The mind for everyday robots.
Most robotics capital is pointed at the factory floor. Cereal starts somewhere else: the home, the people, and the everyday moments where presence matters most. The same mind ports to every venue after that.
Two very different bets on embodied AI.
Billions into hardware and one form factor. Real markets, but the intelligence comes last and stays welded to one body.
One portable mind for everyday life: home, pets, routines, safety, physical assistance.
We're building the mind for everyday life.
The founders already invented the hard part.
Named inventors on 8 granted US patents in simulation-driven robotics from Google X, Everyday Robots, and Google DeepMind: the exact sim-to-real approach Cereal runs on. Every filing below links to the public record.
Simulation inside every control cycle.
The simulator is not a training ground left behind at deployment; it participates in every action the robot takes. The family was continued and granted under Google DeepMind in 2025: active, and still invested in.
Many robots, many permutations, one controller.
The virtual-environment infrastructure that made training and testing at Everyday Robots scale.
Imitation learning that refines control policies.
Training signal mined from real operation: the mechanism behind supervision that compounds into autonomy.
Keeping simulation honest about reality.
Re-simulating recorded episodes and injecting noise for robustness: the ancestor of Cereal's replayable, attested trail.
Inventor credentials reflect work at prior employers; the patents are assigned to those employers. Full record on the founder profiles: Matt Bennice · Paul Bechard.
Interoperability × robotics × simulation.
Unusually complete for a robotics company.
Google X · Wing · Everyday Robots · DeepMind · Stack AV · 1X · Cruise.
Profile →LinkedIn ↗Every robot is a sensor on the real world.
Cereal opens its stack so others can build on it, train it, and, with each owner's consent, contribute scoped real-world data back. The fleet improves the fleet.
Like rovers mapping Mars, a fleet of everyday robots gathers grounded real-world data no lab can simulate, then sends it home to make every robot smarter.