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  • Significantly improve model accuracy and reliability for models based on real world data so that you can solve real problems for your customers.


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  • Cut time spent on data quality by 1/3 and labeling spend by 5x-100x, so that your data scientists can focus their time on generating value, not labeling data.


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  • Data and label quality assurance check for every dataset - instantly see the most common label errors and data issues in your datasets so you can decide what actions you need to take.

Enterprise Subscription Plan

Cleanlab StudioCleanlab Studiofor Enterprise
Improves image/text/tabular data
Trains reliable ML models and LLMs
Support for audio/PDF/entity/etc data
No data/usage caps
Prioritized requests for new features
Support from PhDs who taught the MIT DCAI class
Custom model deployment integration
Custom data integration (VPC, platform, etc)
On-prem integration and support
Active learning, data column correction, more!