Top US Bank
accuracy for contract intelligence built using Snorkel Flow in under 24 hours
Overview
Extract useful data from any tables, cells, and forms linked to all headers, units, or references.
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.
Rapidly Adaptable
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.
High-accuracy Models
Leverage large amounts of labeled and unlabeled data, NLP primitives, and state-of-the-art model architectures to build high-accuracy models.
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.
Use Cases
Information Extraction Customized for Your Workflow
Case Study
Top US Bank
A top U.S. bank uses Snorkel Flow to quickly build AI applications that classify and extract information from contracts and other legal documents.
The bank estimated that, for a time-sensitive use case, labeling data by hand would take over a month.
With Snorkel Flow, the team produced a AI-powered contract intelligence application that was over 99% accurate in under 24 hours.
The resulting AI application was quickly and easily adapted to new problems.
<24 HOURS
to develop first model
99.1%
model accuracy
250K
documents labeled
An End-to-end ML Platform
Designed for Collaboration
Data Scientist Friendly
- Integrated Jupyter notebooks
- Instant analysis tools
- Ready-to-use models
Domain Expert Friendly
- Intuitive, no-code UI
- Rich dashboards and visualizations
- Full-featured, push-button error analysis
Developer Friendly
- Platform access via Python SDK
- Online or batch API deployment
- Containerized software for cloud or on-premises deployments
Research