For VLA and robot-policy teams, where does raw data become training-ready?(reddit.com)

Hi all, I’m building a data-readiness platform that runs a raw-to-training-ready workflow for Physical AI teams. It starts with the messy middle after capture: robot video, sensor streams, logs, and kinematics that are not yet reliable training data. Euler combines visual and kinematic readiness checks with annotation and labeling, with the goal of taking a raw data slice toward a dataset for a specific policy. I’m conducting user interviews to gauge whether I'm heading in the right direction, because I do not want to build just another annotation platform. For teams training VLA or other robot policies, I’d really value a candid view on three questions: Is the harder problem knowing which data is usable, or annotating it once you know? Would a policy-aware workflow from raw capture to training-ready data be useful? What would make this meaningfully better than annotation software: readiness checks, visual plus kinematic context, curation, or something else? Project: https://sudotank.com/ I’m looking for honest pushback as much as interest. Thanks! submitted by /u/sennath [link] [Kommentare]