Labellerr vs segmenteverygrain

Labellerr is a data labeling and annotation platform for AI and machine-learning teams preparing training data. Projects can use images, videos, PDFs, text, and audio. Annotation options include bounding boxes, polygons, polylines, keypoints, dots, classification, segmentation, and object detection. Automated labeling includes prompt-based and model-assisted methods, plus active learning; the company also states native support for Meta’s SAM, SAM 2, and SAM 3. A Python SDK can manage datasets and workflows in ML pipelines. Annotated data can be exported in formats such as COCO JSON, YOLO, Pascal VOC XML, CSV, and custom formats. Remote storage options include AWS S3, Google Cloud Storage, and Azure Blob; integrations with Vertex AI, SageMaker, and Azure ML are add-ons for applicable plans. Stated security measures include Auth0 authentication, TLS 1.2 or higher in transit, and AES-256 encryption. The free Researcher plan includes 2,500 data credits, one seat, one workspace, and up to 10 projects. Pro costs $9,999 a year, and unused data credits do not roll into the next payment cycle.

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