Document Navigator, Konica Minolta’s document management solution, is taking a significant leap forward with the integration of four new AI-powered modules. Leveraging Azure Micro Services and the latest advancements in artificial intelligence, these modules will empower businesses to optimize their document processing workflows, boosting efficiency and productivity.
The new modules—Smart ICR, Smart Document, Smart Translation, and Smart Form—offer powerful automation capabilities, allowing businesses to extract data, classify documents, summarize content, translate text, and recognize personally identifiable information (PII) with precision and ease. These enhancements are designed to streamline document management, reduce manual effort, and improve accuracy in handling critical business documents.
Smart ICR: Data extraction and document classification
Smart ICR, or Intelligent Character Recognition, automatically extracts data and classifies incoming documents based on content and assigns a category. It recognizes handwritten notes, such as annotations on invoices, and creates keyword lists to enhance document retrieval and management.
Smart Document: Document summarization and personally identifiable information (PII) recognition
Smart Document generates concise document summaries in both sentence and bullet-point formats. It also identifies and redacts personally identifiable information such as phone numbers, email addresses, and other sensitive data.
Smart Translation
Smart Translation detects the source language and translates documents into over 100 languages and dialects. It supports more than 20 document formats, including Adobe PDF, Microsoft 365, OpenDocument, Rich Text and more.
Smart Form
Smart Form automates the processing of invoices, receipts, business cards, IDs, HR forms, contracts, and other business documents. Using AI-driven Optical Character Recognition (OCR) and Intelligent Character Recognition (ICR), it extracts text from typed and handwritten fields. This module enables intelligent document recognition and data extraction without relying on fixed templates.
