No code. Automated.
Data you can trust.
Turn unreliable data into reliable models and insights. Automatically find and fix errors for LLMs and the modern AI stack.
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Reliable data. Reliable models (or insights). Reliable revenue.
Cleanlab Studio handles the entire data quality and data-centric AI pipeline in a single framework for analytics and machine learning tasks.

Data Curation

Automatically improve your dataset. No code required.
  • Find and fix data issues (e.g. outliers, ambiguous data)
  • Find and fix label issues (e.g. incorrectly labeled data)
  • Know when to trust your data: Avoid spending time/cost to review data that’s already high quality, by automatically validating all datasets in Cleanlab Studio

Auto ML

Automatically train and tune robust models via the world’s most advanced AutoML.
  • Automated pipeline does all ML for you: data preprocessing, foundation model fine-tuning, hyperparameter tuning, and model selection
  • ML models are used to diagnose data issues, and then can be re-trained on your corrected dataset with one click

Model Deployment

Seamless model deployment: Just a few clicks to get accurate predictions.
  • Train and deploy a robust ML model without writing code
  • Access real-time and batch inference through a web interface or REST API
  • Get predictions for unlabeled data or evaluate models on labeled test data


Explore analytics, summaries, and specific issues within your datasets.
  • Find the classes in your dataset with the most label issues
  • Explore the entire heatmap of suggested corrections for all classes in your dataset
  • Cleanlab Studio provides all of this information and more for free as soon as you upload your dataset
Pioneered at MIT and trusted by hundreds of top organizations.
Pioneered at MIT
Cleanlab’s Chief Executive Officer, Curtis Northcutt, invented confident learning during his PhD at MIT while working with the inventor of the quantum computer
Built on the world’s cutting edge AutoML @ AI layer
Prior to Cleanlab, Chief Scientist Jonas Mueller developed Amazon's AutoML platform, used today to train and deploy many models on AWS SageMaker
Designed for security and scalability for enterprise from the ground up
Cleanlab’s Chief Technology Officer, Anish Athalye, is well cited for his PhD work at MIT in the world’s top systems lab (PDOS)
Founded by the instructors of the MIT course on Data-centric AI

Enterprise Ready Integration

Cleanlab Studio interfaces directly with your data, no matter how it is stored.

Local Data Files