AIOps leverages artificial intelligence (AI) to optimize IT operations by reducing ‘alert noise’ and enhancing troubleshooting processes. It eliminates 90% of incidents to be reassigned to operations teams via proactive management and anomaly detection.

AIOps uses machine learning (ML) models to ingest data from existing monitoring tools and incident management. It prompts the IT operations team about the root cause, which reduces the mean time to repair (MTTR) significantly.

AIOps adopts an enterprise approach that transcends technology. Mature enterprises that understand the limits of manual work are pivoting to AIOps and identifying tasks with context-based automation.

Infosys’ multi-layered AIOps solution, part of Infosys Cobalt, offers visibility and observability, while facilitating better collaboration and actionability to enhance IT operations.

Enabling continuous service assurance through predictive analytics and machine learning.


Challenges & Solutions

AIOps leverages AI and ML to proactively diagnose the IT estate and streamline operations, thereby reducing mean time to identify (MTTI) and mean time to repair (MTTR).

Predictive intelligence enables automation of the issue assignment workflow.

AIOps offers end-to-end visibility for the SRE, and operations engineer to identify the affected business service.