Data-as-Code Co. Datagen Secures $50 Million in Series B Funding Led by Scale Venture Partners

Datagen, the data-as-code leader for computer vision artificial intelligence (AI), announced it has closed $50 million USD in Series B financing led by new investor Scale Venture Partners, with participation from existing investors TLV Partners, Viola Ventures and Spider Capital. Andy Vitus, partner at Scale VP, joins Datagen’s board of directors, effective immediately.

This latest round of funding brings Datagen’s total financing to over $70 million USD. The additional funds will help Datagen to continue to bolster its leadership position in the nascent computer vision (CV) space. As one of the fastest growing fields within AI, computer vision is becoming a fully-fledged, market-tested industry in need of a proper infrastructure stack to help supercharge the development of AI and its most imminent applications.

“As we enter a new, data-centric age of machine learning, a streamlined, operationalized data pipeline is poised to be the most lucrative piece of the machine learning puzzle,” said Andy Vitus, Partner at Scale Venture Partners. “This is why we are placing our bets on Datagen, which is creating a complete CV stack that will propel advancements in AI by simulating real world environments to rapidly train machine learning models at a fraction of the cost — this will fundamentally transform the way computer vision applications are developed and tested. The potential impact of what Datagen has to offer, across a broad range of applications, is staggering.”

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DGU Is the New Data Compute Unit

A key element of Datagen’s success is its unique focus on CV teams. By providing a self-service platform for CV teams, Datagen makes it easy for those responsible for developing and testing AI products to obtain and use synthetic data. Datagen’s unique offering makes it easy for CV engineers to engage and adopt synthetic data by running Data Generation Units (DGUs) by the hour to produce the data their AI needs. For the first time, buying synthetic data is as easy as buying cloud computing resources.

The proof of Datagen’s success is confirmed by its spectacular 8X growth in total revenue, driven in part by lighthouse accounts that include three of the top five global tech giants, who are using Datagen to bring their AI products and solutions to market.

“The need for robust, high-variance and high-performance training data will continue to grow exponentially as computer vision algorithms and their applications become more numerous and diverse,” said Datagen Co-founder and CEO Ofir Zuk (Chakon). “Our mission is to enable every CV team with the best synthetic data solution to power the development of their AI applications. That’s why we are honored to welcome Scale VP to the community of our marquee investors. With today’s new funding, we are poised to accelerate growth and take the market by storm.”

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Building the Infrastructure for Computer Vision

According to a recent industry survey commissioned by Datagen, a stunning 99% of computer vision teams reported having had a machine learning project completely canceled due to insufficient training data. So it’s no surprise that synthetic data is gaining such widespread adoption, with 96% of computer vision teams reporting using synthetic data in some proportion to train computer vision models. Gartner recently placed synthetic data at the top of its list of strategic predictions for 2022 and beyond, saying that “by 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated.”

Datagen was founded in 2018 by computer vision experts Ofir Zuk (Chakon) and Gil Elbaz with a mission to reinvent how AI/ML teams gather data needed for computer vision network training. The company’s unique simulated data (a form of synthetic data) technology obviates the need for producing or sourcing scant 2D and 3D training data for computer vision AI development.

Today, Datagen is defining a new data-as-code category that will serve as the next big frontier following the model- and data-centric approaches to computer vision AI development. By removing the need to source and manually annotate training data, some of its most time-consuming and resource-intensive steps, Datagen is helping CV teams get to market faster with applications in augmented reality, smart offices, automotive in-cabin monitoring, home security, and more.

New Industry Forum

As part of today’s announcement, Datagen is launching a Visual Synthetic Data Forum, a new industry forum that will convene quarterly and focus on topics related to data for computer vision AI development. Under Datagen’s leadership, it will aim to create a strong networking group focused on the advancement of synthetic data development by bringing esteemed leaders from academia and the industry to help shape and accelerate future AI applications and use cases built on computer generated synthetic data.

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