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Labellerr

What Labellerr is
Labellerr is a data labeling and annotation platform for teams preparing training data for AI and machine-learning projects. It supports image, video, PDF, text, and audio projects, with image formats including JPG, JPEG, PNG, BMP, and TIFF. Annotation tools cover bounding boxes, polygons, polylines, keypoints, dots, classification, segmentation, and object detection. Labeling options include prompts, model assistance, and active learning; the company also says it natively supports Meta’s SAM, SAM 2, and SAM 3. Teams can use a Python SDK to manage datasets and workflows in ML pipelines, then export annotations in formats including COCO JSON, YOLO, Pascal VOC XML, CSV, and custom formats. 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 includes 100,000 data credits and up to 200 seats. Unused data credits do not carry forward to the next payment cycle.
Who it suits
Labellerr suits machine-learning teams preparing datasets for computer-vision work, including teams in automotive, medical imaging, and manufacturing. The free Researcher Plan is aimed at students and researchers.
What it does well
- Supports image, video, PDF, text, and audio projects
- Includes model-assisted labeling and active learning
- Python SDK for dataset and workflow management
- Free Researcher Plan includes 2,500 data credits
What to know first
- Unused data credits do not carry forward
- Pro costs $9,999 a year
- Researcher Plan is limited to one seat
Limits
The free Researcher Plan includes 2,500 data credits, one seat, one workspace, and up to 10 projects. Its unused data credits do not carry into the next payment cycle. Pro costs $9,999 per year and includes 100,000 data credits and up to 200 seats.
Plans
| Plan | Billed and limits | Price |
|---|---|---|
| Researcher Plan | Free · 2,500 data credits · 1 seat · 1 workspace · up to 10 projects · students and researchers | Free |
| Pro Plan | $9,999 annually · 100,000 data credits · up to 200 seats · unlimited projects · extra credits and seats available | $9,999 a year |
| Enterprise Plan | Custom · Unlimited data credits and seats · multiple workspaces · SSO · enterprise SLA and support · private cloud and on-premise add-on | On request |
As labellerr.com lists them, read 4 Oct 2026. The maker's own page has the final word.
Getting started
- Visit https://www.labellerr.com/.
- Choose the free Researcher Plan or review Pro and Enterprise options.
- Use the web platform, API, or self-hosted option.
- Create a project with supported image, video, PDF, text, or audio data.
- Use the Python SDK to manage datasets and workflows, if needed.
Verdict
Labellerr supports varied data types, annotation methods, and export formats for machine-learning workflows. The free plan has project and seat limits, while Pro offers more credits and seats for $9,999 a year.
Questions
Does Labellerr have a free plan?
Yes. The Researcher Plan is free and includes 2,500 data credits, one seat, one workspace, and up to 10 projects.
How much does Pro cost?
Pro is billed annually at $9,999 per year. It includes 100,000 data credits and up to 200 seats.
What platforms does Labellerr support?
The listed platforms are web, API, and self-hosted.
What data can teams annotate?
Projects can use images, videos, PDFs, text, and audio. Supported image formats include JPG, JPEG, PNG, BMP, and TIFF.
Can Labellerr connect with machine-learning services?
Integrations with GCP Vertex AI, AWS SageMaker, and Azure ML are add-ons for applicable plans.
Who makes Labellerr?
The site identifies Tensor Matics Inc as the maker. Labellerr was founded in 2018 and lists offices in San Francisco and Chandigarh.
Facts from Labellerr's own pages
- Automated labeling
- Its automated labeling features include prompt-based labeling, model-assisted labeling, and active learning. · labellerr.com, 4 Oct 2026
- Cloud storage
- The enterprise page names AWS S3, Google Cloud Storage, and Azure Blob as supported remote data storage options. · labellerr.com, 4 Oct 2026
- Data credit limit
- The pricing page says unused data credits do not carry forward to the next payment cycle. · labellerr.com, 4 Oct 2026
- Data types
- The platform supports projects using images, videos, PDFs, text, and audio. · labellerr.com, 4 Oct 2026
- Exports
- The homepage lists CSV, JSON, COCO, Pascal VOC, and custom formats for annotated data export. · labellerr.com, 4 Oct 2026
- Founded
- 2018 · labellerr.com, 28 Sept 2026
- Headquarters
- San Francisco, California, United States · labellerr.com, 28 Sept 2026
- Hosting
- Enterprise plans list private cloud and on-premise hosting as an add-on, and the platform page describes deployment on customer cloud infrastructure or hardware. · labellerr.com, 4 Oct 2026
- Maker and offices
- The site identifies Tensor Matics Inc and lists a San Francisco office and an India office in Chandigarh. · labellerr.com, 4 Oct 2026
- ML integrations
- The pricing page lists integration with GCP Vertex AI, AWS SageMaker, and Azure ML as an add-on for applicable plans. · labellerr.com, 4 Oct 2026
- Purpose
- Labellerr is a data labeling and annotation platform for preparing training data for AI and machine learning teams. · labellerr.com, 4 Oct 2026
- SAM
- Labellerr states that it natively supports Meta’s SAM, SAM 2, and SAM 3 for annotation. · labellerr.com, 4 Oct 2026
- SDK
- A Python SDK can be used to manage datasets and workflows programmatically in ML pipelines. · labellerr.com, 4 Oct 2026
- Security
- Labellerr says it uses Auth0 authentication, TLS 1.2 or higher in transit, and AES-256 encryption for data. · labellerr.com, 4 Oct 2026
- Support
- Enterprise plans include 24/7 email, chat, and call support, while Researcher and Pro list business-hours email support. · labellerr.com, 4 Oct 2026
- Who it serves
- The company describes its platform as helping machine-learning teams build computer-vision AI, including teams in automotive, medical imaging, and manufacturing. · labellerr.com, 4 Oct 2026
Where Labellerr stands on Freedom251
- Image Annotation Software#8 of 28