ABot Analytics helps in determining the Root Cause of a failure by presenting a set of RCA screens with relevantmetrics to infer the cause of failure classified by Build, Configuration or Application issues.

ABot uses AI-driven man-machine learning model for predicting test results and root cause identification. The data insights and KPIs generated by ABot analytics box are collated from multiple layers of NFV and multiprotocol test scenarios. ABot Analytics Box intelligently draws inference and leads the user to the exact underlying cause of the failure through a series of interactive dialog boxes. Failures are pin-pointed at every step of the call flow and classified under configuration, VNF or infrastructure issues. The machine also predicts a test failure based on the conditions arising during test run. Thus it helps in live network troubleshooting and reduces CAPEX and OPEX of operators, substantially.