Hyperscience

What is Hyperscience?

Founders & Launch

• Founded in 2014

• Founded by Peter Brodsky, Krasimir Marinov, and Vladimir Tzankov

• Headquarters in New York, with a global presence

Use Cases

• Banking and financial services automation

• Insurance claims processing and underwriting

• Government form digitization and public service workflows

• Healthcare data extraction and clinical record automation

• Legal, compliance, and policy document automation

Technology

• Machine learning-based intelligent document processing

• Human-in-the-loop validation for continuous accuracy

• Modular Blocks & Flows architecture

• API-based integration with enterprise systems

• Secure on-premises, cloud, and hybrid deployment options

Hyperscience is an AI-powered AI Agent platform that enables organizations to automate the processing of complex unstructured documents at scale. Machine learning, combined with human-in-the-loop automation, means that critical data can be extracted with very high accuracy. Enterprises and agencies in the public sector design it to reduce manual effort, speed up decision-making, and improve compliance. The platform works exceptionally well for documents such as forms and handwritten records or legacy types of paperwork that traditional OCR finds difficult to process. Automation combined with learning helps Hyperscience assist teams in handling a large number of documents while ensuring data quality, security, and clear operations throughout the workflows.

Key Features

Hyperscience key features are

• Advanced Document Understanding: Accurately processes structured, semi-structured, and unstructured documents, including handwritten text and low-quality scans.

• Human-in-the-Loop Automation: Human reviews and corrections enable extra accuracy in output while enabling continuous improvements in the training of the AI models.

• High Accuracy Data Extraction: Self-learning models adapt to new document types and layouts to reduce errors.

• Enterprise-Grade Scalability: Provides consistent performance across large organizations while processing millions of documents.

• Workflow Integration: Effortless integration with other enterprise systems, e.g., RPA tools, BPM engines, and data management solutions.

• Security and Compliance: Rigorously maintain data governance, audit trails, and compliance support for regulated environments.

Pricing

• Hyperscience follows a custom, enterprise-level pricing model rather than fixed public plans.

• Pricing typically starts around $50,000 per year for the basic or Essentials package, depending on deployment and usage.

• Advanced and Premium plans are priced on request and vary based on document volume, features, and integrations.

• The platform uses a license-based or document-processing volume model, which impacts total cost.

• Implementation and onboarding fees are usually charged separately and can range from tens of thousands of dollars based on complexity.

• Additional costs may apply for higher document volumes, advanced automation, or custom workflows.

Disclaimer: For the latest and most accurate pricing information, please visit the official Hyperscience website.

Who Is Using Hyperscience?

A diverse range of users and organizations utilize Hyperscience

• Government agencies

• Financial services organizations

• Insurance companies

• Healthcare enterprises

• Large enterprises with document-heavy operations

Alternatives

Some Hyperscience alternatives are

• ABBYY FlexiCapture

• UiPath Document Understanding

• Rossum

• Kofax

• Automation Anywhere IQ Bot

Conclusion

Hyperscience makes a real mark as an AI-based document automation platform for organizations operating in a field of challenging document types. The unique combination of machine learning, human validation, and enterprise scalability makes it suitable for environments where volume is high and accuracy is critical. Hyperscience increases the speed, intelligence, and efficiency of its clients by decreasing manual processing and increasing the trustworthiness of data.

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