Our solution achieved a forecasting accuracy of 70-95%, providing critical insights for better resource allocation and efficient ticket routing.
Meet our client
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Client’s Challenge
A global software leader needed to manage fluctuating service ticket volumes, seeking a solution to improve help-desk efficiency and reduce resolution times while maintaining high service standards across multiple sites.
Our Solution
To create a predictive model, we developed and implemented a custom AI-driven solution using a range of machine learning techniques, including log structure discovery, periodicity detection, time-series analytics, and entropy-based encoding.
Client’s Benefits
Our solution achieved a forecasting accuracy of 70-95%, providing critical insights for better resource allocation and efficient ticket routing. This led to a reduction in mean-time-to-resolution (MTTR) by up to 50% and decreased help-desk workload by up to 40%. Additionally, onboarding time for new team members was cut by up to 50%.
