Sentiment analysis of user-generated feedback

Identifying and categorizing opinions into positive, negative, or neutral in CRM platforms is one example of sentiment analysis application based on NLP technology. It is also applicable for auto blocking negative comments or the ones with banned words. Positive comments could be categorized into so-called “prospective clients” folder for further e-mail marketing or other campaigns.

AI-powered support

Software for automatic client support, or web robot- (simply: bot) generated support, with large knowledge base equips businesses to reach bigger audience and/or assist their online clients 24/7. This could become advantageous almost for any industry, including Finance, Healthcare, Education, Insurance, as a support-bot saves corporate money earlier spent on HR.

Search functionality

Search engine – based on natural language queries rather than keywords – facilitates web pages navigation and the flawless recognition of user-generated requests.
Enabled to enter natural speech enquiries (e.g.”What did Werber write?”), users get full-dress search results, based on derivatives, synonyms, and semantic search history.

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Samples of NLP and Big Data applicatiocn include:


  • Search engines, thesaurus knowledgebases

  • Machine translation, spell checking apps

  • Automated replies: e-mail, online support

  • Knowledge or sentiment discovery in texts

  • Data mining of structured and non-structured data

  • Data-driven decision management, etc