The hyperautomation platform that transforms unstructured documents into actionable data with up to 99.5% accuracy.
Hyperscience is a market-leading Intelligent Document Processing (IDP) platform designed for large-scale enterprises and government agencies that handle massive volumes of unstructured data. By 2026, its technical architecture has evolved into the 'Hypercell' ecosystem, a modular suite that integrates proprietary machine learning models with advanced Human-in-the-Loop (HITL) capabilities. Unlike traditional OCR tools that rely on rigid templates, Hyperscience utilizes deep learning to interpret handwriting, skewed images, and low-resolution scans across varied layouts. Its competitive advantage lies in its 'Accuracy Threshold' system, which allows users to set specific precision levels; the AI processes high-confidence data automatically while routing low-confidence snippets to human operators for validation. This unique approach ensures nearly perfect data integrity for mission-critical workflows such as mortgage processing, insurance claims, and tax administration. The platform is built for high-throughput environments, offering scalable deployment via Kubernetes and seamless integration with legacy RPA and ERP systems, positioning it as a core infrastructure component for the autonomous enterprise.
Uses deep neural networks to extract cursive and block handwriting from non-templated forms.
AI-powered platform for end-to-end document intelligence and business process orchestration.
Enterprise-grade Intelligent Document Processing (IDP) powered by Generative AI.
Enterprise-grade multimodal document intelligence and semantic extraction engine.
Automate unstructured data extraction with LLM-native Intelligent Document Processing.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A proprietary UI that presents only the low-confidence snippets to human reviewers rather than the whole document.
Ability to run full LLM and IDP stacks within air-gapped or private cloud environments.
Utilizes spatial embeddings to find fields (like 'Total Due') regardless of where they appear on a page.
Collects human corrections to automatically update the underlying ML models in the background.
Integrates external database lookups to cross-reference extracted data in real-time.
Predicts the difficulty of a document before processing to optimize resource allocation.
Handwritten claim forms from customers cause massive backlogs and manual entry errors.
Registry Updated:2/7/2026
Output structured JSON to the Guidewire insurance platform.
Loan packets often contain 300+ pages of mixed document types requiring categorization.
High volumes of diverse, paper-based applications for social services.