Former F1 Aerodynamicist Raises $55M to Solve Robot Training Crisis With Human Footage

An F1 aerodynamicist just raised $55m to teach factory robots, using footage of people doing chores

Bercan Kilic left Red Bull Racing at the height of its dominance. His startup's answer to the robot data problem is to film 20,000 people mopping floors. Bercan Kilic got his dream job in 2023, designing aerodynamics for Red Bull Racing while it was winning everything. He found the engineering magnificent and the point of it thin. His Munich startup, microagi, has now raised $55m, which it says is the largest seed round a German company has secured. Hummingbird led, with Northzone, LocalGlobe, Village Global, and redalpine participating. The valuation was not disclosed. What microagi sells is narrower than the funding suggests, and more interesting for it. It does not build robots, and it does not build models. It records workers using cameras and sensor-equipped gloves, then uses the footage to teach existing robotics models to do a specific job inside a specific customer's factory. That is unfashionable in a sector where the money has gone to hardware, from Walden Robotics' $300m launch to All3's legged construction robots. microagi sells the layer between somebody else's robot and somebody else's model. Five companies are collecting data through the platform, Kilic said, and one is preparing to deploy robots on a line. Customers span automotive, logistics, and food. He declined to name the model partners. "We provide the labs with data, they provide us with models, and then we layer on proprietary data to make our customers happy," he said. That arrangement exists because of a detour. microagi planned to do deployment only, until the team found that most robotics models were not good enough to start from. Kilic's analogy is training a new hire: an adult picks up a factory job in a week, a child may never get it, and existing robotics models are still children. So it built shift, which is the part you may have encountered without knowing whose it was. It went viral this year offering free apartment cleanings in New York in exchange for filming the cleaners doing dishes, mopping, and folding laundry. This week it started offering free private chefs in San Francisco. shift now operates in 15 countries and pays more than 20,000 people to record themselves performing physical tasks, selling the footage to the labs building robot brains. It competes with Scale AI, Turing, and micro1, all doing versions of the same thing. The reason the business exists is a genuine asymmetry. Language models were trained on the internet. Robots have no internet, a gap the Berkeley roboticist Ken Goldberg puts at 100,000 years, and no amount of capital collapses it directly. Hence the cameras. Kilic's answer on whether he is filming people out of their own jobs is demographic rather than moral. Europe and the US are running out of workers, and China is automating regardless. It installed 295,000 factory robots in 2024, 54% of the world's total, against 34,200 in the US. Adapting existing models rather than training one is also a bet on those models arriving, which is the theory Nvidia has spent the year seeding. If it works, microagi has a market. If not, it has a great deal of footage of people mopping. "If you run factories, the math is already on your desk," he said. "Your most experienced people retire this decade, and their replacements were never born. Reshoring only works if the robots do." The numbers support the frame. The EU's median age hit 44.9 in 2025, up from 39.6 two decades earlier, and the European Commission estimates the bloc could lose 18.8 million workers by 2050. Hummingbird's Firat Ileri, who led the round and previously backed Lovable, Kraken, and Etched, said he was struck by how rarely anyone at the Munich office seemed to leave it. The money goes on compute, expanding shift's network, and a US presence run from New York. microagi employs 37 people; shift about 75. Kilic's four co-founders include a former Mercedes F1 engineer, Yoan Iliev, and an ex-Alan Turing Institute researcher, Anton Poletaev. Kilic thinks robotics is at its "GPT-2 moment", with the scaling recipe not yet worked out but close. He also wants microagi to be the world's largest company inside five years. "In five years, if we haven't deployed more than 20 million or 30 million robots, it's a big failure," he said. The company currently has one customer close to putting robots on a factory floor.

Microagi nabs $55M to teach factory robots how to work

Munich-based startup Microagi GmbH today announced it raised $55 million in seed funding led by Hummingbird to change how industrial robotics works with artificial intelligence models. Northzone, LocalGlobe, Village Global and Redalpine also participated in the round. The capital raise arrives around ten months after the company was founded by Formula One engineers from Red Bull Racing and Mercedes-AMG Petronas, two high-octane racing teams. Microagi is helmed by Bercan Kilic, whose career path includes being a former aerodynamics engineer for Red Bull Racing in 2023. He left his position in the sport to found the AI company. The power behind Microagi is Atlas, a robotics data and deployment platform for industrial companies, which ingests large volumes of data for training - something that is at a premium for AI-driven robotics - and integrates it to fine-tune frontier robotics models for customers. The company does not build robots or robotics AI models; instead, it provides a powerful data layer that enables it to teach existing models to do a better job. "Our partners build genuinely good robots and models," said Chief Technology Officer Nico Nussbaum. "Our job starts after that, on the factory floor. We put our engineers on site with each customer, and the system learns from their real operations and feeds that back into the next run, so every month we're there, they pull a little further ahead of their competitors." By using the data captured from industry customers, using dedicated recording hardware, and a secure ingestion platform designed to curate training data, the company is able to multiply the data and fine-tune AI models for plant-specific tasks. After deploying to the end customer, the company continues to refine its models using factory-floor data in a reinforcement loop designed to improve accuracy. The company boasts that its design foundation helps close the gap between impressive robotics demos and actual "hands-on" capabilities in industrial environments. Although no specific customers have been named, the firm told Business Insider that five companies are currently collecting data through the Atlas program, with one customer preparing to deploy robots in a factory. Customers span industries including automotive, logistics and food. Robotic data is sparse, so Microagi brought its own Microagi went viral last month when Shift, the company's consumer-facing arm that collects data, said it would begin offering New York City residents free home cleaning. As part of the offer, housecleaning staff will arrive with cameras attached to their bodies. The company's app website said it would connect "New Yorkers with free, trusted professional house cleaners" so that Microagi could record "first-person-cleaning footage to help train the next generation of household robots." It adds that there is "no catch" and that the free cleanings will go on for a limited time. Why does this matter? Although large language models and image models, the best-known AI models on the market, have a giant volume of text and images produced directly by human hands to use for training - robot AI models lack a lot of data they can use for training. This is because although there's a lot of video displaying people on YouTube and other sources, there is a paucity of video of people actually doing things, such as folding clothing, sorting objects, cleaning and other activities. Not just any video will work either. Most robotics platforms must be trained on video that has been curated for best practices, good lighting, full view of arms and hands, and other conditions that make it easier to turn into movement telemetry. This means that many robotics AI model developers must gather their own video and movement data from other sources. In this case, Microagi is offering spotless apartments for the side benefit of useful domestic data. The company also announced that it's launching private chefs in San Francisco with the same objective: to provide data for robotic cooking. The video announcing the project is an exercise in secondhand awkwardness, but it gets the point across.