Your robot looks fine in training...until it fails in the real world.

Training metrics like loss and accuracy only measure how well the model copies your examples — they don't reveal blind spots in your data, like an untested motion range or a camera angle you never recorded. Those gaps only surface once the robot meets a situation it never saw during training.

Start by checking your training data for hidden gaps — incomplete motion ranges, single-angle camera views, or unbalanced examples — before assuming the model architecture is at fault. Bohrin scans your dataset in seconds and lists the specific issues, with the data behind each one.

Bohrin catches silent failures in robot training before they ship. It analyzes your training data and every version you've shipped, tells you exactly why your robot is failing, and warns you before you ship a version that's worse than the last one.

Yes. Bohrin's free check-up scans your training data and returns a specific list of issues in seconds, with no credit card or setup required.

Loss and accuracy curves only show that the model is copying your examples well — they can't tell you the examples themselves are incomplete. Bohrin analyzes the underlying data and version history, not just the training metrics.