Hyperscience
Enterprise AI infrastructure software for Intelligent Document Processing (IDP).
Data Extraction Accuracy
Up to 99.5%
Last Funding Round
$100M (Series E)
Company Size
201-500 employees
About Hyperscience
Hyperscience provides an AI-powered platform designed to automate and orchestrate complex, document-heavy business processes. Its core focus is Intelligent Document Processing (IDP), which uses proprietary machine learning to classify documents and extract data from diverse and unstructured formats, achieving up to 99.5% accuracy. The platform is built for large enterprises in regulated industries like financial services, insurance, and government. By creating 'digital assembly lines,' Hyperscience turns manual processes into configurable, automated workflows, involving human operators only for exceptions. This helps organizations improve efficiency, reduce operational costs, and leverage their back-office data for strategic advantage.
Platform Capabilities
Intelligent Document Processing
Automates data extraction from structured and unstructured documents, including handwritten text.
Digital Assembly Lines
Turns complex processes into simple, configurable workflows that combine data, people, and processes.
Human-In-The-Loop
Engages human operators for verification and exceptions through an intuitive user interface.
Flows Sdk
A Python library for programmatically building and managing custom business process flows.
Use Cases
Claims Processing
Automates the intake and processing of insurance and healthcare claims.
Client Onboarding
Streamlines new customer and account opening processes in financial services.
Invoice & Receipt Processing
Automates accounts payable by extracting data from invoices and receipts.
Public Sector
Supports government agencies in processing forms and applications, like tax and benefits administration.
Company Information
Headquarters
New York, NY, USA
Key Investors
Bessemer Venture Partners, Tiger Global, Stripes, FirstMark Capital, Battery Ventures
Notable Customers
American Express, Charles Schwab, Mars, Stryker, U.S. Social Security Administration