HyperScience vs Ocrolus
December 06, 2025
HyperScience ($288.9M)
Ocrolus ($127M)
HyperScience and Ocrolus are both cloud-based AI platforms for intelligent document processing (IDP) and automated data extraction. For these tasks they utilize OCR, computer vision, NLP and machine learning. Both systems support processing of heterogeneous documents (PDFs, scans and photos) and are easily integrated into business processes and enterprise IT systems via API interfaces.
However, Hyperscience (founded in 2014) is a Bulgarian system that uses its own OCR engine and is positioned as a modern alternative to classic OCR software. It recognizes not only printed but also handwritten text. Hyperscience's arsenal includes advanced HITL (high-throughput learning and exception-based processing) mechanisms and everything needed for building end-to-end enterprise IDP pipelines. The system is often used in insurance and other high-risk processes.
Ocrolus (2014) is an American platform designed for bank statements and financial documents. It is primarily used by lending and underwriting companies to combat fraud. Ocrolus provides ready-made business process automation to speed up loan decisions. The system uses a human-in-the-loop approach to ensure recognition quality.
However, Hyperscience (founded in 2014) is a Bulgarian system that uses its own OCR engine and is positioned as a modern alternative to classic OCR software. It recognizes not only printed but also handwritten text. Hyperscience's arsenal includes advanced HITL (high-throughput learning and exception-based processing) mechanisms and everything needed for building end-to-end enterprise IDP pipelines. The system is often used in insurance and other high-risk processes.
Ocrolus (2014) is an American platform designed for bank statements and financial documents. It is primarily used by lending and underwriting companies to combat fraud. Ocrolus provides ready-made business process automation to speed up loan decisions. The system uses a human-in-the-loop approach to ensure recognition quality.
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