This company trusted Aptude with the task. Our data scientists developed the machine learning models based on the use case and the data sources available. Because certain data points like fuel prices, accidents and weather, for example, can change on a dime, a big hurdle we had to solve for them was the “real time” problem.
Most of the time, there’s a latency in the data – a day, half a day later the data might get “ingested” for the model. To solve this problem, we installed a team of expert python data engineers whose job is to ingest the data in real-time and deliver it to the machine learning model quickly. That model is constantly learning and applying that learning to the algorithms without delay.
As a result, the model is spitting out recommendations in real-time based on nearly real-time data. So if their customer wants a quote, they will get pricing and turnaround times that are both efficient and profitable. The client is able to quote different pricing based on the factors and make highly data-driven routing decisions.