AI translates across different customer requirements, facility layouts, and operational constraints.
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