Building physical AI systems that work in the real world
is fundamentally a data problem.

Most failures in physical AI are not caused by model design.
They arise from missing interactions, unobserved edge cases,
and limited exposure to real-world constraints.

Without high-quality, task-grounded data,
systems fail to generalize beyond controlled environments.

Rekna builds and executes real-world data pipelines
that make physical AI systems trainable, testable, and deployable.

That is the problem Rekna is built to solve.