Labellerr: Data Labeling and Annotation Software
Labellerr helps AI teams prepare training datasets. It is designed for organizations that need to manage data types such as LiDAR, DICOM, and video within a single workflow.
At a glance
- Category
- Data & Analytics
- Best for
- Software companies building AI products, Machine learning engineering teams, Data scientists, Medical AI researchers
- Pricing
- Offers a free Researcher Plan (2,500 credits, 1 seat). The Pro Plan is $499/month for 50,000 credits and 10 seats, with additional seats costing $29-49 per user monthly.
- Key use cases
- Computer Vision Training, Medical Imaging Analysis, LLM Fine-Tuning, Autonomous Systems Development, Content Classification
- Integrations
- GCP Vertex AI, AWS Sagemaker, Azure ML, Google Cloud Storage, AWS S3
- Official website
- labellerr.com
Labellerr is a data labeling and annotation platform for machine learning teams. It supports various data formats, including images, videos, text, audio, PDFs, and specialized medical or robotics formats like DICOM, LiDAR, and NIfTI.
The platform provides tools such as model-assisted labeling and active learning, and offers human-in-the-loop services via professional annotators.
Users can manage the process from data ingestion via cloud storage to exporting labels in formats such as JSON or COCO. The platform includes security features such as AES-256 encryption and options for on-premise deployment.
Buyers should confirm their data volume and seat requirements, as the Pro plan has specific limits on data credits and collaborators.
Key Features
Supports annotation for images, videos, text, audio, PDFs, DICOM, LiDAR, and NIfTI formats.
Includes prompt-based labeling, model-assisted labeling, and active learning automation to help reduce manual work.
Uses Segment Anything Model (SAM and SAM 2) tools to create object masks in images and videos.
Provides pre-trained model-based and ground-truth quality assurance tools to monitor label accuracy.
Supports connection with AI development environments including GCP Vertex AI, AWS Sagemaker, and Azure ML.
Includes AES-256 encryption, Auth0 authentication, and options for private cloud or on-premise hosting.
Use Cases
Annotating images and videos for object detection and instance segmentation.
Using DICOM tools for annotation of medical data.
Preparing text datasets and transcripts for large language model training.
Labeling LiDAR and video data for automotive or robotics applications.
Using text annotation for sentiment analysis and named entity recognition.
Best For
Integrations
Pricing
Offers a free Researcher Plan (2,500 credits, 1 seat). The Pro Plan is $499/month for 50,000 credits and 10 seats, with additional seats costing $29-49 per user monthly.
FAQ
Labellerr supports images (jpg, png), videos (mp4), audio (wav), text (txt), and PDFs, as well as specialized formats like DICOM, LiDAR, and NIfTI.
Yes, there is a free Researcher Plan that includes 2,500 data credits and one seat for students and researchers.
Yes, for enterprise customers, Labellerr offers an on-premise solution that can be deployed in a private cloud or on local hardware.
The Pro Plan is $499/month and includes 50,000 data credits and 10 seats. Additional seats can be added for $29 to $49 per user per month.
Source category: Data & Analytics
Source subcategory: Machine Learning Platform
