Eran Shlomo

Dataloop builds an AI data management and annotation platform that covers the full data pipeline for computer vision and NLP model development, combining data labelling tools, annotation workflow management, quality assurance automation, and model training integration in a single platform. The Tel Aviv company targets AI teams at enterprises and AI product companies that need to manage large-scale data labelling operations with quality controls and annotator workforce management.\n\nThe company raised approximately $49 million including a Series B round from investors including Viola Ventures and Samsung Next. Dataloop counts enterprise AI teams in automotive, retail, and agriculture verticals among its clients, with the platform used for large-scale computer vision dataset creation including bounding box annotation, semantic segmentation, and polygon annotation for object detection model training. The platform supports human-in-the-loop annotation workflows where model predictions are reviewed and corrected by human annotators to improve efficiency.\n\nDataloop competes in the data annotation and management market alongside Scale AI, Labelbox, Encord, and V7, as well as annotation services providers. The market has evolved from pure annotation tooling toward platforms that combine labelling with dataset management, model evaluation, and active learning capabilities. Dataloop positioning as a full data management platform rather than a labelling tool aims to capture more of the AI development workflow and reduce customer dependency on multiple point solutions across the data pipeline.