Building the foundation for Physical AI.
Y-Kenistik builds the data systems, evaluation infrastructure, and operational tools that help intelligent machines understand—and act in—the physical world.
to reliable intelligence
Physical intelligence is built into the data before the model ever sees it.
Run the work others defer.
Robotics makes data work computationally heavy: video processing, full-corpus reprocessing, evaluation sweeps, and ML.
We have invested deeply in the infrastructure behind those jobs—making them faster, more reliable, and far more efficient to run.
Video is not a stack of frames. It is a record of change.
The deepest meaning lives inside the timeline: what began before motion became obvious, what changed together, which moment redirected the outcome, and how an attempt became success, failure, or recovery.
We study video from the inside out—connecting visual change with the signals unfolding alongside it. That temporal structure can turn passive footage into evidence of progress, interaction, and outcome: a richer foundation for understanding and learning.
From raw capture to structured understanding.
Physical AI data must move cleanly between systems, stand up to scrutiny, and preserve the context that makes real behavior useful. We build the infrastructure that connects raw logs, media, and state to training and evaluation workflows.
Meet the data where it is.
Leave with data that learns.
Built by people who have operated at scale.
A decade of Google engineering across security, abuse prevention, and the infrastructure behind high-volume media processing.
Commercial experience spanning McKinsey, Stanford, and the expansion of consumer businesses across Asia.
Published researchers and engineers who graduated at the top of their class build the core data and ML pipelines behind our platform.
Bring us one dataset.
We are taking on a small number of first pilots with Physical AI teams. Bring one representative dataset and the decision you are trying to make. We will return an evidence-backed read of what it actually contains—what survived collection, what may be missing or unreliable, and where deeper review is worth the effort.