AI Use Case
Detect anomalies in software stacks prior to deployment
Detect anomalies in software stacks (e.g. security or downtime risks). Fro example, banks tend to have complicated legacy systems based both on multiple generations of development and software codes but also driven by historic merger activity in the industry.
Cost - Job automation,Risk reduction - Maximise system uptime,Operational - Increased machine uptime,Operational - Faster system build / test / deploy
H&R Block~H&R Block improves filing acceptance rates by 10% by monitoring the performance of its online tax filing application and user experience using machine learning,Trek Bicycle~Trek Bicycle reduces error rates in its website and bike sharing app services from 8-14% to <1% using machine learning to monitor anomalies in real-time,ReTest~ReTest automates testing of Java based software application GUI with 82% accuracy using artificial neural networks and machine learning
Structured / Semi-structured
Machine Learning (ML),ML Task - Grouping - Anomaly Detection
New Relic,New Relic