Predictive Intelligence for Universal Request

  • Versão de lançamento: Australia
  • Atualizado 12 de mar. de 2026
  • 1 min. de leitura

    • The Predictive Intelligence for Universal Request uses machine-learning algorithms for the auto-assignment of universal requests and to find similar knowledge articles and closed universal requests.

    Predictive Intelligence for Universal Request has the following benefits:
    • Use of machine learning algorithms to predict the assignment group across various departments based on the data provided by the requester in the short description and description fields of the request.
    • Use of machine learning similarity solution to provide recommendations for similar Knowledge Base articles and similar closed Universal Request. These recommendations are based on the data provided in the short description and description fields of the request, and help agents to resolve universal requests quickly.

    Solution definitions for Predictive Intelligence for Universal Request

    The solution definition for Predictive Intelligence for Universal Request is available when you activate Predictive Intelligence plugin (com.glide.platform_ml) and Predictive Intelligence for Universal Request (com.snc.universal_request.ml) plugins. You can customize the solution definition to meet your business requirements.

    Tabela 1. Solution definition for Universal Request
    Solution definition Solution type Description
    Universal Request Categorization Classification
    • Predicts the assignment group from the short description and description of a Universal Request.
    • Runs a business rule to create service level tickets using the prediction.

      The service level tickets that are created will be associated with the universal request.
    Similar Knowledge Articles for UR Similarity Predicts similar knowledge base articles based on the short description and description of a Universal Request.
    Similar closed Universal Request Similarity Predicts closed Universal Request that have similar short description, description, and assignment group.
    Identify sensitive information in UR Classification Identifies and predicts that the UR is sensitive based on the short description and description of the request. It also marks the request as restricted.