Labellerr is a computer vision workflow automation platform. It helps ML teams to manage their AI development lifecycle much more efficiently. It helps teams to collaboratively work on data labeling tasks and have modules to manage multiple projects, users, and millions of unstructured data. Teams can perform- 1. Automated data curation 2. EDA (Exploratory Data Analysis) 3. Automated data labeling 4. Quality control with assurance 5. Automated QC 6. Model debugging Data types that it supports are images, videos, text, audio, and PDFs. Use cases it supports are object detection, segmentation, classification, image captioning, transcription, and translation. The active learning feature has helped users save 1000s USD per task. Labellerr recently launched LabelGPT which labels images using a prompt. It leverages the combination of generative AI models to label data in minutes rather than months.