Labellerr review
A capable image annotation platform for teams that need automation, APIs, and export choice.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Labellerr is a web-based data annotation platform for AI and machine learning teams working with image datasets. Its image tools cover bounding boxes, polygons, polylines, keypoints, dots, classification, object detection, segmentation, and pose estimation. The platform is suited to students and researchers through its Researcher plan, as well as teams managing larger machine learning workflows. It also supports video, audio, document, and text datasets, with project management, annotation workflows, analytics, APIs, and a Python SDK.
Pricing separates an entry-level Researcher plan from paid business tiers. Researcher includes 2,500 data credits, 1,000 files, 1 seat, 1 workspace, and 10 projects. Pro is listed at $9,999 per plan per year and adds 100,000 data credits, up to 200 seats, unlimited projects, advanced automation features, and human-in-the-loop services. Enterprise adds multiple workspaces, unlimited data credits and seats, single sign-on, enterprise SLA and support, plus private cloud and on-premise add-ons. The structure gives smaller research projects a defined starting point, while the annual Pro price makes larger deployments a significant commitment.
Its strongest fit is for teams that value model-assisted labeling and downstream dataset flexibility. Labellerr supports SAM, SAM 2, SAM 3, and custom models, along with active learning, prompt-based labeling, pre-annotation review, and workflow analytics. Dataset exports include COCO JSON, YOLO, Pascal VOC XML, CSV, and custom formats. AWS S3, Google Cloud Storage, Azure Blob Storage, webhooks, CI/CD, the API, and Python SDK support broader platform integration. Teams needing self-hosting, single sign-on, or private cloud options can consider Enterprise. Smaller projects needing only basic annotation may find the Pro commitment disproportionate, while teams seeking automation, collaboration, and many export paths have a stronger case for Labellerr.
Labellerr pros and cons
- Where it wins
- Supports boxes, polygons, polylines, keypoints, dots, and classification
- SAM-based automation, active learning, and custom model-assisted labeling
- Exports to COCO JSON, YOLO, Pascal VOC XML, CSV, and custom formats
- Where it doesn't
- The listed Pro plan costs $9,999 per year
- Researcher is limited to 2,500 data credits and 1,000 files
- Advanced automation and human-in-the-loop services are on Pro
Labellerr fact sheet, pricing and score →
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