About us

Our mission is to empower everyone to solve their most impactful problems through data-centric AI. To do this, we have introduced Snorkel Flow, a data-centric AI platform, and are building an incredibly talented team. We empower Fortune 500 enterprises such as Chubb and BNY Mellon, and several government agencies to accelerate AI application development by 10-100x.


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Rooted in research

Snorkel AI started as a research project in the Stanford AI Lab in 2015, where Alex Ratner, Chris Re, Paroma Varma, Braden Hancock, and Henry Ehrenberg set out to explore training data programming, a new interface layer for machine learning. The founding team spent over half a decade researching programmatic labeling, weak supervision, and other techniques to break through one of the biggest bottlenecks in AI: the lack of labeled training data. This research has resulted in the Snorkel research project and 60+ peer-reviewed publications. Snorkel has developed and deployed its technology with Google, Intel, DARPA, Stanford Medicine, and more.


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Culture

Snorkel AI strives to create a culture that welcomes, represents, and gives opportunity to all. We’re building a unique team that’s equal parts ambitious and supportive. We're as dedicated to communication and helping each other as we are to our craft and product. We cultivate autonomy across the entire team by being open about our goals, wins, and challenges. We get to answers fast, focusing on what works—not what’s fancy.

In our field of AI and software engineering, we believe that diverse thinkers increase collective insights and knowledge. Our journey has just started. We’re committed to an inclusive team fostering cognitive diversity to build products that resonate with all users.


Our investors


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Dive in

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Press
Blog
Research
Case studies
Press
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March 21, 2022
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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Are you ready to dive in?

Label data programmatically, train models efficiently, improve performance iteratively, and deploy applications rapidly—all in one platform.
Request a demo