For this case, my team and I worked on providing our client, Allied Solutions, a way to integrate artificial intelligence and machine learning into their customer service platform. The main goal was to manage the costs related to their customer relationship management (CRM) solution.

The main issues we highlighted with their existing system were; the rudimentary data collection method, the monolithic system of record (SOR), and the time wasted while rerouting customers & verifying information.

Our solution consisted of 3 parts which are also released in phases to minimize potential issues with implementation & also to build the AI model with data over time. First, to Integrate the existing CRM solution with the backend insurance tracking system called Unitrac. Second, to create a robust chatbot using artificial intelligence. Third, to reduce call length, customer service representatives are provided with all information collected with the chatbot.

This solution allows AI/ML to be integrated by using Unitrac to gather data from the information submitted through the AI chatbot, which then can provide potential solutions to customers’ issues in the chatbox by looking at past cases that might be similar and building a larger database of cases and insurance info that the AI model can learn from. Also, the chatbot could provide a summary of the case to the customer service representative if the problem is routed to a representative (chatbot solutions were not able to assist). This can also further reinforce machine learning as the customer service representative can provide feedback on whether the solutions given by the AI were adequate or not. One further use of the AI chatbot is to help route calls to the right agents, as rerouting takes time and increases costs.