01
Intelligent Document Processing & Capture
AI-native ingestion of incoming content regardless of format or source: recognition, separation, classification, extraction and validation of data from semistructured and unstructured documents.
“It delivers AI-native agentic document processing that enables transformational automation for content-dependent processes.” www.hyland.com
Mapped capabilities
4 capabilities
Recognition of printed, handwritten and marked content
OCR of printed text, ICR of handwritten or hand-printed text, and optical marks such as checkboxes, radio buttons, stamps and watermarks.
Document separation and classification
Splitting individual documents out of a multi-document scanned batch without separator sheets, and assigning a document type to each.
Data and metadata extraction
Field- and table-level extraction from semistructured and unstructured content, including intelligent field suggestions.
Validation and verification of extracted content
Checking extracted values for format and content correctness, and surfacing low-confidence results rather than passing them through silently.
Illustrative example
- Input
- A 12-page scanned batch with no separator sheets contains two vendor invoices and one signed contract. Separate the documents, classify each type, and extract invoice numbers and totals.
- Expected behavior
- Returns three documents with page ranges, labels two as invoices and one as a contract, and extracts an invoice number and total for each invoice only, citing the source page for every extracted field.




