Support teams receive lots of data in form of client logs and traces while working on support tickets. This data can provide very valuable actionable insights if processed correctly. In this collaborative project between IBM and York University, we have created AI powered tools to parse client logs in systematic way. These tools are executed on client data arrival with support ticket and extract meaningful insights. These insights than get consolidated with historic data which keeps building pipeline of insights in a prioritize order. Product Management and Development team utilized this priorities list and improves product quality avoiding similar issues from happening in future. As it’s other application, anomalies detected before is passed to another LLM which is trained on specific product domain, provides possible resolution for each anomalies identified. This helps support engineers to head start their PD process saving time to resolution.

Session Topic: App Runtimes
Speaker(s): Ashish Ghodasara, Gias Uddin