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RWS and WAND, Announce New Partnership

WAND Taxonomies Now Working Hand-in-Hand with Tridion to Provide AI Semantic Layer

WAND,announced a new partnership with RWS. This partnership will blend Tridion, RWS’s world-leading content technology, with WAND, Inc.’s prebuilt taxonomies to accelerate client time to delivery.

“The combination of WAND Taxonomies and RWS’s Semantic Artificial Intelligence offering dramatically reduces the time it takes to get a successful process up and running,” says Ross Leher, CEO at WAND, Inc. “The barriers of creating a taxonomy from scratch — things which have previously caused significant delays to enterprise-wide content management projects — have been eliminated.”

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Alex Abey, General Manager of Tridion, explains, “Our customers are looking for ways to improve information discovery and streamline content management. Taxonomies are a key part of such a solution but are time-consuming to manually build. By combining WAND’s industry and domain-specific taxonomies with Tridion’s semantic AI capabilities, we solve this problem once and for all.”

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The benefits of this new partnership include:

  • WAND Prebuilt Taxonomies/Metadata models reduce the model creation time by up to 90%
  • WAND foundation metadata models address 33 major industries
  • WAND foundation metadata models import into RWS applications in minutes

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Since 1983, WAND, has developed taxonomies to improve the way our clients search and organize unstructured and semi-structured information. WAND is the premier source for taxonomies, glossaries, and common data models. The breadth and coverage of WAND’s libraries are unmatched, and for years, WAND Taxonomies have been used by thousands of companies around the world to organize information. Applications, where WAND Taxonomies are being deployed, include enterprise content management, enterprise search, behavioral targeting, big data, text analytics, business intelligence, semantic technologies, local search, Artificial Intelligence, knowledge graphs, and sentiment analytics.

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