Data Labeling Unicorn Snorkel AI Raises $85M, Plans to Hire Across Departments

August 9, 2021
Snorkel’s software is used to speed up machine learning processes at big name tech companies like Apple and Google. Moving forward, the data labeling platform will focus on expanding its engineering and marketing teams.
Image: snorkel ai

Palo Alto-based data labeling platform Snorkel AI announced Monday that it raised $85 million in a Series C round led by Addition. The latest raise solidifies the company’s status as a unicorn with a valuation of $1 billion. 

Snorkel’s software is used to speed up machine learning processes at major tech companies like Apple and Google. 

But how does it work? Typically, in order to train an AI model, the AI must first study a training dataset. A training dataset contains “question and answer” pairs that an AI then studies in order to develop answers of its own. 

For example, in order to build an AI model that sorts books by genre, a company would need a training dataset where the books that operate as the “question” and the “answers” are an assortment of genres. These “answers” are also referred to as tags. 

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Clearly, tech companies are dealing with datasets that are much more complicated, and the process of acquiring data to train an AI can oftentimes be a long and laborious process. 

Snorkel AI’s solution automates this process. The platform removes the need for manual work by providing developers with the chance to write code scripts that automatically perform data tagging. 

“Today, an increasing number of organizations see that data is the arbiter of their AI success or failure, as well as their risk, governance, and privacy compliance, fairness and equitability, and agility,” Alex Ratner, co-founder and CEO of Snorkel AI, said in a statement. “As data moves to the forefront, so too does the pain of labeling and managing it all by hand.” 

Snorkel will use the fresh injection of capital to build out its go-to-market and customer success infrastructure as well as accelerate its AI research. 

“The shift from model-centric to data-centric development is transforming the landscape of AI, and making it clear that the legacy approach of manually labeling and managing data is simply not a feasible path forward,” Ratner continued. 

Snorkel AI plans to continue growing its team in order to account for its rapid pace of growth. Dozens of remote-based tech roles are currently up for grabs across departments. Moving forward, the data labeling platform will focus on expanding its engineering and marketing teams. 

Snorkel AI has raised $135.3 million in venture capital financing to date, according to Crunchbase

Additional investors Greylock, GV and Lightspeed Venture Partners participated in the round, among others.

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