About Cleanlab
At Cleanlab, we pioneer a future where AI works reliably with messy, real-world, human data. We envision a world where AI empowers people even in domains where error-prone data makes building AI systems extremely challenging, whether automating error correction in a hospital’s medical code data, helping a self-driving car company train navigation AI on noisy data, or assisting a software engineer in automating data cleaning for an ML pipeline.
What we do and how we do it
Cleanlab is the data reliability layer checking every input and output of your modern AI stack. Our flagship product Cleanlab Studio is an enterprise grade data curation platform that adds trust and reliability to data-driven solutions like LLMs, ML models, analytics, product catalogs, and data warehouses. It integrates like a Brita filter on the data going in and the predictions flowing out of your data-driven systems, to find and fix errors in data, auto-label data accurately and cheaper with AI, and train more accurate state-of-the-art ML models for you in a single click using the improved data.
Cleanlab Studio offers three standout features that set it apart from other platforms: data-agnostic — it works equally well for text, tabular, image, structured, and unstructured data, domain-specific — it learns what good looks like for each customer's data/models, and intuitive — web app, API, and both model training and data improvement in one-click.
Our story
The three Cleanlab founders did their PhDs together at MIT, conducting over a decade of computer science research and amassing over 15,000 citations.
Their mission was simple: empower any organization to automatically find and fix every major issue in datasets to automate reliability for data-driven solutions (e.g. Large Language Models (LLMs), AI models, analytics systems).
The team invented the theory and algorithms that became a sub-field of machine learning called
eventually realized as the most popular software for systematically improving the value of any dataset.We envision a future where anyone can build reliable AI solutions to solve hard tasks with low quality data, in hours, not months.
Curtis Northcutt CEO
MIT | PhD in CS (ML) - 1,500+ citations
MIT thesis award. PhD in CS from MIT. Invented confident learning, the foundation of Cleanlab.
Jonas Mueller Chief Scientist
MIT | PhD in CS (ML) - 4,000+ citations
Built Amazon Web Services AutoML service used by thousands of companies.
Anish Athalye CTO
MIT | PhD in CS (Systems) - 7,000+ citations
30,000+ stars across GitHub projects. ICML best paper winner.
The Cleanlab Mission
Our mission is to empower people with the first enterprise solution for automated data-centric ML ops: from data cleaning to training reliable models on real-world, human, noisy labeled data. At Cleanlab, we strive to combine the good and avoid the bad from what we've learned while working across the world's top technology and AI organizations to build a company culture that cares: about our customers, our impact on the world, and each other. Every Cleanlab product is built with four pillars in mind:
Security
Cleanlab provides enterprise customers with SaaS encrypted solutions and VPC-first solutions.
Data-agnostic
Works for all major data types (text, visual, tabular, audio, etc) regardless of model/platform
Scalability
Solutions for small datasets and massive datasets.
Trust and Reliability
Add trust and reliability to every datapoint with 20+ dimensions of smart metadata.
Recognized industry leaders in AI
Cleanlab has been featured as an industry leader by Forbes and CB Insights.
2024
AI 50
Listed among the 50 most innovative firms driving advancements and commercial applications in AI.
2024
AI 100
Listed among the most promising private companies applying AI across industries and around the world.
2023
GenAI 50
Listed among the top 50 private companies leading advancements in generative AI technology.