Information silos have grown up around disparate databases, software-as-a-service applications and departmental workflows, making the data people need difficult to find, creating duplicate and conflicting versions and heightening the risk of error. The problem will only worsen as data volumes continue to surge.
Universal semantic search empowers people to find related information across multiple documents and databases based on descriptions rather than keywords. Using natural language processing and machine learning, it understands the intent behind a query rather than relying solely on keyword matches.
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