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Document Classification

Build AI-powered document classification applications in a fraction of the time without hand-labeling data using Snorkel Flow.

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6 MONTHS

of hand labeled data replaced in 30 minutes using Snorkel

Overview

One Size Fits You, Not All
Achieve greater performance gains by exploiting domain-specific text features of your own data.
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Faster, Lower-cost Development

Use programmatic labeling to develop high-quality AI applications in hours instead of spending weeks or months on expensive hand-labeling.

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Higher-accuracy Models

Iterate on your application, using a closed-loop approach with intermediate results and analysis at every step to zero in on errors.

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Flexible Integrations

Easily integrate labeling, training and analysis pipelines defined over diverse input types–text, PDF, HTML, and more–with downstream applications using APIs or a Python SDK.

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Easier SME Collaboration

Build complex classification apps intuitively while preserving natural information about data taxonomies with subject matter expert (SME) collaboration.

Use Cases

Explore Enterprise Solutions For Classification

Case Study

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Google used Snorkel to replace 100K+ hand-annotated labels in critical ML pipelines for text classification.

Problem

Content, product, and event classification problems change too fast to hand-label, even with significant annotation budget.

Solution

Google deployed early versions of Snorkel's core technology with three high-impact teams, repurposing many resources as labeling functions.

Result

Hours of labeling function development replaced 10-100K+ hand labels, significantly impacting the bottom line and accelerating of ML adoption.

6 MONTHS

of hand-labeling data replaced in 30 mins

52%

performance improvement

100K+

hand labels replaced with
programmatic approach

How Snorkel Flow Works

Customized AI Apps for Classification
Snorkel Flow is an end-to-end ML platform that makes AI-powered document classification practical and efficient. Create labeling functions to programmatically label and manage training data, then train state-of-the-art machine learning models using your own data. Analyze errors using guided tools and systematically iterate until you achieve deployment-ready performance. Deploy your custom classification application as a real-time or batch API or Python SDK with just one click.

An End-to-end ML Platform

Designed for Collaboration

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Data Scientist Friendly

  • Integrated Jupyter notebooks
  • Instant analysis tools
  • Ready-to-use models
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Domain Expert Friendly

  • Intuitive, no-code UI
  • Rich dashboards and visualizations
  • Full-featured, push-button error analysis
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Developer Friendly

  • Platform access via Python SDK
  • Online or batch API deployment
  • Containerized software for cloud or on-premises deployments

Research

Based on Years of Novel Research
Learn more about groundbreaking techniques for machine learning and weak supervision developed by the Snorkel AI team at Stanford AI Lab and beyond.

Accelerate your AI application development today

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