Label Studio
Annotate diverse data types for AI model training and validation
Target Audience
- Machine Learning Engineers
- Data Science Teams
- AI Research Labs
- Quality Assurance Specialists
Hashtags
Overview
Label Studio is an open-source platform that helps teams prepare high-quality training data for machine learning models. It supports labeling for text, images, audio, video, time series data, and LLM responses with customizable workflows. The tool is particularly valuable for organizations needing to validate AI outputs or fine-tune large language models with human feedback.
Key Features
Multi-format support
Label text, images, audio, video, and sensor data in one platform
ML-assisted labeling
Accelerate workflows using model predictions as starting points
Team collaboration
Enable multiple annotators with quality control features
Custom templates
Adapt labeling interfaces to specific project needs
API integration
Connect directly to ML pipelines via Python SDK and webhooks
Use Cases
Label images for object detection
Transcribe and tag audio recordings
Evaluate LLM chatbot responses
Annotate time-series sensor data
Mark entities in legal documents
Pros & Cons
Pros
- Supports widest range of data types in open-source ecosystem
- Enterprise-grade collaboration features
- Active community with 17,000+ Slack members
- ML pipeline integration capabilities
Cons
- Steep learning curve for non-technical users
- Advanced features require enterprise subscription
- Self-hosted setup needs technical expertise
Pricing Plans
Community Edition
perpetualFeatures
- Open-source version
- Basic labeling features
- Community support
Enterprise
subscriptionFeatures
- Advanced security
- Premium support
- Team management
Pricing may have changed
For the most up-to-date pricing information, please visit the official website.
Visit websiteFrequently Asked Questions
Is Label Studio really free to use?
Yes, the Community Edition remains free and open-source under Apache 2.0 license
What data types does it support?
Supports text, images, audio, video, time-series data, and LLM response evaluation
Can teams collaborate on projects?
Yes, supports multiple annotators with review workflows and quality control
Integrations
Reviews for Label Studio
Alternatives of Label Studio
Automate AI training data preparation with smart quality assurance
Streamline machine learning operations with real-time model monitoring and governance
Accelerate computer vision model training with precise data labeling
Generate diverse training datasets for AI systems