Snorkel AI Announces General Availability Of Its Data-Centric AI Platform

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The generally available version of Snorkel Flow delivers a data-centric development workflow for data science and machine learning practitioners

Snorkel AI announced the general availability of its data-centric AI platform, Snorkel Flow, for enterprises to accelerate AI application development 10-100x with automated data labelling. The generally available version of Snorkel Flow includes enhancements to its programmatic data labelling, integrated ML modelling, collaborative AI application development, guided data iteration capabilities, and pre-built templates for classification of and information extraction from documents.

To solve the training data bottleneck, Snorkel Flow provides the data-centric AI platform for enterprise teams to label training data programmatically, use error analysis to guide training data and model iteration in tandem, and adapt to real-world changes with a few clicks rather than complete manual relabeling. With Snorkel Flow, organisations have achieved state-of-the-art machine learning model accuracy in days rather than weeks or months.

“Snorkel Flow is the result of over half a decade of research and close partnership with our customers. With a focus on speed, privacy, and collaboration, the platform delivers what Fortune 500 companies need to build mission-critical AI applications that power their business, protect data, and scale the use of AI,” said Alex Ratner, Co-Founder and CEO, Snorkel AI.

The generally available version of Snorkel Flow delivers a data-centric development workflow for data science and machine learning practitioners to tackle document intelligence applications.

Snorkel Flow is built for the modern enterprise featuring cloud-agnostic Kubernetes deployment options, role-based access controls, SSO integrations, encryption in transit and at rest, and more. In addition to generally available capabilities, several enhancements were released as beta recently, including the new Studio experience, annotation workspace, PDF extraction and conversational AI pipelines, sequence tagging capabilities, and more.