The client is a leading multinational Oil and Gas corporation with a workforce of over 51,000 employees. As one of the world’s leading public companies, their operations span across crude oil and natural gas exploration, power generation, transportation, refining, and trading.

The client faced a complex IT, application, and network infrastructure, managed by multiple vendors across on-premise and cloud environments. Manual interventions were prevalent, leading to employee dissatisfaction and decreased productivity. Key challenges included:

• Lack of standardized processes for resolving the large volume of incoming incidents, resulting in increased human errors and turnaround times (TAT).
• Complicated infrastructure and network landscape, with different vendors handling various technology towers.

To maintain its leadership position in the Oil and Gas industry, the client needed to implement zero-touch automation and efficient incident resolution. They aimed to reduce IT operations costs through automation, create and retain knowledge, establish best practices, and develop standardized, reproducible, and machine-executable workflows. Airo’s AIOps services facilitated this transformation.

Why Airo’s AIOps?

The client opted for Airo’s AIOps solutions for its advanced capabilities in Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP). These technologies significantly accelerated the IT resolution lifecycle and enabled the client to achieve zero-touch automation, resulting in faster time-to-value.

Key Features and Benefits

In collaboration with the client’s AIOps service, IT Service Management (ITSM) tool (ServiceNow), and Robotic Process Automation (RPA) tool (Ansible Tower), AiOps automated the end-to-end incident resolution process, fostering a culture of “Zero Touch Incident Resolution.” With AiOps, the client realized several benefits, including:

• Leveraging NLP micro-services to understand incident context and recommend the most relevant solutions.
• Triggering resolution processes using the RPA tool for achieving closed-loop remediation while continuously learning and improving over time.
• Intelligently transferring tickets to another queue for manual intervention in exceptional cases.

Key Use Cases

Some principal use cases of AiOps in the client’s environment included:

• Service and agent checks and restarts
• Disk cleanups
• Server and storage connectivity checks
• Monitoring compute and memory utilization across various operating systems

By implementing AiOps, the client experienced the following benefits:

• Improved SLA adherence
• Higher system availability
• Significant reduction in human effort
• Substantial savings in downtime-related costs

• Successful resolution rate: 96%
• Reduction in Mean Time to Resolution (MTTR): 48%
• Effort saved: 93,000+ hours
• Number of tickets handled: 540,000+