GenAI you can trust.

Cleanlab adds trust to all data going in and responses coming out of AI, RAG, and GenAI solutions.
Experience GenAI that doesn't hallucinate.
Automatically detect and fix data issues that negatively impact your revenue, and significantly reduce the time and cost associated with improving analytics, LLM, and ML/AI solutions built on imperfect data.
80%
Time saved
Cut down data quality management time and reduce labeling costs by 5x to 50x.
10x
Faster production
Instantly assure data quality with AI-powered checks for every datapoint.
50%
More output
Increase the output of your team for the same level of effort.
See why our customers 🤍 us
Our solutions
Cleanlab Studio is an AI-powered data curation platform that automates essential data science and engineering tasks for AI model and data improvement. It refines and curates your data by correcting information errors, addressing common issues, and automatically adding intelligent metadata to each data point, improving reliability for tasks like training ML models, business intelligence, and analytics.
Automatically improve your dataset. No code required.
Our AI automatically detects label errors, outliers, PII, NSFW, near duplicates, drift, low-quality image examples like dark/blurry, under/over-exposed, and more.Explore interactive demo
Automatically improve your dataset. No code required.
Data curation
Automatically improve your dataset. No code required.
Our AI automatically detects label errors, outliers, PII, NSFW, near duplicates, drift, low-quality image examples like dark/blurry, under/over-exposed, and more.Explore interactive demo
Automatically improve your dataset. No code required.
Detect hallucinations
Detect hallucinations in production-ready GenAI systems with reliable trustworthiness scores for every LLM output.
Cleanlab’s Trustworthy Language Model (TLM) produces higher quality outputs than the leading LLMs using built-in hallucination detection, observability, and trustworthiness scores for every response-- enabling production-grade automation with LLMs where hallucinations are a show-stopper. Learn more about TLM
Detect hallucinations in production-ready GenAI systems with reliable trustworthiness scores for every LLM output.
Automated labeling
AI-automated data labeling.
Our AI-automated data labeling is domain-specific and we guarantee better results than third-party data annotation tools. Cleanlab automatically labels most of your data using Foundation model confidence-scores, and then suggest which data is best to label or re-label next using active learning.Get started for free
AI-automated data labeling.
Analytics
Explore analytics, summaries, and specific issues within your datasets.
Find the classes in your dataset with the most label issues and explore the entire heatmap of suggested corrections for all classes in your dataset. Estimate consensus and annotator-quality for datasets labeled by multiple annotators.Get started for free
Explore analytics, summaries, and specific issues within your datasets.
Model deployment
Automatically train, tune, and deploy 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.Read tutorial
Automatically train, tune, and deploy robust models via the world’s most advanced AutoML.
Pioneered at MIT and trusted by hundreds of top organizations. Read our story.
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Cleanlab helps our customers increase the business value of their data.
All customer stories
200+ hrs saved
In ML project development time
Amazon has used Cleanlab to improve product recommendations and device response, increasing customer satisfaction and boosting sales.
Manually inspecting and fixing potential label errors can be time consuming. We can train a better model using Cleanlab to filter noisy data.
Cher Simon
Amazon AWS Principal Solutions Architect at Amazon
Add trust to every data point.
Start your 2-week free trial today. No credit card needed.
Cleanlab Open-Source
GitHub
Limited Python API Access
Automatically detects issues
No auto-fix
Learn more
Cleanlab Studio
Free trial
Sign up now
No code / ML engineering needed
Web interface and API access
Auto-fix data issues
Image, text, document, and tabular data
AI-automated data labeling
Trustworthy Language Model (TLM)
Analytics
AutoML model training/deployment
Contact sales
Cleanlab Studio Enterprise
Contact sales
Everything in free trial
More ML and data correction tasks
Project-optimized AutoML
Image segmentation
Object detection
VPC and cloud integration
Hosted deployment / inference
Priority for new feature requests
Scale to massive datasets
Dedicated support engineer
Book demo
Lukas Lodes
I got significantly better results using Cleanlab Studio than the cleanlab open-source package, mainly because it’s so much easier to use.
Lukas Lodes | AI Researcher at AIMotion Institute
AI Researcher at AIMotion Institute
Andrew Ng
Question: There’ve been many Model-Centric breakthroughs that have excited and inspired the field. What are some of your favorite examples of Data-Centric breakthroughs or wins that will inspire the field?
Answer: “The Cleanlab stuff out of MIT”
Andrew Ng, Keynote talk at ICML 2023 Workshop on Data-Centric Machine Learning
Keynote talk at ICML 2023 Workshop on Data-Centric Machine Learning
Fredrik Olsson
Cleanlab Studio is a very effective solution to calm my nerves when it comes to label noise!
Fredrik Olsson | PhD. Head of Data Science at Gavagai
PhD. Head of Data Science at Gavagai
Lukas Lodes
I got significantly better results using Cleanlab Studio than the cleanlab open-source package, mainly because it’s so much easier to use.
Lukas Lodes | AI Researcher at AIMotion Institute
AI Researcher at AIMotion Institute
Andrew Ng
Question: There’ve been many Model-Centric breakthroughs that have excited and inspired the field. What are some of your favorite examples of Data-Centric breakthroughs or wins that will inspire the field?
Answer: “The Cleanlab stuff out of MIT”
Andrew Ng, Keynote talk at ICML 2023 Workshop on Data-Centric Machine Learning
Keynote talk at ICML 2023 Workshop on Data-Centric Machine Learning

Enterprise-ready
integration.

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

Local Data Files

Programmatically

Data Warehouse

Cloud Storage

Enhanced security for sensitive data.
Some datasets require privacy beyond Cleanlab’s already top-tier security. Cleanlab Studio is deployable within your Virtual Private Cloud (VPC) for you to manage regular, rigorous security testing and isolated network environments, minimize exposure and provide granular control over network configurations and access permissions.
Learn more
Ready to get started?
Start your 14-day free trial today with Cleanlab Studio.