Cleanlab

Cleanlab Studio is a comprehensive platform that handles the entire data quality and data-centric AI pipeline within a single framework, designed for analytics and machine learning tasks. It offers a range of features, including data curation, AutoML, model deployment, and diagnostics, and can automatically improve datasets without requiring any code. Cleanlab Studio can identify and fix data issues such as outliers, ambiguous data, and incorrect labels, providing real-time and batch inference through a web interface or REST API. The platform is built for security and scalability, making it suitable for enterprise use, and interfaces directly with various data storage solutions, including local files, data warehouses, and cloud storage. Cleanlab’s Trustworthy Language Model (TLM) adds a trustworthiness score to every LLM response, making it reliable for large datasets and enterprise applications, such as chatbots, auto-labeling, data extraction, and retrieval-augmented generation. Recognized by CB Insights as one of the 50 most innovative Generative AI companies, Cleanlab’s technology is used by top organizations like Google, Amazon, and BBVA to enhance data quality and model accuracy. The company raised $25 million in Series A funding to further develop its data-centric AI software. Cleanlab’s open-source library is the leading software framework for practicing Data-Centric AI, applicable across various industries, including healthcare, financial services, e-commerce, and manufacturing. The platform offers automated support for data labeling, issue detection and correction, ML model training, and deployment, significantly reducing label costs and improving model accuracy. Cleanlab Studio ensures high-quality data for applications such as fraud detection, customer interaction, and risk assessment in financial services, and aids in content moderation by detecting unsafe or low-quality content in image and text datasets.