HyperScience, the machine learning startup tackling data entry, raises $30 million Series B

HyperScience, the machine learning company that turns human readable data into machine readable data, has today announced the close of a $30 million Series B funding round led by Stripes Group, with participation from existing investors FirstMark Capital and Felicis Ventures, as well as new investors Battery Ventures, Global Founders Capital, TD Ameritrade and QBE.

HyperScience launched out of stealth in 2016 with a suite of enterprise products focused on the healthcare, insurance, finance and government industries. The original products were HSForms (which handled data-entry by converting hand-written forms to digital), HSFreeForm (which did a similar function for hand-written emails or other non-form content) and HSEvaluate (which could parse through complex data on a form to help insurance companies approve or deny claims by pulling out all the relevant info).

Now, the company has combined all three of those products into a single product called HyperScience. The product is meant to help companies and organizations reduce their data-entry backlog and better serve their customers, saving money and resources.

The idea is that many of the forms we use in life or in the workplace are in an arbitrary format. My bank statements don’t look the same as your bank statements, and invoices from your company might look different than invoices from my company.

HyperScience is able to take those forms and pipe them into the system quickly and easily, without help from humans.

Instead of charging by seat, HyperScience charges by documents, as the mere use of HyperScience should mean that fewer humans are actually “using” the product.

The latest round brings HyperScience’s total funding to $50 million, and the company plans to use a good deal of that funding to grow the team.

“We have a product that works and a phenomenally good product market fit,” said CEO Peter Brodsky. “What will determine our success is our ability to build and scale the team.”

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