Hyland Intelligent Document Processing Software

Easily scales to meet growing user demands and document quantities across departments, business divisions, and locations.

A flexible design can adapt to different document formats, types, and evolving business needs.

Facilitating end-to-end automation at scale by making integration with current systems and procedures easier.

Extensible through APIs and low-code tools, enabling personalized process configurations and modifications.

Intelligent character recognition (ICR) and advanced OCR are used to accurately identify handwritten and printed text.

Accurately recognizes watermarks, stamps, radio buttons, and checkboxes, minimizing data entry and human inspection.

Ensures accuracy in processing large volumes of documents by extracting structured data from intricate forms like tables.

Gen AI improves recognition accuracy and speed while gradually adjusting to different layouts and changing information kinds.

Eliminates the need for barcodes or separator sheets by automatically separating individual documents from scanned batches.

Intelligently uses AI models trained to identify layouts, content, and context to classify documents by type.

Accurately identifies and classifies pages into the right document categories, reducing the need for human sorting.

Automates the identifying, routing, and indexing of different document types at scale, which speeds up processing.

AI-driven methods to extract key data and metadata from organized, semi-structured, and unstructured texts.

Advanced field suggestions to find and extract relevant data with little assistance from the user.

Reduces errors by automatically comparing data collected to pre-determined formats and business standards.

Increases efficiency by rapidly obtaining important information from contracts, invoices, forms, and other sources.

Verifies the extracted data for structure, format, and accuracy against established guidelines and business logic.

Automatically detects anomalies and discrepancies, ensuring dependable downstream processing.

Allows for human-in-the-loop evaluation for sensitive or intricate data validation tasks that need human coordination.

Improves compliance by verifying content before it is added to important systems or processes.

Enhances data collected with contextual details to increase the accuracy of the downstream process and offer deeper insights.

Enables more intelligent decision-making and automation by using Gen AI to give unstructured content shape and meaning.

Connects extracted data to business context, enhancing document classification, routing, and retrieval.

Provides relevant tags, categories, and contextual signals to raw data to turn it into actionable intelligence.