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StartUps Raises $4M for Data Tech Platform in action

Israeli startup offers a labeling platform for AI. The company has raised $4 million in Seed funding from a group of investors, one of which is Wix’s former Head of AI, Professor Shai Dekel.

The company boasts its platform helps data scientists break down the scenery of an image or video as much as 30 times faster than its competitors and provides a nearly unlimited supply of data identifiers – known as ‘Tasqers’ – to help reduce biases compared to ‘trained’ business process outsourcing.

This helps with just about anything and everything having to do with images posted online, from SEO to categorizing images under every conceivable label for a firm’s database. So, let’s say one picture is of a child on a swing. You can label it as such and so it will only show up under searches for child and swing. But what about “happy,” “playground” “smile” “sky” “grass,” etc. And then there are all of those fancy high tech terms that are used to delineate the image’s type and metadata and so forth.

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So, this is where comes into the picture. was founded in 2019 by CRO Nathan Catalan, CTO Yossi Motro and CEO Erez Moscovich. The company’s platform is already partnered with several ad networks and helps clients, such as Intel, build better AI faster. It is based in Tel Aviv, Israel, with field headquarters for sales and business development in New York and Chicago.

The platform is a Visual Data Platform empowering Data Science and ML teams to create training datasets for AI developments.

Data science is defined as an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data that is called noisy, structured or unstructured data. Noisy data are data that is corrupted or distorted. Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Data Science applies knowledge and actionable insights from data across a broad range of application domains to manage this problem.

Oracle explains that data science encompasses preparing data for analysis, including cleansing, aggregating, and manipulating the data to perform advanced data analysis. Analytic applications and data scientists can then review the results to uncover patterns and enable business leaders to draw informed insights. Co-founder and CEO Erez Moscovich said, “We’re bringing the usage model that Amazon pioneered for cloud storage to data annotation for AI. It’s going to completely upend the way AI is built and eliminate the data bottlenecks that are slowing progress. This round of funding paired with our existing revenue will allow us to more rapidly expand adoption, build out our R&D here in Israel, and solidify our presence in the U.S with offices in New York and Chicago.”

“Everyone knows that AI capabilities are a must-have, but only those of us who have built AI companies and products understand the extent of the massive data annotation bottleneck issue that is the first to solve,” added investor Professor Shai Dekel. “They’re alone at the forefront of the data annotation field and that’s a tremendous achievement and advantage, not to mention a big leap forward for the development of AI.’s success means expanding access to the ability to quickly build great AI and more effective applications that will be a boon to businesses and users alike.”



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