Cleanlab: Open-Source Library for Data-Centric AI and Label Quality

Cleanlab is an open-source library for data-centric AI and machine learning quality, developed by the Cleanlab organization and updated through January 2026. It provides a standardized package for identifying and fixing issues in messy, real-world datasets and labels.

Use Cases

• Detecting "noisy-labels" in classification datasets to improve model performance
• Identifying "outlier-detection" for anomaly removal in feature sets
• Automating "data-validation" within machine learning workflows

Strengths

• Apache-2.0 license
• Supports data-centric-ai workflows
• Includes weak-supervision capabilities

Limitations

• Software library rather than a static dataset
• Requires integration into ML pipelines

Provenance

Source

cleanlab

Freshness

Updated as of January 2026.