In the rush to adopt AI across diverse sectors, today’s enterprises face a common hurdle: efficient data labeling at scale. Numerous enterprises are grappling with generating usable data despite having huge amounts of raw information. Organizations are overwhelmed by the influx of image data, highlighting the need to process and label it for practical use. Data labeling is a crucial step in the model training pipeline. Choosing an efficient data labeling tool can directly impact the performance of machine learning (ML) models.
