Automating text mining analytics at a major philanthropic foundation

Automating text mining analytics at a major philanthropic foundation

Azure AI/ML, Bots, Customer Stories, MLOps, Technology
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Challenge

  • The foundation needed a more efficient grant selection process due to the volume of requests, which come from a multitude of partnerships from all over the world.
  • Factors that contribute to grant success are difficult to determine and may seem unrelated.
  • Factors indicative of failure or success using grant proposal data and external data sources were difficult to identify.

Text mining solutions

Solution

  • Using Microsoft Cognitive Services and the Bot Framework, Neal Analytics developed a chatbot capable of asking questions, displaying on-the-fly data metrics, and giving insight.
  • Behind the scenes, the bot leverages several machine learning algorithms and text mining techniques.
  • By combining both internal and external data sources, a high predictive analysis is now possible from the grant proposals alone.

Text mining results

Result

  • Bot outputs graphical and text-based insight
  • Bot automates user queries and answers a key question
  • Bot surfaces information

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