Build AI-powered sentiment analysis applications to detect sentiments, at the level of words, sentences, paragraphs, or documents, in a fraction of time without hand-labeling training data using Snorkel Flow.
Technology developed and deployed with the world’s leading organizations
Decode Sentiments in Shades of Gray
Rapidly and precisely build ML models to quantify and analyze complex sentiments in virtually any text.
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.
Monitor for changes in the data, and rapidly adapt using built-in error analysis tools. Zoom in on errors to fine-tune training data & models with guided iteration.
Easier SME Collaboration
Enable Subject Matter Experts (SME) to define polarity, subjectivity or tone, and refine schematic boundaries programmatically using a no-code or Jupyter notebook-based interface.
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.
Industry Use Cases —
Sentiment Analysis Customized for Your Workflow
Build industry-specific AI applications combining state-of-the-art machine learning approaches with industry-specific best practices and last-mile connectors, all on an enterprise-scale platform.
Banks can classify contracts by terms and conditions to smoothly ensure regulatory complience.
TELECOM & CYBER
Telecom organizations can classify customer usage documents to target promotional offers.
Clinical Trial Matching
Biotech organizations can classify patient records to identify actionable clinical trial candidates.
Insurance underwriters can classify piolicy documents by behavioral or occupational variables to assess risk.
Search Engine Optimization
Software companies can recognize named entities in customer search queries and to optimize website content.
An End-to-end ML Platform —
Designed for Collaboration
Data Scientist Friendly
- Integrated Jupyter notebooks
- Guided error analysis
- Ready-to-use models
Domain Expert Friendly
- Intuitive, no-code UI
- Rich dashboards and visualizations
- Full-featured, push-button error analysis
- Platform access via Python SDK
- Online or batch API deployment
- Containerized software for cloud or on-premises deployments
Explore More About Snorkel
Learn more about groundbreaking techniques for programmatic labeling and weak supervision developed by Team Snorkel and the broader data science community.