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Hyland IDP uses large language models (LLMs) with generative AI (gen AI) to power document processing and simplify automation design and configuration.
Intuitive configuration
Gen AI prompt-based design with dynamic suggestions, prebuilt templates, low-code configuration and automatic business process model and notation (BPMN)-compliant process generation accelerates time to value.
Highly scalable, flexible and extensible
Hyland IDP scales to handle high volumes of documents and easily integrates with your enterprise applications and processes, making it easy to deploy in multiple use cases across your organization.
AI-powered recognition
Hyland IDP leverages gen AI-powered character recognition of content in the document. It can recognize printed text (optical character recognition), handwritten and hand-printed text (intelligent character recognition), optical marks such as checkboxes, radio buttons, stamps, watermarks, and even data in table format.
Document separation and classification
Hyland IDP intelligently distinguishes between document types and automatically separates individual documents from a set of scanned pages without relying on separators.
Data extraction
AI-powered extraction of data and metadata from semistructured and unstructured content with intelligent field suggestions.
Data validation
Validation and verification of the extracted content, format and structure of the processed documents with available human-in-the-loop verification options.
Data enrichment
Using gen AI, extracted content is enriched with contextually relevant insights and metadata to enable not just recognition but understanding.