Data Labeling platforms enable teams to annotate images, text, audio, video, and sensor data to produce training datasets for supervised machine learning. Core capabilities include multi-modal annotation tooling (bounding boxes, polygon segmentation, classification, named-entity recognition, keypoint annotation), labeler workforce management (in-house, crowd, or managed services), quality-assurance workflows (consensus voting, gold-standard tasks, inter-annotator agreement), active learning loops that prioritize ambiguous samples for human review, and increasingly programmatic and weak-supervision approaches that reduce manual labeling volume. Leading vendors include Scale AI, Labelbox, Snorkel AI, V7, SuperAnnotate, Dataloop, and Appen.