Redefining Enterprise Automation

The Hyperscience Platform enables Global 2000s and government agencies to automate data-centric, mission-critical processes.

94% Automation
99.5% Accuracy
90% Cost Reduction

Outperform your competition (Because We Do.)

When organizations have access to accurate, complete data, customers receive better and faster service, and employees can turn their attention to a wider range of tasks that drive the business forward.

Faster Time-to-Automation
Create new layouts in less than 30 minutes with no IT costs. Scale to more use cases quickly.
Higher Accuracy
Extract more data with less manual intervention. Hyperscience has quality assurance built-in.
Dedicated Hypercare
Our dedicated Customer Experience team will guide you through your digital transformation journey.

Your data at the speed of Hyperscience.

Classify and extract data across complex, difficult-to-read documents, including 
handwritten forms, PDFs, images, emails and more. Our unique, proprietary ML reads through document imperfections to deliver results. It's "right first time" automation.


Minimize manual work, maximize human potential.

Decrease the costs of manual data entry, and free your employees
 to focus on higher-
level work. The Hyperscience UI for data keying makes humans more efficient and effectively and intelligently prioritizes Supervision keying tasks.

Accurate data, when and where you need it.

Complete, accurate data is the critical step zero of automating any business process. Extract machine-readable data to drive faster, more reliable downstream decision-making and business outcomes.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
"documents": [
        "id": 201373,
        "state": "complete",
        "layout_uuid": "30dca16c-99a2-49b1-9265-4f9b39f0be59",
        "document_fields": [
                "id": 11079100,
                "state": "complete",
                "name": "Phone Number:",
                "data_type": "Phone Number",
                "transcription": {
                    "raw": "123 456 7890",
                    "normalized": "1234567890",
                    "source": "machine_transcription",