Cleanlab
by Cleanlab
AI for data quality and trustworthy datasets
Cleanlab automatically detects and fixes issues in datasets and AI model outputs. Identifies label errors, outliers, near-duplicates, and data quality problems for more reliable AI.
🎯 Key Features
Label error detection
Outlier detection
Near-duplicate detection
Data quality scoring
Automatic data cleaning
LLM output validation
Trustworthiness scoring
Dataset curation
Multi-modal support
Confidence estimation
Active learning support
Strengths
Excellent data quality detection
Open-source core
Research-backed algorithms
Multi-modal support
Easy integration
Active development
Strong academic foundation
Limitations
Not real-time focused
Primarily for training data
Limited LLM-specific features
Batch processing oriented
Studio features require subscription
Best For
- Training data curation
- Model quality improvement
- Dataset cleaning
- Fine-tuning preparation
- Quality assurance
- Research projects