OpenText has launched a new offering to enable large organisations to ensure records management policy is applied automatically across the huge volumes of documentation that businesses generate every day.
The new tool, OpenText Auto-Classification, is the first automated classification application with built-in transparency and defensibility that enables organisations manage the retention and disposition of high-volume, low-touch content such as social media, email, office documents and legacy content, to reduce legal risk and eDiscovery costs.
The technology enables organisations, for the first time, to apply document classification, use, retention, protection, retrieval and disposal policies to all corporate content, said the company.
OpenText chief marketing officer James Latham said they now have the industry’s first machine-assisted classification with built-in statistical sampling and quality assurance to ensure that auto-classification is both transparent and defensible.
OpenText Auto-Classification provides consistent, defensible classification of content without end-user intervention after the system has been set up, and codifies language specific nuances identified by teams of linguistics experts to dramatically improve accuracy.
It uses the OpenText Content Analytics engine to "read" through each document, email or social media posting to classify content according to corporate policy and legal requirements, said the company.
Open Text Auto-Classification includes workbenches for identifying exemplar documents and rules, testing and refining effectiveness and quality assurance and sampling against a broader set of documents on an ongoing basis.
OpenText Auto-Classification was developed in close partnership with customers using the OpenText ECM Suite, and works in conjunction with OpenText Records Management so that existing classifications and classified documents can be used in the tuning process.
