Aevitae’s customer service receives hundreds, if not thousands of e-mails per day. Up until recently, every new e-mail was read by an employee and manually forwarded to the relevant department. Not only was this process time-consuming, but it was also costly. The question was: can we tackle this problem smarter and more efficiently? Within six weeks, our Data Science team developed a machine learning model that automatically forwards 90% of the incoming e-mails to the right department. The AI tool can spare up to 2 FTEs per year. During this project, we assisted Aevitae with:

Every day, up to thousands of incoming e-mails were manually forwarded to the right department. An AI tool can automate this repetitive task by learning from the historical data. For example, by looking at the e-mails that Aevitae has filtered and categorized over the past year, the AI tool can use machine learning techniques to predict which department should pick up the e-mails.

Our team also designed a Power BI dashboard that showcases the numbers of forwarded e-mails. It also displays how often this process is performed correctly and when an employee had to correct it manually. The new ability to track the number of e-mails each department receives and how it evolves over time provides Aevitae with brand new insights into their customers.