Hyperscience vs. Legacy Document Processing

Human-centered automation goes beyond traditional automation. By combining human decision making with machine learning, Hyperscience seeks to improve outcomes for businesses, clients, and the world.

Turn document content into better business decisions. Classify and extract printed and/or handwritten text from any document—structured or unstructured.

The results of a human centered approach speak for themselves. See how we compare with some of the main legacy process document software according to G2 Comparison table.

Hyperscience’s Human-in-the-loop (HITL) process provides flexible and transparent automation that prioritizes optimizing business outcomes.

Accuracy takes precedence for HITL automation. To ensure the highest accuracy, ML models can recognize their own uncertainty and seek out human input only when needed.

ML models augmented with human input can be more easily explained and understood, promoting trust and transparency—particularly valuable in industries such as healthcare and finance.

Legacy providers neglect business impact, favoring vanity metrics such as straight-through processing instead. With human-in-the-loop automation, the entire document handling process is made more efficient.

Where OCR and RPA struggle to process handwriting and can’t process data outside of fields, Hyperscience can process structured and unstructured data, and boasts the highest accuracy in the industry for handwriting.

Pre-trained ML data types and a point-and-click interface helps users train machine learning models—making organizations more efficient and employees more valuable.

Whereas legacy solutions require weeks (or months!) of development work to implement new use cases, machine learning allows new use cases to be rolled out in a matter of days.