If you’ve had the opportunity to build a search application for unstructured data (i.e., wiki, informational web sites, self-service help pages, internal documentation, etc.) using open source or commercial-off-the-shelf search engines, then you’re probably familiar with the inherent accuracy challenges involved in getting relevant search results. The intended meaning of both query and document can be lost because the search is reduced to matching component keywords and terms. Consequently, while you get results that may contain the right words, they aren’t always relevant to the user. You need your search engine to be smarter so it can rank documents based on matching the meaning or semantics of the content to the intention of the user’s query.
Amazon Kendra provides a fully managed intelligent search service that automates document ingestion and provides highly accurate search and FAQ results based on content across many data sources. If you haven’t migrated to Amazon

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