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.


Featured on

ImageImageImageImageImageImage
Image

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.


Image

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.


Image
Image
Image
Image
Image
Image
Image
Image


Our investors


Image
Image
Image
Image
Image
Image
Image
Image
Image
Image

Dive in

[get_press_posts]
Press
Blog
Research
Case studies
Press
Image
November 17, 2022
Snorkel AI Accelerates Foundation Model Adoption with Data-centric AI


Image
November 17, 2022
AI startup Snorkel preps a new kind of expert for enterprise AI


Image
November 17, 2022
Snorkel dives into data labeling and foundation AI models


Image
July 28, 2022
Here’s why a gold rush of NLP startups is about to arrive


Blog
Image
November 17, 2022
Data-centric Foundation Model Development: Bridging the gap between foundation models and enterprise AI


Image
November 17, 2022
Better not bigger: How to get GPT-3 quality at 0.1% the cost


Image
November 3, 2022
Building an NLP application to analyze ESG factors in Earnings Calls using Snorkel Flow


Image
August 4, 2022
The Future of Data-Centric AI 2022 day 1 highlights


Research
Image
2022
Universalizing Weak Supervision


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


Image
2017
Rapid Training Data Creation with Weak Supervision


Image
2016
Data Programming: Creating Large Datasets Quickly


Customer Stories
Image
September 30, 2022
How Schlumberger uses Snorkel Flow to enhance proactive well management


Image
September 30, 2022
How a global custodial bank automated KYC verification with Snorkel Flow


Image
September 28, 2022
How Memorial Sloan Kettering Cancer Center used Snorkel Flow to scale clinical trial screening


Image
February 26, 2022
How Genentech extracted information for clinical trial analytics with Snorkel Flow


Image

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