For example, consultancy Dachis Group has developed what it calls a Social Business Design architecture whose purpose is to help users collaborate, share ideas and then narrow down and "expose and make sense of" data within a business organization or other community of relevant individuals, such as customers or partners, says Lee Bryant, managing director of the firm's European operations.

Such offerings can significantly ease the task of developing a semantic infrastructure. For instance, Bouygues Construction used Sinequa's semantic platform, , and needed only about six months to do an initial implementation of a semantic system for locating in-house expertise, according to Eric Juin, director of e-services and knowledge management at Bouygues.

Bouygues has since developed a semantic search application that helps knowledge workers quickly find information that resides either on internal systems or on the Web, Juin says.

Context Engine indexed and calculated the relevance of people and concepts in a half-million documents, including meeting minutes, product fact sheets, training materials and project documentation, he says. The platform includes a "generic semantic dictionary" of common words and terms, which it can translate between various languages, according to Juin. For example, a French employee could semantically search a document written in German.

Certain business-specific acronyms and terms have to be added manually -- that's an ongoing process that requires semantic experts to collaborate with business users, Juin says. Over time, however, his group has been adding fewer keyword definitions, because the semantic engine can use other, related words to determine a term's relevance to a specific subject, he says.