Ez-XBRL Solutions Announces Ez-XBRL Version 6
Advanced automation for detailed footnotes using natural language processing and machine learning algorithms
MANASSAS, VA – JUNE 29, 2012: Ez-XBRL Solutions, Inc., a global software and solutions provider of XBRL data conversion and analytics platforms, today released the latest enhanced version 6.0 of its flagship product, Ez-XBRL.
Ez-XBRL 6.0 incorporates advanced, patent-pending technologies using Natural Language Processing and Machine Learning to significantly enhance the automation of XBRL tag selections. The new features greatly reduce the time taken to complete XBRL detailed footnote filings. Also included are major enhancements to the user interface to streamline workflow, add ease-of-use features and simplify the process of creating, reviewing and validating XBRL files. In addition to automated, predictive XBRL concept recommendations, Ez-XBRL’s new technology also provides recommendations for complex constructs such as XBRL dimensions and members.
A variety of other built-in tools enable users to take full advantage of powerful search capabilities, tag filtering, tag comparisons, and tag reviews to help users make decisions for creation of taxonomy extensions through reviews of peer company filings. Machine learning capabilities continually provide feedback to the underlying model to improve accuracy of results. A sophisticated spreadsheet output facilitates offline review and editing of mappings. This effective and elegant output aids the review process through color-coded highlighting while maintaining the look-and-feel of the SEC’s rendered output.
“Our new technologies enable more users to create SEC-compliant XBRL filings without requiring vast XBRL knowledge,” said Ms. Aneet Kumar, President of Ez-XBRL Solutions, Inc. “Ez-XBRL greatly reduces the need for external reporting teams to be XBRL experts and significantly reduces the time required to complete challenging tasks such as detailed footnotes mapping and tagging.”