Snorkel AI

Snorkel AI emerged from Stanford University's renowned AI Lab in 2019 as a pioneering force in data-centric artificial intelligence, transforming how enterprises develop, deploy, and manage AI applications at scale. Founded by a team of world-class researchers including CEO Alex Ratner, co-founders Chris Ré, Paroma Varma, Braden Hancock, and Henry Ehrenberg, Snorkel AI built upon four years of groundbreaking research that began in 2015 at Stanford. The company's fundamental insight—that labeled training data is increasingly what determines the success or failure of AI applications—catalyzed a paradigm shift from manual data labeling to programmatic data development, enabling organizations to build AI models 10-100x faster than traditional methods.

Headquartered in Redwood City, California, Snorkel AI has rapidly established itself as the enterprise standard for data-centric AI development. The company's flagship platform, Snorkel Flow, revolutionizes AI application development by enabling users to programmatically label and curate data using rules, heuristics, and automation rather than tedious manual annotation. This approach has attracted an impressive roster of customers including five of the top ten U.S. banks, Fortune 500 enterprises such as Google, Intel, Apple, IBM, Experian, Wayfair, and Bank of America, plus critical government agencies including DARPA and In-Q-Tel. With this customer base managing mission-critical AI applications, Snorkel AI has proven its platform's capability to handle the most demanding enterprise requirements.

Snorkel AI's meteoric growth trajectory culminated in achieving unicorn status in 2021 following an $85 million Series C round at a $1 billion valuation. By May 2025, the company announced a landmark $100 million Series D funding round, bringing total capital raised to $235 million from leading investors including Lightspeed Venture Partners, Greylock, Google Ventures (GV), In-Q-Tel, BlackRock, and Walden. This funding enabled Snorkel to expand its platform beyond traditional machine learning to address the rapidly evolving landscape of foundation models, large language models (LLMs), and generative AI, introducing new products like Snorkel Evaluate and Snorkel Expert to power custom AI deployment with enhanced evaluation and fine-tuning capabilities.

What distinguishes Snorkel AI in the crowded enterprise AI landscape is its unwavering focus on solving the data problem that lies at the heart of AI success. While competitors concentrate on models and infrastructure, Snorkel pioneered programmatic labeling functions that express domain expert knowledge as code, enabling rapid iteration and continuous improvement of training data quality. The company's research-driven approach, combined with deep integrations with platforms like Databricks, Amazon SageMaker, and leading foundation models including OpenAI ChatGPT, Google Gemini, and Meta Llama, positions Snorkel AI as the essential data layer powering the next generation of enterprise AI applications across industries from financial services to healthcare to government.