AnnotateIt AI

nnotateIt AI is a local-first image and video annotation tool for creating high-quality computer vision datasets on your iPhone and iPad. Label data for object detection, segmentation, classification, keypoint detection, and other machine learning workflows. Combine precise manual annotation tools with on-device AI assistance to work faster while keeping control of every result. Your projects, images, videos, and annotations are stored on the device. AnnotateIt AI does not require you to upload datasets to a third-party annotation service, making it suitable for private, sensitive, and proprietary data. KEY FEATURES • Annotate images and video frames • Create bounding boxes, polygons, masks, keypoints, and classifications • On-device AI-assisted segmentation, ready to use offline • Organize labels and classes for different project types • Import and export complete project archives • Dataset versioning with undo and redo history • Export annotations for common computer vision workflows • No account required BUILT FOR COMPUTER VISION AnnotateIt AI supports workflows for: • Object detection • Instance segmentation • Single-label and multi-label classification • Keypoint detection • Video frame annotation • Anomaly detection FLEXIBLE EXPORTS Export labeled datasets to widely used formats, including YOLO, COCO, Pascal VOC, and Datumaro, for use in model training and evaluation pipelines. PRIVATE BY DESIGN Your dataset media and annotations stay on your device during the core annotation workflow. Network access may be used only to download an optional sample project or to open links you request; your projects are not uploaded to an external annotation service. AnnotateIt AI is built for machine learning engineers, computer vision researchers, students, consultants, and small teams that need practical annotation tools without a cloud-first workflow. Note: on iPhone and iPad, imports are limited to images up to 32 MB, videos up to 128 MB and 10 minutes, and archives up to 128 MB. AI-generated suggestions should always be reviewed before inclusion in production datasets.