Downloadable cloud-computing software for analyzing data collected from the connected fleet vehicles to help fleet stakeholders make highly informed real-time decisions for proactive quality and safety improvements and allowing for increased vehicle uptime through prediction-based maintenance utilizing supervised and unsupervised learning-based algorithms to provide purpose-built contextual awareness leading to root cause analysis, early detection of issues, and effective predictive maintenance recommendations, which enables fleet stakeholders to reduce downtime, ensure drivers' safety, and limiting upkeep costs by predicting failures; Downloadable computer software platforms for analyzing data collected from the connected fleet vehicles to help fleet stakeholders make highly informed real-time decisions for proactive quality and safety improvements and allowing for increased vehicle uptime through prediction-based maintenance utilizing supervised and unsupervised learning-based algorithms to provide purpose-built contextual awareness leading to root cause analysis, early detection of issues, and effective predictive maintenance recommendations, which enables fleet stakeholders to reduce downtime, ensure drivers' safety, and limiting upkeep costs by predicting failures; Downloadable computer software for analyzing data collected from the connected fleet vehicles to help fleet stakeholders make highly informed real-time decisions for proactive quality and safety improvements and allowing for increased vehicle uptime through prediction-based maintenance utilizing supervised and unsupervised learning-based algorithms to provide purpose-built contextual awareness leading to root cause analysis, early detection of issues, and effective predictive maintenance recommendations, which enables fleet stakeholders to reduce downtime, ensure drivers' safety, and limiting upkeep costs by predicting failures

Providing on-line non-downloadable software for analyzing data collected from the connected fleet vehicles to help fleet stakeholders make highly informed real-time decisions for proactive quality and safety improvements and allowing for increased vehicle uptime through prediction-based maintenance utilizing supervised and unsupervised learning-based algorithms to provide purpose-built contextual awareness leading to root cause analysis, early detection of issues, and effective predictive maintenance recommendations, which enables fleet stakeholders to reduce downtime, ensure drivers' safety, and limiting upkeep costs by predicting failures; Software as a service (SAAS) services featuring software for analyzing data collected from the connected fleet vehicles to help fleet stakeholders make highly informed real-time decisions for proactive quality and safety improvements and allowing for increased vehicle uptime through prediction-based maintenance utilizing supervised and unsupervised learning-based algorithms to provide purpose-built contextual awareness leading to root cause analysis, early detection of issues, and effective predictive maintenance recommendations, which enables fleet stakeholders to reduce downtime, ensure drivers' safety, and limiting upkeep costs by predicting failures