Pingar
Pingar solves problems faced by organizations that have large amounts of unstructured data. It is re
14/07/2017
Digital transformation research shows NZ businesses must up their digital game.
Read more here: https://blogs.business.microsoft.com/en-nz/2017/04/18/digital-transformation-research-shows-nz-businesses-must-up-digital-game/
07/06/2017
Do you know what is the difference between Findability and Discoverability?
Read more here: http://pingar.com/discoverability/
08/05/2017
One of the typical attributes of legacy documents is uncertainty. As it is exceptionally costly to review the documents, companies enable automatic tagging solutions to identify the documents that should be deleted or should be archived. It makes document migration notably faster and cleaner. DiscoveryOne easily analyzes documents in different languages and categorizes them according to the evolving requirements of agile businesses.
Read more here: http://pingar.com/automatic-classification-categorization/
11/04/2017
Automatic Metadata for Effective Data Migration.
Pingar enables organizations to evaluate enterprise-wide information quickly, thoroughly and efficiently, regardless of how information has previously been stored. Pingar enriches compliance practices while decreasing manual effort and increasing accuracy, improving productivity and saving money.
read more here: http://pingar.com/data-migration/
30/03/2017
Many content management system users complain about poor search experience. Do you know what it takes to ensure a good user experience?
Learn more: http://pingar.com/enterprise-search/
28/03/2017
Critical information is easily lost or leaked due to insufficient document tagging. DiscoveryOne recognizes documents that contain sensitive data, such as personal identifiable information, confidential records, financial details, etc. Therefore, DiscoveryOne enables automatic classification and categorization of your documents.
For more information click here: http://pingar.com/automatic-classification-categorization/
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20/12/2017