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

Former Formula One Engineer Tackles the Data Problem in Robotics

Bercan Kilic, an aerodynamicist who left Red Bull Racing during its dominant 2023 season, has secured $55 million in seed funding for microagi, marking Germany's largest seed round to date 1

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. Hummingbird led the round, with Northzone, LocalGlobe, Village Global, and redalpine participating 2

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. The Munich-based startup was founded approximately ten months ago by engineers from Formula One teams Red Bull Racing and Mercedes-AMG Petronas 2

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What makes microagi distinct is its narrow focus. The company doesn't build robots or develop AI models. Instead, it records workers using cameras and sensor-equipped gloves, then uses this footage to teach factory robots specific jobs inside customer facilities 1

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. This positions microagi as the layer between existing hardware and existing models, an approach that stands apart in a sector where capital has flowed toward hardware companies like Walden Robotics' $300 million launch 1

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How MicroAGI's Atlas Platform Addresses Industrial Applications

The company's core technology, Atlas, functions as an AI-driven robotics platform that ingests large volumes of real-world data and fine-tunes industrial robotics models for specific customers 2

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. Chief Technology Officer Nico Nussbaum explained the approach: "Our partners build genuinely good robots and models. 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" 2

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Five companies are currently collecting data through the platform, with one preparing to deploy robots on a production line 1

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. These customers span automotive, logistics, and food industries 2

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. The company employs a reinforcement learning approach, continuously refining models using factory-floor data in a loop designed to improve accuracy over time 2

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Shift Platform Collects Robotics Training Data Through Unconventional Methods

Microagi's consumer-facing initiative, Shift, went viral by offering free apartment cleanings in New York in exchange for filming cleaners performing tasks like mopping, dishwashing, and folding laundry 1

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. This week, the company launched free private chefs in San Francisco with similar objectives 1

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. Shift now operates in 15 countries and pays more than 20,000 people to record themselves performing physical tasks, selling the footage to labs building robot brains 1

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. The platform competes with Scale AI, Turing, and micro1 1

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The business exists because of a fundamental asymmetry. While language models trained on internet text, robots lack equivalent data sources. Berkeley roboticist Ken Goldberg estimates this gap at 100,000 years, and no amount of capital collapses it directly 1

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. Robotics platforms require curated video with specific conditions: best practices, proper lighting, full view of arms and hands, and other factors that convert into movement telemetry 2

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Demographic Crisis Drives Automation Urgency

Bercan Kilic frames the opportunity around demographics rather than displacement. Europe and the US face worker shortages, while China installed 295,000 factory robots in 2024, representing 54% of the world's total, against 34,200 in the US 1

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. "If you run factories, the math is already on your desk," Kilic said. "Your most experienced people retire this decade, and their replacements were never born. Reshoring only works if the robots do" 1

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The EU's median age reached 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 1

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. This demographic reality makes automation less optional for manufacturers attempting to maintain production capacity.

Betting on the GPT-2 Moment for Robotics

Microagi's strategy of adapting existing models rather than training new ones represents a calculated bet on foundation models arriving soon. Kilic describes robotics as at its "GPT-2 moment", with the scaling recipe not yet worked out but close 1

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. If foundation models materialize as predicted, microagi controls a critical data layer. If not, the company holds extensive footage of human task performance.

Kilic's ambition extends beyond incremental growth. He wants microagi to become the world's largest company within 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 1

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. The company currently employs 37 people for microagi and about 75 for Shift 1

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. The seed funding will support compute resources, expanding Shift's network, and establishing a US presence operating from New York 1

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