Label data 100x faster
Buld high-quality datasets at enterprise scale using programmatic data development and your subject matter experts.
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Top 3 US bank
A Top 3 US bank uses Snorkel Flow to quickly respond to high-stakes regulatory changes hidden in complex finance documents while reducing their AI data development time from 6 months to less than one day.
Schlumberger utilizes Snorkel Flow for programmatic data operations, efficiently labeling over 70 years of oil well reports to enhance proactive maintenance for its customers.
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Label data 100x faster programmatically
Rather than asking domain experts to provide individual labels manually or outsourcing to questionable 3rd party services, transform their insight into labeling functions that are applied intelligently 100x faster.
Learn how Google reduced 6 months of hand labeling down to a 30-minute process
Labeling functions: simple techniques for complex use cases
Quickly encode data and expertise into software with programmatic labeling functions using keywords, existing ontologies, knowledge bases, other models, and cluster embeddings.
Dive deep into programmatic labeling
Build better AI starting today
Dive into our curated selection of guides and demos to streamline your AI journey.
Unparalleled support for complex data types
Leverage pre- and post-processors, data viewers, and LF types purpose-built for text, PDFs, conversational data, and more.
Leveraging Data-Centric AI for Document Intelligence and PDF Extraction
Adapt easily to inevitable changes
Keep models performant in the face of data drift or objective changes by only updating a handful of labeling functions vs billions of data points.
Importance of data development: highlights from the Enterprise LLM Summit
AI data development platform capabilities
Flexible labeling function creation
Effortlessly create custom Labeling Functions(LFs) with our intuitive no-code UI and SDK, or leverage auto-suggested LFs to speed up AI data development even further.
AI data development as software development
Snorkel Flow’s label models aggregate your LFs intelligently to label data at scale automatically.
Labeling functions from external models
Incorporate signal from integrated the latest LLMs and foundation models using prompts.
Curate data at scale
Leverage programmatic labeling to curate, filter, and augment slices of data to build highly relevant training datasets from millions or billions of data points into smaller distilled models specialized towards a specific task.
Labeling functions from existing labels
Reuse existing labels (even noisy ones) as labeling functions that are combined and corrected by other labeling sources.
Our interface enables domain experts to label ground truth and troubleshoot challenging data slices during iteration.
Get real-time quantitative and qualitative feedback on the labeling functions you write for guided iteration.
Diverse data displays
Multiple ways to view your data (individual, table, clusters, etc.) help you understand and label it more efficiently.