How Cleanlab can help
Cleanlab Studio automatically improves data and deploys robust models.

Cleanlab Studio helps you quickly fix the detected issues to get a better version of your dataset. Use the auto-corrected dataset produced by Cleanlab in place of your original dataset to get more reliable ML and analytics, without any change in your existing code!

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In this tabular dataset of student grades, Cleanlab Studio automatically detected label errors, ambiguous examples, and outliers. These issues harm downstream models and analytics.

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HOW IT WORKS

How Cleanlab can help your consulting team
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Auto-detect Issues

Automatically detect issues in a client’s data such as incorrect values, anomalies, bad metadata, etc. Consider if using software to audit data for mistakes is helpful for compliance.

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Efficient Annotation

Efficiently annotate data for a client, or help them set up an effective data labeling pipeline.

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Built with AI

Issue detection is based on state-of-the-art AI algorithms invented by Cleanlab scientists.

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Train and Produce Reliable Models

Easily train robust ML models on messy real-world datasets and deploy them in one click. Cleanlab uses Data-Centric AI to produce reliable models. Learn more about these techniques via the free MIT course taught by the Cleanlab founders.

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Quickly Resolve Errors

Fix detected data issues quickly via the Cleanlab Studio interface, or inform client which data require careful review.

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Resources and Tutorials

Videos on using Cleanlab Studio to find and fix incorrect labels for: text data, tabular data, and image data.

CASE STUDY

Berkeley Research Group is a global consulting firm that helps leading organizations advance in three key areas: disputes and investigations, corporate finance, and performance improvement and advisory.

After over a month of using Cleanlab to improve ML and AI models, Berkeley Research Group reported Cleanlab had increased model accuracy by 15%, improved explainability, and addressed performance impediments. The team was able to cut out training iterations by one-third, and saw an overall performance improvement for our Data Science team.

Read more: LinkedIn post by Steven Gawthorpe on Cleanlab

15%

improvement in ML model accuracy

33%

reduction in time spent on data/ML work

“We’ve started relying on Cleanlab to improve our ML and AI models at Berkeley Research Group LLC… I have to say, I’m impressed.”

Steven Gawthorpe

Associate Director of Data Science at Berkeley Research Group

Start learning with step-by-step tutorials
Catching Issues in a Product Catalog (Multimodal Dataset)
Use Cleanlab Studio to ensure high-quality product catalogs.
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Understanding Your Data
Utilize Filters and Analytics to better resolve label issues and process errors.
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Reliable ML Model Training and Deployment From Raw Data
Deploy reliable ML models in production using Cleanlab Studio.
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Related Applications
Foundation and Large Language Models
Boost fine-tuning accuracy and reduce time spent.
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Data Annotation and Crowdsourcing
Label data efficiently and accurately, understand annotator quality.
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Data Entry, Management, and Curation
AI expert review of your data stores to find errors or incorrect labels.
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Business Intelligence/Analytics
Correct data errors for more accurate analytics/modeling enabling better decisions.
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Customer Service
Fix common issues in customer data, and deploy robust ML models to better understand customers and handle their requests.
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Content Moderation
Train more accurate content moderation models in less time.
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