Continuously update and analyze models to guide development

Use actionable analysis to guide targeted, rapid iteration to improve your models and training data.
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Get immediate data quality feedback

As you label your data, Snorkel Flow automatically retrains models to provide real-time analysis of both your model and (crucially) your training data quality.


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Improve with targeted iteration

Reach performance goals faster by focusing on the slices of your data that are most important to act on. Use auto-generated suggestions and active learning to iterate intelligently.
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Improve with targeted iteration

Reach performance goals faster by focusing on the most important slices of your data to take action on. Use auto-generated suggestions to iterate intelligently.


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Flexible model training

Train leading model architectures without code or use the Python SDK to train custom models on your own infrastructure and bring predictions back to Snorkel Flow for analysis.


Platform modeling capabilities

Integrated model zoo
Train preconfigured, state-of-the-art ML models for a range of modeling tasks with a single click.
AutoML
Automate selecting the best algorithm and hyperparameters for your problem.
Guided iteration
Use suggested actions from error analysis to focus your efforts where you can make the greatest impact.
Custom model flexibility
Easily integrate with your existing models and inference infrastructure using our Python SDK.
Active learning
Use model guidance to prioritize programmatic labeling effort against the highest-impact slices of data.
Auto-generated visualizations
Understand model performance with auto-generated, interactive plots and analyses (no code needed).
Slice-based analyses

Identify, analyze, and improve data slices through collaboration workflows with domain experts.

Automated model updates
Get rapid feedback on training AI development from automatically retrained models and updated analyses.

Dive in

[get_press_posts]
Press
Blog
Research
Case studies
Press
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September 20, 2021
Snorkel AI welcomes industry leaders to the team

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August 9, 2021
This hot startup is now valued at $1 billion for its A.I. skills

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February 24, 2021
The Data-First Enterprise AI Revolution

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July 14, 2020
Meet The Stanford AI Lab Alums That Raised $15 Million To Optimize Machine Learning

Blog
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February 4, 2022
Making Automated Data Labeling a Reality in Modern AI

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Date: Jan 25, 2022
The Principles of Data-Centric AI Development

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Date: Jan 5, 2022
Meet the Snorkelers

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Date: Jul 9, 2021
How to Use Snorkel to Build AI Applications

Research
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2022
Universalizing Weak Supervision

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2021
Ontology-driven weak supervision for clinical entity classification in electronic health records

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2017
Rapid Training Data Creation with Weak Supervision

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2016
Data Programming: Creating Large Datasets Quickly

Customer Stories
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February 26, 2022
Genentech used Snorkel Flow to extract information from clinical trials

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February 18, 2022
Google used Snorkel to build and adapt content classification models

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2019
Intel used Snorkel to accelerate sales and marketing agents

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2019
Apple built a Snorkel-based system to answer billions of queries in multiple languages

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Let’s connect

Speed time to value, reduce costs, and unlock more AI possibility with the Snorkel Flow platform.
Request a demo