Robots that work where automation never could.

Singapore's cleaning workforce is aging faster than new workers enter it. Southeast Asia and Europe face the same shift. The cause is demographic: fewer people will do this work, and demand for well-maintained commercial space keeps growing.

Operators want to automate. The tools they can buy have not worked in the environments they manage. Griffin gives these operators machines that share the load.

Mobility platforms and sensor arrays can now execute the physical tasks facilities require. The hardware moves, reaches, and senses.

These machines still cannot perceive a new situation and act without explicit programming. Rooms vary. Shifts change. Intelligence is the bottleneck.

Foundation models give physical systems two capabilities they lacked: reasoning from language and generalizing from limited examples.

The remaining challenge is grounding: training models that connect perception to action and adapt based on live sensor data.

Griffin Labs exists for this work. We train embodied AI on data from live facilities and build the robotic systems that run those models. Each deployment feeds training data back into the next.