We developed a machine learning-based application to intelligently route complaints to the appropriate department in a municipality. The goal was to automate the complaint routing process, reduce the workload on human operators, and improve the overall efficiency of the complaint management system.
The application uses a machine learning model to classify complaints based on their content and then routes them to the corresponding department. The model was trained on a historical dataset of complaints and their resolutions. We used various features, including the type of complaint, the location of the complaint, and the description of the complaint to train the model.
We also developed an API to expose the functionality of the machine learning model to the complaint management system software. The software would query the API to determine the appropriate department for each complaint and then route the complaint directly to that department without the need for human intervention.
The machine learning-based complaint routing system provided the following benefits for the municipality:
Increased efficiency: The automated routing process significantly reduced the time and effort required to handle complaints.
Improved accuracy: The machine learning model was able to route complaints to the correct department with a high degree of accuracy.
Reduced costs: The automation of the complaint routing process led to a reduction in the cost of handling complaints.
This project demonstrates the potential of machine learning
to improve the efficiency and accuracy of complaint routing systems.
By using machine learning, we were able to help the municipality automate the complaint routing process, reduce the workload on human operators, and improve the overall efficiency of the complaint management system.
