AI data labelling startup SuperAnnotate raises $3 million seed from Point Nine Capital


SuperAnnotate, an AI-driven annotation platform for data scientists and machine learning teams, has raised $3 million in a seed round led by Berlin’s Point Nine Capital. Runa Capital and Fathom Capital also joined the investment, as well as previous investors Berkeley SkyDeck Fund and Plug and Play Ventures. 

Though the company is based in California, the two founders are from Armenia and each came to Europe for their PhDs, Tigran Petrosyan to ETH Zurich and Vahan Petrosyan to the KTH Royal Institute of Technology in Sweden. The algorithms developed during Vahan’s studies became the basis of SuperAnnotate’s data annotation platform.  

Labeled data is key to advances in self-driving cars, retail, healthcare and other industries, but it’s extremely tedious. In a press release, the startup says data preparation and engineering tasks consume over 80 percent of the time spent in most AI and ML projects, adding that the market for data annotation tools is expected to reach $2.57 billion by 2027.

SuperAnnotate is an end-to-end platform for image annotation, providing a toolkit for manual labeling, a simple communication system, recognition improvement, image status tracking, templates, dashboards and other tools. 

Coming from academia and seeing the pains of labeling first-hand, we work overtime to make sure our users have the right tools and are connected with the right teams to successfully complete their computer vision projects with the highest detection accuracies,” explains Tigran, the startup’s CEO.

Launched this February, the AI company has already attracted more than 3,000 data scientists and over 100 companies. “Having launched publicly only three months ago, we were very overwhelmed by such a high level of organic adoption of our platform from thousands of ML engineers and large annotation teams,” Tigran added.

Louis Coppey, a principal at Point Nine, says the firm was “impressed by Vahan and Tigran’s deep understanding of data scientists’ pain points and by their ability to assemble such a cutting edge team of ML researchers to automate some of the most tedious yet necessary annotation tasks required of building cutting edge software.”

Photo: Tigran Petrosyan (CEO) and Vahan Petrosyan

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