CUSTOMERLeading IT Infrastructure
A large software provider for IT operations needed to expertly handle a huge volume of service tickets. We created a solution that expedites the ticket resolution process by forecasting request volume in advance and employing suitable resource allocation.
We created a solution to forecasts the volume of service tickets based on multiple ML techniques, including log structure discovery and parsing, periodicity detection, time-series analytics, frequent pattern mining, entropy-based encoding and temporal association detection.
Our solution forecasts service ticket volume with 70-95% accuracy, additionally generating actionable resource-allocation suggestions.