Datagen raises $50 million Series B to empower computer vision teams

Datagen raised a $50 million Series B round to boost the growth of its synthetic data solution for computer vision teams. Scale Venture Partners led the round, with partner Andy Vitus joining the board.

With offices in Tel Aviv and New York, Datagen is creating a complete CV stack that will propel advancements in artificial intelligence 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 according to the Palo Alto-based VC.

Datagen's Series A round of financing had investors in it. TLV Partners, Spider Capital, and Series A leader Viola Ventures are also included in this. Some of the high-profile individuals from the data field doubled down as well.

The list of investors could get longer according to the CEO of Datagen. Although the round closed a few weeks ago, the startup left with a few names still to be confirmed.

Datagen has built a self-serve platform that its target users demanded in their early feedback. Datagen can help clients generate the visual data that they need to train their computer vision applications.

Datagen's solution is used by computer vision teams and machine learning engineers inside a variety of organizations. It has a wide range of applications, but there are four that are faster than others.

In-cabin automotive is an example of what Datagen does. The passenger wearing a seatbelt is referred to as the term refers to what happens inside a car. The passengers and cars come in many different forms. Datagen's customers can use the initial real-life 3D motion capture to create a much larger quantity of data that they need to decide where to deploy the airbag.

Synthetic data uses real-world data to amplify it into the kind of data that needs more and more of, plentiful, and enriched to remove bias, cover edge cases, and more.

Datagen's focus is visual data, but it isn't tied to a sector in particular. It will only need to collect real-life data, such as motion capture from warehouses, if use cases in retail and robotics take off. The technology on top of this is domain-agnostic.

Scale is bullish about simulation data and invested in an automotive simulation platform. Synthetic data is taking over real data, he said.