– An Enhanced Version of Newgen’s Intelligent Data Extraction Software Launched
Newgen Software, a global provider of low code digital automation platform, has launched OmniXtract 3.0, an enhanced version of its intelligent data extraction software.
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The latest version of the software leverages intelligent technologies to enable the accurate extraction of critical data from paper and digital documents and offers enhanced reporting and visualization capabilities. Additionally, it collects documents of various design layouts and formats from disparate sources for extraction.
“When digital has become the new normal, it is important to have an efficient solution for managing content. The enhanced version of our software will help organizations simplify the process of identifying and obtaining complex information from multiple data sources. Organizations can easily extract information from a large volume of documents across various business processes, enabling smarter decision-making, enhancing operational efficiency, and reducing errors,” said Diwakar Nigam, MD, and Chairman, Newgen Software.
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Key features of the new version include:
- Reports and Visualization: Offers contextual reports for real-time visualizations and to provide actionable insights across various stages of the extraction lifecycle
- Extraction Engine: Supports on-premise and cloud-based third-party extraction engines.
- Pre-configured Document Types: Offers pre-configured document types for common use cases, enabling quick implementations
- Extraction Analytics: Analyzes historical data for enhancing extraction performance
- Seamless Integration: Supports various application programming interfaces (APIs) for enabling seamless integration with various Newgen’s offerings
Newgen OmniXtract supports a wide array of extraction technologies, including guided intelligent character recognition, optical mark recognition, optical character recognition, barcode, and magnetic ink character recognition. Furthermore, it enhances accuracy through continuous learning from previously processed documents.
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