NEW YORK, March 29, 2019 — HyperScience, the machine learning company that turns human readable documents into machine readable data, has been recognized as a Major Contender in the 2019 Everest Group Intelligent Document Processing (IDP) Products PEAK Matrix™.
This year’s IDP PEAK Matrix, the first of its kind, reflects the growing interest from companies to automate their operations and a dawning realization that document processing is often a crucial step in these workflows.
Participant evaluations were based on a comprehensive set of multiple evaluation criteria, including: vision and strategy, product capability, monitoring and improvement, implementation & support, commercial model, market success, portfolio mix, and value delivered. As part of the evaluation process, Everest Group also conducted customer references and saw in-depth product demos.
“HyperScience has emerged as a Major Contender in Everest Group’s PEAK Matrix for IDP software products in 2019. Its IDP solution leverages proprietary machine learning algorithms to process hand-filled forms, images, and printed documents,” commented Anil Vijayan, Practice Director at Everest Group. “In addition to business-user friendly features such as a set-up console to configure use cases, a visual tool to adjust accuracy thresholds, and comprehensive dashboards, its flexibility to align product features and a roadmap with evolving customer requirements have contributed to its success.”
“Everest Group is a highly respected research firm and HyperScience being acknowledged as a Major Contender is a testament to the distinctive product that we’ve built.” said Peter Brodsky, the CEO of HyperScience. “The product came out of Beta at the start of 2018 and has achieved higher client satisfaction than other Major Contenders and Leaders. We are looking forward to delivering our ambitious roadmap, providing more value to our customers, and emerging as a leader in the space.”
Learn more about how HyperScience is tackling data extraction by downloading the full report here.Back to Articles