Content Discovery

Discover the gems in your content archives

Large organizations are uniformly suffering from information overload, both internally and externally. The downside to the digital era is that incredible amounts of unstructured data are created daily. The upside is that each content can also contain value.

By semantically mining internal content and applying understanding and intelligence to it, Nstein helps minimize corporate waste and truly begin to understand the secondary purposes (and value) inherent to content.

Nstein allows large organizations to mine their content for meaning, and categorize it against industry-specific taxonomies. This now structured data can be easily grouped by topic, and retrieved. Whether to help research a particular field of interest, create thematic microsites, or leverage custom publishing opportunities, having this macro view of content unlocks opportunities to maximize the ROI of content, whether through the development of new products and the acceleration of research cycles, and increase productivity as content search is rendered so trivial.

Leveraging Nstein’s DAM and TME products, Reader’s Digest was able to ingest an XML representation of content in a central repository, semantically tag it and properly categorize it. Reader’s Digest now has access to its content in all its depth no matter where a particular piece of content might reside, nor what format it is in. Doing so, the media giant is now able to create new products on the fly with minimum effort on the part of its staff, and find new revenue streams for its existing content assets.

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