HyperScience Raises $30 Million to Automate Enterprise Data Entry
Machine learning startup HyperScience raises $30 million in a Series B round to expand its automated data-entry platform. The company uses AI to convert arbitrary human-readable documents into machine-readable data without human intervention.
HyperScience secures $30 million in a Series B funding round led by Stripes Group to expand its machine learning platform that automates enterprise data entry. The round includes participation from existing investors FirstMark Capital and Felicis Ventures, alongside new investors such as Battery Ventures and TD Ameritrade. This latest investment brings the startup's total funding to $50 million.
The company consolidates its previous trio of products into a single unified platform called HyperScience. This AI-driven system processes arbitrary documents like bank statements and insurance claims, turning human-readable formats into structured machine-readable data. By handling these complex forms without human assistance, the technology helps organizations in healthcare, finance, and government reduce their data-entry backlogs and save valuable resources.
HyperScience utilizes a unique pricing model that charges by the document rather than by the user seat, reflecting the product's ability to operate independently of human workers. Chief Executive Peter Brodsky emphasizes that the company already enjoys strong product-market fit and plans to use the new capital primarily to build and scale its team to meet growing demand.