CLASSIFICATION
AI-Powered Automatic Document Classification Software
Minimize or Eliminate Manual Document Pre-Sorting
CAPSYS provides AI-powered automatic document classification as part of its Intelligent Document Processing (IDP) capabilities. Using CAPSYS AcuityAI™ and CAPSYS CAPTURE™ or CAPSYS CAPTURE ONLINE™, organizations can automatically identify, classify, separate, and route incoming documents based on their content and context—reducing or eliminating manual document pre-sorting.
CAPSYS classification technology can process invoices, checks, forms, orders, delivery documents, correspondence, page separators, and other structured, semi-structured, and unstructured business documents. Once identified, documents can be automatically routed to the appropriate capture workflow, business process, content repository, or enterprise application.
CAPSYS CAPTURE ADC™ (CCADC) provides established document recognition and classification capabilities within the CAPSYS CAPTURE platform. CCADC supports content-based document categorization and can be incorporated into scanning, indexing, archiving, sorting, search, ECM, line-of-business, and proprietary information management workflows.
By combining intelligent classification with enterprise document capture and workflow automation, CAPSYS helps organizations reduce document preparation, minimize manual intervention, improve processing accuracy, and accelerate document-driven business processes.
Advanced AI-Powered Document Classification with CAPSYS AcuityAI™
For complex documents that require classification based on meaning and context—not simply keywords, layouts, or image similarity—CAPSYS AcuityAI™ provides advanced AI-powered document understanding and classification.
Using generative AI, large language models (LLMs), and fine-tuned models, CAPSYS AcuityAI™ can classify structured, semi-structured, and unstructured documents as part of an Intelligent Document Processing (IDP) workflow.
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CAPSYS AcuityAI™
to learn how AI-powered document classification, data extraction, and validation can automate complex document-intensive business processes.
CCADC Text and Image-Based Document Classification.
Not every document classification requirement requires advanced AI. For predictable document types, consistent layouts, identifiable keywords, or well-defined document classes, traditional text- and image-based classification can provide an efficient and highly effective approach.
CAPSYS CAPTURE ADC™ (CCADC) complements CAPSYS AcuityAI™ by providing configurable text- and image-based document classification for use cases where advanced contextual AI may not be necessary. This gives organizations the flexibility to apply the appropriate classification technology based on document complexity, business requirements, and desired confidence levels.
Text-Based Classification
Text-based classification identifies documents by detecting defined keywords, phrases, or other textual content. Classification rules can require exact matches or use configurable confidence thresholds to determine the appropriate document type or class. This approach is particularly effective when documents contain identifiable text—such as company names, form titles, document identifiers, or other distinguishing information—that can reliably determine document type.
Image-Based Classification
Image-based classification compares incoming documents against representative sample images associated with known document types or classes. Multiple samples can be assigned to the same class to accommodate variations in document appearance and improve classification confidence.
For example, similar invoice formats—with or without VAT information or other layout variations—can be associated with the same document class. Incoming documents are compared against the library of known samples and automatically assigned to the most appropriate document type based on the resulting confidence level.
New document variations can be incorporated into the classification library over time, helping CCADC accommodate changing document formats and improve recognition performance.
