BatchOCR in Greenbooks Imaging Services automates large-scale text extraction from scanned documents and images. It efficiently converts bulk files into searchable, editable formats using advanced OCR technology. Integrated with Greenbooks’ DMS, it ensures faster processing, accurate indexing, and seamless digital transformation for enterprises handling high document volumes.
Batch processing is a fundamental capability of Docuventa's OCR solution that enables automated conversion of large document volumes simultaneously. BatchOCR software allows for the conversion of multiple files at once through a hot folder or watched folder method that converts any files added to a particular folder on a preset schedule.
Docuventa's batch processing engine can handle thousands of documents daily, automatically sorting, indexing, and converting them into searchable PDFs without manual intervention. This functionality significantly reduces processing time and operational costs while maintaining consistent quality standards. The system operates in the background, allowing users to continue working while documents are being processed.
Organizations can configure automated workflows where scanned documents are automatically routed through OCR processing, classified by document type, indexed with metadata, and stored in appropriate digital repositories, creating a seamless end-to-end document digitization pipeline.
Go to BatchOCR FeaturesDocuventa leverages Tesseract, a powerful open-source OCR engine, to deliver comprehensive multilingual support in its BatchOCR system. Tesseract can recognize more than 100 languages, making it an ideal choice for organizations handling diverse document collections.
Docuventa's standalone Image-to-Multilingual Text-Searchable PDF Converter utilizes Tesseract's robust language recognition capabilities to automatically detect and process documents in various scripts including Latin, Cyrillic, Arabic, Devanagari, Chinese, Japanese, and Korean. This Tesseract-powered solution enables businesses to digitize multilingual archives without requiring separate processing workflows for each language. The engine's machine learning algorithms ensure high accuracy across different fonts, layouts, and document types.
By integrating Tesseract into Docuventa's BatchOCR workflow, organizations can create fully searchable digital repositories where users can retrieve documents regardless of language, enhancing accessibility and efficiency across global operations while maintaining consistent quality standards.
Go to BatchOCR FeaturesSplit PDF is a crucial feature in Docuventa's document management system that enables intelligent separation of multi-page PDF files into individual documents or logical sections. BatchOCR can automatically process heterogeneous scanned material by splitting entire scanned batches into individual documents, even when documents have different page counts.
Docuventa's split PDF capability uses advanced algorithms to identify document boundaries through barcode recognition, blank page detection, or custom separation rules. For instance, a single scanned batch containing a five-page invoice, three-page delivery note, and ten-page contract can be automatically separated into three distinct files. This functionality is essential for organizations that scan documents in bulk, eliminating tedious manual splitting tasks. Users can define splitting criteria based on page numbers, content patterns, or visual markers.
The split documents are then automatically indexed, classified, and routed to appropriate folders within Docuventa's repository, streamlining document organization and retrieval workflows while maintaining document integrity.
Go to BatchOCR Features
