Instead of hand-labeling millions of data points by hand, automatically label vast amounts of training data using programmatic labeling functions—based on rules, heuristics, ontologies, legacy systems, and more—via a no-code UI or Python SDK.

Snorkel Flow automatically estimates the different labeling functions’ accuracies, denoises and integrates them, and stores versioned training data. Unlike with hand-labeled data, you create training data in Snorkel Flow using code, so you can audit and modify it almost instantly.

Train state-of-the-art ML models with a button push or use the Python SDK to plug into your existing modeling pipelines. Deploy these high-accuracy models immediately as real-time or batch APIs or via SDK.

Identify errors to improve application quality with guided analysis. Monitor and rapidly adapt to changes without having to relabel from scratch. The result: AI development evolves from a one-shot exercise to a continuous improvement process.