segellapp

Segellapp is a cloud-based data annotation platform designed for segmentation tasks across images, video, and text. Developed by Segell Labs, it was released in 2019 and has since been adopted by research groups and organizations building machine-learning models. The service focuses on flexible annotation tools, project management features, and integration with common data ecosystems to support end-to-end labeling workflows.

Its annotation toolkit includes polygon, brush, freehand, bounding boxes, and semantic and instance segmentation masks. Users can create multi-class labels, assign attributes, and track edits through version control. It supports task assignment, reviews, and quality checks within project workflows. It covers frame-accurate labeling for video and supports exports in COCO, PASCAL VOC, and YOLO formats, in JSON, XML, or CSV. An API and webhooks enable integrations with ML pipelines and cloud storage such as AWS S3 and Google Cloud Storage.

Segellapp runs in the cloud and is accessed through a web interface, with optional mobile companion apps. It provides role-based access control, data encryption in transit and at rest, audit trails, and activity logging to support collaboration and compliance.

Since its launch, the platform has been used by academic laboratories, startups, and enterprise teams for computer vision, image analysis, and natural language processing tasks. Reviewers have highlighted its collaborative features and the breadth of annotation tools, while noting that mastering advanced workflows can require a moderate learning curve.

See also: Data labeling, Image annotation, Video annotation, Semantic segmentation, Instance segmentation, COCO format, PASCAL VOC.