Manual Labeling sets important foundational framework for pre-trained CV models which enables AI Copilot Labeling and active learning. The #DeCorp system runs on a self-evolving cycle where manual labeling forms a 60%-75% "accurate" pre-trained model that, when used for Copilot Labeling, greatly enhances labeling efficiency. Over time, outputs from AI Copilot Labelings are either sold to clients, or fed back into the RLHF loop to reinforce accuracy of CV models until they reach industry-grade. In this case, the copilot model becomes industry-ready and can also be provided along with the data to our clients.