Cleanlab

Elevate Data Quality with Cleanlab: Advanced AI for Data-Centric Machine Learning

Cleanlab offers a state-of-the-art AI-powered platform designed to enhance data quality and streamline the machine learning pipeline. With automated tools for data curation, model training, and deployment, Cleanlab enables organizations to transform unreliable data into reliable models and insights. Trusted by leading institutions and companies, Cleanlab provides robust solutions to ensure high-quality datasets for analytics and machine learning tasks.

Acquisition note (January 2026): Handshake acquired Cleanlab, announced on January 28, 2026. The Cleanlab team now leads data-quality research for Handshake AI, and the Cleanlab site still offers its trust and hallucination detection tools.

Key Features:

• Data Curation: Automatically improve your dataset by finding and fixing data issues such as outliers and ambiguous data, and correcting label errors without writing code.
• AutoML: Utilize the world’s most advanced automated machine learning pipeline for data preprocessing, foundation model fine-tuning, hyperparameter tuning, and model selection.
• Model Deployment: Seamlessly train and deploy robust ML models with just a few clicks, enabling real-time and batch inference through a web interface or REST API.
• Diagnostics: Explore detailed analytics, summaries, and specific issues within your datasets, identifying the classes with the most label issues and suggested corrections.
• Enterprise Integration: Interface directly with your data regardless of its storage location, whether local files, programmatic access, data warehouses, or cloud storage.
• Security and Scalability: Built with enterprise-level security and scalability, ensuring data protection and efficient handling of large datasets.

Ideal Use Case:

• Data and Tech Consulting: Enhance data reliability and model performance for consulting projects.
• Financial Services and Insurance: Improve model accuracy and reduce label costs for financial and insurance data.
• E-Commerce and Retail: Ensure high-quality data for customer behavior analysis and inventory management.
• Healthcare: Improve the accuracy of medical datasets and models, enhancing patient care and research.

Why Use Cleanlab:

• Efficiency: Automate the entire data quality management process, saving time and reducing manual effort.
• Accuracy: Enhance model accuracy by correcting data and label issues, ensuring reliable insights and predictions.
• Integration: Seamlessly integrate with existing data storage solutions and workflows, enhancing operational efficiency.
• Scalability: Support large-scale data projects with robust, scalable AI solutions.
• Security: Maintain high standards of data security and compliance, protecting sensitive information.

tl;dr:

Cleanlab provides an AI-powered platform for data-centric machine learning and dataset quality management, enhancing efficiency, accuracy, and scalability. Ideal for various industries, it offers automated tools for data curation, model training, and deployment, ensuring high-quality datasets and reliable insights.

FAQ

Who owns Cleanlab? Handshake acquired Cleanlab in January 2026. The Cleanlab product is still offered at cleanlab.ai, and its team works on Handshake AI's training data.

Q: What is Cleanlab used for? A: Advanced AI for Data-Centric Machine Learning.

Q: Is Cleanlab free? A: Pricing varies by plan. Visit the Cleanlab pricing page for current tiers and details.

Q: What is Cleanlab's main use case? A: Cleanlab helps ML engineers and platform teams build, deploy, and scale AI infrastructure and pipelines.

Q: What are alternatives to Cleanlab? A: Top alternatives to Cleanlab include Grok, fal.ai, and Vercel AI SDK. See our directory for in-depth comparisons.

Related

Looking for more options? Browse the AI Infrastructure directory or read our best AI infrastructure tools listicle. Cleanlab is also tracked on Crunchbase.