Snorkel AI is a data-centric artificial intelligence (AI) platform that focuses on programmatic data labeling and weak supervision. The platform, developed at the Stanford AI Lab, allows enterprises to turn their data into accurate and adaptive AI applications quickly. Snorkel AI's solutions include programmatic data sampling, labeling, curation, and cleaning, which help to fine-tune and align AI models 10-100 times faster and better. The platform supports the development of foundation models and large language models (LLMs) by providing tools for data labeling at scale, improving model quality, and customizing LLMs. Snorkel Flow, a key feature of the platform, automates data development and labeling while reducing AI development costs and time by 90%. It also enables users to programmatically label training data, correct model errors, and discover important slices of datasets through guided analysis. Snorkel AI is interoperable with various AI stacks, supports cloud and on-premises infrastructure, and offers comprehensive support for a wide range of ML tasks and data types. The platform has been proven effective at world-leading companies and can be used in various industries, including finance, healthcare, insurance, government, and more. Snorkel AI has a strong research background, with over 80 open-access publications and contributions to top peer-reviewed journals. Their website provides resources such as blogs, events, research papers, and case studies featuring well-known companies like Apple, Google, and Intel. Overall, Snorkel AI aims to make AI more accessible and customizable for every enterprise by focusing on the crucial aspects of data that models learn from.