LabelSpark is a connector from Labelbox that links Databricks to Labelbox’s annotation platform, letting teams programmatically push unstructured data (images, text, video) into Labelbox, configure labeling ontologies in Databricks, and pull back labeled results as Spark DataFrames for ML workflows; it accelerates data preparation by integrating model-assisted labeling and active-learning features to reduce manual effort and improve label quality, while supporting enterprise security and scalable pipelines so AI teams can more quickly produce auditable, training-ready datasets.