Pioneered at MIT and proven at Fortune 500 companies, Cleanlab provides the world's most popular Data-Centric AI software.

Most AI and Analytics are impaired by data issues (data entry errors, mislabeling, outliers, ambiguity, near duplicates, data drift, low-quality or unsafe content, etc); Cleanlab software helps you automatically fix them in any image/text/tabular dataset. This no-code platform can also auto-label big datasets and provide robust machine learning predictions (via models auto-trained on auto-corrected data).

What can I get from Cleanlab software?

1. Automated validation of your data sources (quality assurance for your data team). Your company's data is your competitive advantage, don't let noise dilute its value.
2. Better version of your dataset. Use the cleaned dataset produced by Cleanlab in place of your original dataset to get more reliable ML/Analytics (without any change in your existing code).
3. Better ML deployment (reduced time to deployment & more reliable predictions). Let Cleanlab automatically handle the full ML stack for you! With just a few clicks, deploy more accurate models than fine-tuned OpenAI LLMs for text data and the state-of-art for tabular/image data.

Turn raw data into reliable AI & Analytics, without all the manual data prep work.

Most of our cutting-edge research powering Cleanlab tools is published for transparency and scientific advancement:  cleanlab.ai/research/

AI/ML

Analytics

Data

Enterprise Software

Software Engineering

Cleanlab

Cleanlab's headquarters in San Francisco, CA, United States

Curtis Northcutt

David Kong

Derek Salama

Angela Liu

Andrew Oh

Angie Ruiz-Mitchell

Jonas Mueller

Anish Athalye

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People (10)

Curtis Northcutt

Anish Athalye

Jacob Green

Max Buchan

Jonas Mueller

Andrew Oh

Angie Ruiz-Mitchell

Matt Murphy

Kyle Veator

Derek Salama

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