A global leader in on demand cab service has one critical requirement to sustain and remain a leader in their business, that is to have on demand drivers to cater to growing just in time demand. One of the process that their back offices manage is the driver verification which requires complete demographics to be validated and entered into the database for validation. The number of data sets run into thousands per day and the verification time in hours. This surges their peak hour pricing due to high demand and low availability.
This process of demographic data entry itself is managed by about 1500 plus staff at the back office. Current system is to classify based on visual cues and enter the data manually through a validator screen.
The cab aggregation market is a growing business and with growing competition validation of driver data in the quickest of the time is critical to stay ahead. With latest advancements in Computer Vision technologies it is possible to automate this process by using object detection techniques.
Reduce verification time from a few hours to within minutes.
Reallocate 50% of back-office resources to service over one year.
Reduce surge pricing by 20 % over the year.
AI based classification model.
Deep learning models for improvised self-learning.
RPA Orchestrator for task and workflow management.