Monumo is a UK-based deep-tech company that uses AI and machine learning to redesign electric motors. It works across the electromagnetic, mechanical, and thermal domains simultaneously, aiming for motors that are lighter, more compact, more energy-efficient, and less reliant on rare-earth materials. Sectors targeted include electric vehicles, industrial and domestic appliances, robotics, and aviation.
“What we do is AI for engineers: the optimization of complex engineering systems,” says CEO Jarek Rzepecki.
Think of it as Physics AI, incorporating physical laws into models, as opposed to “Physical AI,” which acts in the physical world (robots, drones, autonomous vehicles).
The five-year-old UK company’s relevance to Physical AI is that it sits upstream. Every robot, drone, and humanoid moves through motors and actuators, and those are what Monumo designs. Its robotics briefing makes the economics clear: actuators account for 40–60% of a humanoid robot’s bill of materials, and the motor, reducer, driver, and encoder stack makes up 80–90% of that.
Its pitch to industrial and appliance manufacturers also centers on cost: a $10 swing in copper or magnet cost per unit, multiplied across millions of units, hits the P&L hard, and the company claims it can help cut bill-of-materials costs by up to 20%.
Another advantage cited by the company is that, by designing motors that use fewer or no rare-earth magnets, Monumo addresses manufacturers’ dependence on China-processed rare earths.
Monumo’s core product is the Anser AI Engine, a proprietary multi-physics optimization platform that runs millions of simulations a day to explore motor designs beyond human capability. The company’s key claim is that Anser generates its own training data from high-fidelity simulations, cutting design time from months to days. Rather than tuning one component at a time, it co-optimizes the whole system.
“We produce optimal designs extremely fast, which helps our customers get their products to market faster,” says Rzepecki, who in his prior role as CTO is credited with being the driving force behind the Anser AI Engine.
On September 17, Hyundai Cradle and Hyundai Motor Company R&D announced a completed proof of concept using Anser. In a LinkedIn post, the global automaker said that by leveraging advanced simulation and optimization capabilities through Monumo’s proprietary Anser AI platform, the team demonstrated how next-generation engineering tools can:
- Accelerate innovation cycles
- Enable deeper design optimization
- Deliver significant cost savings
- Produce high-quality motor designs in a fraction of the time compared to conventional methods
Hyundai also described how, through the proof-of-concept trial, its Motor Group identified alternative motor designs that can improve efficiency while reducing material costs, providing valuable insights into performance trade-offs across different configurations.
Monumo is already generating significant revenue from customers in the U.S., Europe, and Asia and expects commercial contracts and revenue to double in 2026, says Rzepecki. Prior to joining Monumo, he held various technical roles in companies including Microsoft Research, Siemens, and Arm. Rzepecki holds a PhD in astrophysics from Heidelberg University and an MSc in theoretical physics from Nicolaus Copernicus University.
Monumo’s primary business model is a subscription plus token-based consumption model. A yearly subscription gives customers access to its tech, and then customers pay as they use it with tokens. A single token gives one optimization. “However, some customers do ask us to just use our own tech to design a motor for them, in which case we create the motor design and then license/transfer the design IP to them,” Rzepecki says.
The company’s AI and software team is in Cambridge; the hardware domain experts are in Coventry. The company has raised a total of £10.5 million in a seed round from angel investors plus Innovate UK grants and is currently raising a Series A round of venture capital funding to help it scale.
Competitive Landscape
Monumo’s best-funded rivals are horizontal engineering AI platforms. London’s PhysicsX is the giant: it raised a $300 million Series C in June 2026 at a $2.4 billion valuation, led by Temasek, with Nvidia, Siemens, and Applied Materials among its backers. Lausanne’s Neural Concept raised a $100 million Series C led by Goldman Sachs Alternatives in December 2025 and says it works with 40% of the largest European and Asian OEMs. Both are general-purpose platforms. Monumo’s argument is that motors require deep, domain-specific, system-level co-optimization.
Competition is also coming from simulation incumbents, who are now adding AI. These are a threat because engineers already use their tools. SimScale now markets AI surrogates that sweep thousands of rotor and magnet configurations in seconds, with rare-earth-free topologies as a first-class use case. Ansys Motor-CAD (now owned by Synopsys) and Altair FluxMotor (now owned by Siemens) are the established motor-design standards.
“The benefit we have over them is we are smaller and more agile,” says Rzepecki. “We developed our technology from scratch, so there are no legacy systems to deal with. We can move faster and deliver solutions that are tailored to customers’ needs right now.”
The company’s closest direct competitor is Canada’s Enedym, which overlaps on rare-earth-free switched reluctance motors and also has design software: its FARM tool reportedly lets engineers design, optimize, and test a new motor in a couple of weeks. Honda invested in Enedym through its Honda Xcelerator Ventures program in late 2025. The difference is the business model: Enedym mainly builds motors, while Monumo sells the design platform.
Among smaller and adjacent players, India’s Vimag Labs pursues the same rare-earth goal by a different route, generating the rotor’s magnetic field electronically instead of with permanent magnets. In-house OEM motor-engineering teams are also a de facto competitor.
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