Could you please elaborate on what you mean by "intelligently validate the quality of labels in a document and complement human judgment", and discuss your methodology?

This seems to operate under the assumption that human labels are not actually the ground truth. I understand that they can be dirty, but most unsupervised approaches aren't producing a ground truth, either. So, are you saying it's better to have multiple pretty good sources of truth instead? Because depending on the application, that might make sense or it might be like trying to start a farm with a dead horse and a dead cow.