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Incident Management System

CogniTensor Technology Pvt Ltd

Predictive Analytics to predict incidents and automate resource allocation for the incidents

CogniTensor’s Incident Management System is a combination of correlation analytics and predictions dashboards that are designed specifically to allow you to track and manage any imminent incidents that may arise, making use of powerful predictive and descriptive analytics. It also enables you to make data-driven decisions with high accuracy, based on real time advanced and predictive analytics for all emergency incidents and related resources.

The predictive analytics is given using combinations of cutting-edge machine learning and deep learning models, backed by advanced research. These algorithms have been tailored specifically to handle complex data coming from the services that monitor the incidents.

Each of the dashboards are powered by actionable descriptive analytics that compliments predictions for the future and in turn gives your organization a head start for an optimized management of resources. 


Features and Specifications:

  1. Integrated with industry leading AI techniques and models

  2. Provide the complete Overview Analytics about all Emergency Incidents happening in a State/Region/City, including: Response Time Analytics, Resource Analytics and Incident Analytics

  3. Provide AI based Predictive Analytics on future Emergency Incidents and resources required

  4. Drill down by multiple categories: Fire Station, Type of Incident, Period of time, etc for Live and Predictive Analytics

  5. The predictive models are capable of self-learning, hence getting better performance over time.

  6. Highly customizable dashboards with ability to customize each component.

  7. Actionable recommendations can be provided based on action history plus future predictions.

  8. Easy integration support with databases management systems such as oracle, postgres, etc.

Similar experience on mobile through dedicated mobile app for IOS and android devices.
Огляд
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