Sleight is building the physical AI platform for a new class of dexterous robots — systems that can manipulate, navigate, and reason across the full complexity of real environments, without scripting, without guardrails.
Most robotics research optimizes for controlled settings. We build for the opposite — the clutter, ambiguity, and variability of real homes and workplaces. That demands an AI foundation trained on how the world actually behaves. We have assembled one of the broadest real-world training data programs in the industry to make this possible.
Robots that parse a room — objects, relationships, and likely next events — before taking any action.
Trained on large-scale video of people engaged in everyday tasks across diverse environments and demographics.
Fine-grained interaction with objects — picking, placing, operating — generalized across form factors.
Movement through real, changing spaces — not mapped environments, not simulation. Ground-truth real.
Understanding and executing natural-language task requests across novel contexts without re-training.
Dexterous physical AI requires training data at a scale and diversity that does not yet exist off the shelf. We are building that foundation — sourcing, curating, and structuring the real-world activity data that the future of robotics requires.
DATA PARTNERSHIPS · alex@sleightlabs.com