Nomagic
AI-powered robotic picking systems for warehouses, focused on pick-and-place tasks in logistics operations.
Website: https://nomagic.ai/
Cover Block
PUBLIC
| Name | Nomagic |
| Tagline | AI-powered robotic picking systems for warehouses, focused on pick-and-place tasks in logistics operations. |
| Headquarters | Warsaw, Poland |
| Founded | 2017 |
| Stage | Series B |
| Business Model | Hardware + Software (Robotics-as-a-Service) |
| Industry | Logistics / Supply Chain |
| Technology | AI / Machine Learning, Robotics |
| Geography | Western Europe (Poland HQ) |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (2) |
| Funding Label | $50M+ (total disclosed ~$84.9M) |
Links
PUBLIC
- Website: https://nomagic.ai/
- LinkedIn: https://www.linkedin.com/company/nomagic
Executive Summary
PUBLIC Nomagic builds AI-powered robotic picking systems for logistics warehouses, a startup that has secured over $84 million in capital by focusing on the hardest part of the operation. The company, founded in Warsaw in 2017, targets the costly and labor-intensive process of picking, scanning, and placing individual items within fulfillment centers [TechCrunch, Feb 2025]. Its differentiation lies in a software-heavy, Robotics-as-a-Service (RaaS) model, layering advanced vision and machine learning algorithms onto standard industrial arms to handle millions of different SKUs, which allows for deployment into existing warehouse infrastructure without a complete rebuild [Nomagic LinkedIn], [StartupIntros].
Leadership combines commercial and deep technical expertise. Co-founder and CEO Kacper Nowicki is a former Google director, while co-founder and Chief AI Officer Marek Cygan is a professor at the University of Warsaw, a pairing that underpins the company's research-driven approach to physical AI [Crunchbase, Kacper Nowicki], [Marek Cygan LinkedIn]. A significant recent hire, Markus Wulfmeier from Google DeepMind as Chief Scientist, signals a push into next-generation visual language action models for robotics [Aithority, Apr 2026].
The funding history shows consistent institutional support, progressing from a $9 million Seed in 2020 led by Hoxton Ventures to a $44 million Series B in 2025 led by the European Bank for Reconstruction and Development (EBRD), with Khosla Ventures as a recurring investor [StartupIntros, Feb 2020], [TechCrunch, Feb 2025]. The RaaS business model aligns customer costs with operational throughput, a structure aimed at reducing adoption barriers for large e-commerce and retail players like Zalando, which has selected Nomagic to install up to 50 robots across its European fulfillment centers [Nomagic, Oct 2025].
Over the next 12-18 months, the key monitorables are the execution of its stated North American expansion, the scaling of the Zalando deployment into a repeatable commercial blueprint, and the translation of its advanced AI research under Wulfmeier into measurable improvements in system autonomy and SKU coverage. Data Accuracy: GREEN -- Core claims on product, funding, team, and customer traction are confirmed by multiple independent sources including TechCrunch, Crunchbase, and company announcements.
Taxonomy Snapshot
| Axis | Classification |
|---|---|
| Stage | Series B |
| Business Model | Hardware + Software |
| Industry / Vertical | Logistics / Supply Chain |
| Technology Type | AI / Machine Learning |
| Geography | Western Europe |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (2) |
| Funding | $50M+ (total disclosed ~$84,900,000) |
Company Overview
PUBLIC
Nomagic was founded in 2017 in Warsaw, Poland, with the specific aim of applying advanced AI to the physical world of warehouse logistics. The founding team, led by CEO Kacper Nowicki, a former Google director and CTO of GoEuro, sought to address what is widely considered the hardest part of warehouse automation: the robotic picking of diverse items [Crunchbase, Kacper Nowicki]. Co-founder Marek Cygan, who serves as Chief AI Officer and is a professor at the University of Warsaw, brought deep academic and technical expertise in machine learning to the venture [Marek Cygan LinkedIn]. The third co-founder, Tristan d'Orgeval, as Chief Strategy Officer, contributed experience from roles at The Climate Corporation and Premise Data [Crunchbase, Tristan d'Orgeval].
The company's evolution has been marked by consistent capital support, beginning with a $9 million Seed round in early 2020 led by Hoxton Ventures and Khosla Ventures [StartupIntros, Feb 2020]. This was followed by a $22 million Series A in 2022 and a significant $44 million Series B in early 2025, which was led by the European Bank for Reconstruction and Development (EBRD) and signaled a strategic push for expansion [TechCrunch, Feb 2025]. Two subsequent extensions in early 2026 brought the total disclosed capital raised to approximately $84.9 million [StartupIntros, Jan 2026].
A key operational milestone was the 2025 selection by European fashion retailer Zalando to deploy up to 50 of Nomagic's AI-powered robots across its fulfillment centers, a partnership that serves as a public validation of the technology's readiness for scale [Nomagic, Oct 2025]. The company further strengthened its technical leadership in 2026 with the appointment of Markus Wulfmeier, formerly of Google DeepMind, as Chief Scientist to lead development of foundational Visual Language Action (VLA) models for robotics [Aithority, Apr 2026].
Data Accuracy: GREEN -- Founders, funding rounds, and key milestones confirmed by multiple independent sources including Crunchbase, TechCrunch, and company announcements.
Product and Technology
MIXED Nomagic’s product is not a single robot but a software-defined automation service for the most labor-intensive part of a warehouse. The company focuses exclusively on robotic picking, a task that involves identifying, grasping, and placing individual items from bins or conveyor belts, which is widely considered the most difficult challenge in warehouse automation due to the infinite variability of SKUs [TechCrunch, Feb 2025]. The core offering is a Robotics-as-a-Service (RaaS) model, which bundles AI software, standard industrial robotic arms, and 24/7 remote monitoring into a single operational subscription, aiming to reduce the upfront capital expenditure and technical complexity for logistics and e-commerce customers [StartupIntros].
The system’s intelligence is built on a proprietary vision language model (VLM) that enables robots to handle a wide variety of products without pre-programming for each one [Bruno Lusic LinkedIn, retrieved 2026]. This software-heavy approach allows the company to deploy its systems into existing warehouse infrastructures, using a tool-changer system that lets a single robot select between multiple specialist grippers in real-time to achieve what the company claims is over 95% SKU coverage for packing tasks [Nomagic, Packing]. A key deployment example is with European fashion retailer Zalando, where robots named "Richard" perform single-item picking, scanning, and induction into automated sorters [Fotoshoe Magazine, Oct 2025].
Recent leadership hires signal a deepening investment in core AI research. In April 2026, Nomagic appointed Markus Wulfmeier, formerly of Google DeepMind, as its Chief Scientist to lead the development of foundational Visual Language Action (VLA) models for robotics [Aithority, Apr 2026]. This move suggests the company’s technology roadmap is oriented toward more generalizable and adaptable AI systems that can learn continuously from operational data, a capability highlighted in its work with Zalando [Nomagic, Oct 2025].
Data Accuracy: GREEN -- Product claims and technology descriptions are confirmed by company sources and multiple press reports. The RaaS model and VLM focus are consistent across materials.
Market Research
PUBLIC The warehouse automation market is expanding beyond fixed conveyor belts and automated guided vehicles, moving toward flexible, AI-driven systems that can adapt to unpredictable SKU mixes and labor constraints. This shift is driven by the persistent difficulty of automating the core picking function, a bottleneck that has historically resisted cost-effective robotic solutions.
Total addressable market figures for robotic picking are not publicly disclosed by third-party analysts in the cited sources. However, the broader warehouse automation market provides a relevant analog. According to a 2025 report from Interact Analysis cited by TechCrunch, the global warehouse automation market was valued at $45.6 billion in 2024 and is projected to grow to $90.6 billion by 2028 [TechCrunch, Feb 2025]. Within this, the segment for goods-to-person and piece-picking robots, which includes Nomagic's focus area, is noted as a high-growth sub-sector.
Demand is anchored by three primary tailwinds. First, labor scarcity and rising wage costs in logistics hubs across Europe and North America pressure operators to automate core tasks. Second, e-commerce growth continues to drive demand for fulfillment speed and accuracy, with retailers needing to handle a vast and changing array of items. Third, the evolution of enabling technologies, particularly advanced computer vision and machine learning, has reached a point where robotic systems can achieve the necessary reliability and return on investment for complex picking tasks. The cited research frames robotic picking as the "hardest part" of warehouse automation, suggesting the solved portion of the market remains small relative to the total operational challenge [TechCrunch, Feb 2025].
Adjacent and substitute markets include traditional fixed automation (conveyor sortation), manual labor augmented by wearable technology, and competing robotic solutions from general-purpose robotics firms. A key regulatory and macro force is the push for "nearshoring" or "friendshoring" of supply chains, which could drive new warehouse construction in Europe and North America, creating greenfield opportunities for automated systems from the outset. Conversely, economic downturns that slow capital expenditure in logistics could delay adoption cycles.
Warehouse Automation Market 2024 | 45.6 | $B
Projected Market 2028 | 90.6 | $B
The projected doubling of the warehouse automation market over four years indicates strong underlying sector growth, though Nomagic's specific niche within robotic piece-picking likely represents a smaller, faster-growing slice of this total. The company's positioning targets the portion of this spend that is shifting from fixed infrastructure to flexible, software-defined automation.
Data Accuracy: YELLOW -- Market sizing is drawn from a single cited third-party report; the specific robotic picking segment size is not independently verified.
Competitive Landscape
MIXED Nomagic enters a competitive field defined by hardware incumbents, software-first challengers, and a growing list of startups all targeting the high-value automation of warehouse picking.
| Company | Positioning | Stage / Funding | Notable Differentiator | Source |
|---|---|---|---|---|
| Nomagic | Software-centric RaaS for pick-and-place; uses standard arms with proprietary AI vision. | Series B; $84.9M total raised (estimated). | Focus on pure picking as a service; leverages remote ops and a tool-changer system for high SKU coverage. | [TechCrunch, Feb 2025], [StartupIntros] |
| Covariant | Generalist AI robotics platform (Robotics Foundation Model) applied to warehouse picking and sorting. | Series C; $222M total raised. | Unified AI model (RFM) trained on massive real-world dataset; aims for generalizable intelligence across tasks. | [Crunchbase] |
| RightHand Robotics | Piece-picking robotics with integrated perception, motion planning, and gripper hardware. | Series C; $99M total raised. | Proprietary gripper and suction-cup hardware designed in-house for fragile and variable items. | [Crunchbase] |
| Berkshire Grey | End-to-end robotic automation systems for retail, e-commerce, and logistics fulfillment. | Public via SPAC (2021). | Full-system solutions (sortation, packing, palletizing) targeting large-scale, greenfield deployments. | [Crunchbase] |
| Smart Robotics | Collaborative robot (cobot) solutions for flexible pick-and-place and palletizing. | Venture-backed; funding undisclosed. | Emphasis on ease of deployment and programming for mid-market customers in Europe. | [Company Website] |
| Plus One Robotics | Vision software for parcel handling and depalletizing, paired with various robot arms. | Series B; $50M total raised (estimated). | Focus on parcel logistics; software-centric approach with human-in-the-loop oversight for exceptions. | [Crunchbase] |
The competitive map splits into three primary segments. First, integrated system providers like Berkshire Grey offer comprehensive, high-capex solutions often suited for new facility builds. Second, software-platform players, notably Covariant, are betting that a foundational AI model can outperform task-specific systems in the long run. Third, there are specialists focused on the picking operation itself, where Nomagic, RightHand Robotics, and Plus One Robotics compete. Adjacent substitutes include traditional automation integrators and manual labor, which remain the dominant solution for most warehouses due to flexibility and lower perceived risk.
Nomagic's current edge appears to be its specific combination of a capital-light RaaS model and a deep focus on the picking task. The company's decision to use standard industrial robot arms, rather than developing custom hardware, lowers unit costs and simplifies integration into existing brownfield sites, a common warehouse scenario. Its proprietary vision language model (VLM) and tool-changer system, which allows a single arm to select different grippers, aim to deliver the high SKU coverage (claimed 95%+) that customers require without bespoke engineering per item. This software-heavy, service-aligned approach is a defensible position against hardware-focused rivals, as it builds a data flywheel from deployed systems and creates recurring revenue stickiness. However, this edge is perishable if a platform player like Covariant achieves sufficient generalization with its Robotics Foundation Model, potentially making task-specific software obsolete, or if a hardware innovator like RightHand Robotics achieves a significant cost or performance breakthrough with its integrated gripper systems.
The company's most significant exposure lies in the capital intensity and go-to-market challenges of scaling physical deployments. While the RaaS model reduces customer capex, it requires Nomagic to fund the robots and installations itself, tying growth closely to fundraising capacity. Competitors with deeper pockets or public currency, such as Berkshire Grey, could engage in price competition or pursue larger, multi-year deals that strain a startup's balance sheet. Furthermore, Nomagic's European focus, while a strength in its home market, leaves it with less proven traction and channel presence in North America compared to U.S.-based rivals. Its technology is also not a full-stack warehouse solution; it remains vulnerable to competitors that can bundle picking with adjacent automation like sortation or palletizing, offering a more comprehensive value proposition to logistics operators.
The most plausible 18-month scenario is one of continued segmentation, where no single player captures the entire market. The winner in this period will likely be the company that most effectively proves unit economics at scale while expanding its footprint. If Nomagic can successfully deploy its planned North American expansion and demonstrate consistent, high-uptime operations for anchor clients like Zalando, it will solidify its position as a leading specialist. Conversely, the loser would be any player that fails to transition from successful pilots to widespread, economically sustainable deployments. A competitor that relies on custom hardware and cannot reduce its cost per pick sufficiently could find itself locked out of the price-sensitive mid-market, becoming a niche provider for high-margin, low-volume applications.
Data Accuracy: YELLOW -- Competitor funding and positioning drawn from Crunchbase and company sources; differentiation analysis is inferred from public positioning.
Opportunity
PUBLIC
If Nomagic can successfully execute its plan to become the de facto standard for robotic picking in modern warehouses, the prize is a controlling stake in the automation of one of the most labor-intensive and costly bottlenecks in global logistics.
The headline opportunity is to become the category-defining software layer for robotic manipulation in unstructured environments, specifically within high-volume fulfillment. The evidence that this is reachable, not merely aspirational, lies in the company's strategic focus and early traction. Nomagic has deliberately targeted the "hardest part of warehouse automation",the picking of diverse, unpredictable items,with a software-heavy approach that runs on standard industrial arms [TechCrunch, Feb 2025]. This positions them as an intelligence layer that can be integrated into existing infrastructure, avoiding the need for customers to rebuild entire facilities. The selection by Zalando, a major European e-commerce player, to install up to 50 AI-powered robots across its fulfillment centers validates the technology's ability to meet industry-leading operational standards in a real-world setting [Nomagic, Oct 2025]. The company's Robotics-as-a-Service (RaaS) model further aligns its success with customer outcomes, creating a path to becoming the default operational partner for automated picking.
Several concrete paths could lead to massive scale. The table below outlines two primary growth scenarios, each tied to a specific, cited catalyst.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| North American Expansion | Nomagic replicates its European success in the larger, more fragmented U.S. logistics and e-commerce market, securing anchor customers among major retailers or third-party logistics providers. | The $44 million Series B round in 2025 was explicitly earmarked for expansion "specifically in North America" [TechCrunch, Feb 2025]. | The company has proven its model with European leaders like Zalando and has the capital to establish a commercial beachhead. |
| Platformization via VLA Models | The proprietary vision-language-action (VLA) models under development become a foundational technology licensed to other robotics OEMs or system integrators, turning Nomagic into an AI provider beyond its own hardware deployments. | The April 2026 appointment of Markus Wulfmeier, formerly of Google DeepMind, as Chief Scientist to lead foundational model development signals a serious investment in this frontier [Aithority, Apr 2026]. | The team's deep AI expertise, led by Chief AI Officer and professor Marek Cygan, provides the technical credibility to pursue this high-margin software opportunity [Marek Cygan LinkedIn]. |
Compounding success for Nomagic would likely manifest as a data and operational flywheel. Each new deployment in a customer warehouse generates unique visual and kinematic data on handling millions of SKUs. This proprietary dataset continuously improves the core perception and manipulation algorithms, increasing the system's accuracy, speed, and the range of items it can handle reliably. As performance improves, unit economics get better,higher throughput per robot and fewer required human interventions,which makes the RaaS offering more compelling to the next customer. There is early evidence this flywheel is turning: the company claims its systems achieve "95%+ SKU packing coverage" through continuous learning and adaptation [Nomagic, Packing]. A growing, diversified customer base across different verticals (e-commerce, retail, logistics) further enriches the training data, creating a widening data moat that becomes difficult for new entrants to replicate.
Quantifying the size of a win is challenging for a private company in a nascent category, but public comparables provide a frame of reference. Covariant, a competitor also focused on AI for robotic picking, was reportedly valued at over $1 billion in its 2024 funding round. While direct financials are not public, this benchmark suggests the category can support unicorn-scale outcomes for technology leaders. If Nomagic's North American expansion scenario plays out and it captures a meaningful share of the robotic picking segment within the multi-billion dollar warehouse automation market, a valuation in the high hundreds of millions to low billions is a plausible outcome (scenario, not a forecast). The company's asset-light RaaS model and software-centric differentiation could command premium multiples relative to pure hardware robotics firms, as evidenced by investor interest from firms like Khosla Ventures and Accel that typically back software-defined businesses.
Data Accuracy: GREEN -- Scenario catalysts and market context are confirmed by named publisher reports (TechCrunch, Aithority). The existence of a public comparable (Covariant) is widely reported in industry press.
Sources
PUBLIC
[TechCrunch, Feb 2025] Nomagic picks up $44M for its AI-powered robotic arms | https://techcrunch.com/2025/02/26/nomagic-picks-up-44m-for-its-ai-powered-robotic-arms/
[Nomagic LinkedIn] Nomagic LinkedIn About | https://www.linkedin.com/company/nomagic
[StartupIntros] Nomagic company profile | https://startupintros.com/orgs/nomagic
[Crunchbase, Kacper Nowicki] Kacper Nowicki | https://www.crunchbase.com/person/kacper-nowicki
[Marek Cygan LinkedIn, retrieved 2026] Marek Cygan LinkedIn | https://www.linkedin.com/in/marekcygan
[Crunchbase, Tristan d'Orgeval, retrieved 2026] Tristan d'Orgeval | https://www.crunchbase.com/person/tristan-dorgeval
[StartupIntros, Feb 2020] Nomagic Seed Round | https://startupintros.com/orgs/nomagic
[StartupIntros, Jan 2026] Nomagic Series B Plus Round | https://startupintros.com/orgs/nomagic
[Nomagic, Oct 2025] Nomagic selected by Zalando | https://nomagic.ai/news/nomagic-selected-by-zalando
[Aithority, Apr 2026] Markus Wulfmeier joins Nomagic as Chief Scientist | https://aithority.com/robots/nomagic-appoints-markus-wulfmeier-as-chief-scientist
[Bruno Lusic LinkedIn, retrieved 2026] Bruno Lusic LinkedIn Post | https://www.linkedin.com/in/brunolusic
[Nomagic, Packing] Nomagic Packing Solution | https://nomagic.ai/solution/packing/
[Fotoshoe Magazine, Oct 2025] Zalando deploys Nomagic robots | https://fotoshoe.com/zalando-deploys-nomagic-robots
[Crunchbase] Covariant Crunchbase Profile | https://www.crunchbase.com/organization/covariant
[Crunchbase] RightHand Robotics Crunchbase Profile | https://www.crunchbase.com/organization/righthand-robotics
[Crunchbase] Berkshire Grey Crunchbase Profile | https://www.crunchbase.com/organization/berkshire-grey
[Company Website] Smart Robotics | https://www.smart-robotics.nl/
[Crunchbase] Plus One Robotics Crunchbase Profile | https://www.crunchbase.com/organization/plus-one-robotics
Articles about Nomagic
- Nomagic's Robotic Arms Land a 50-Robot Deal With Zalando — The Polish startup, backed by $84.9M, is expanding its AI-powered picking service across European fulfillment centers.