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Robi Axiata drives efficiency with AIOps service monitoring and assurance

12 Sep 2022
Robi Axiata drives efficiency with AIOps service monitoring and assurance

Robi Axiata drives efficiency with AIOps service monitoring and assurance

AIOps monitors and assures services to reduce risk, improve customer experience, productivity and business continuity

Robi Axiata wants to manage and resolve customers’ complaints from end to end, with little or no human intervention. It is also striving to improve customer experience by minimizing complaints about and the duration of issues that impact service level agreements (SLAs). It does this by automating repetitive operational tasks and incubating awareness of operational activities through an AI-powered backend. The solution uses machine learning and deep learning as part of natural language processing (NLP) and understanding, predictive analytics and decision making, using both supervised and unsupervised models.

Robi Axiata’s AIOps solution contains three key components, complaint, performance and capacity management. It provides a human-machine mid-layer interface that analyzes data from communication channels, structured or unstructured log files, calls detail records and bot-generated reports to capture information from warnings, alarms, health metrics, security issues and customers’ complaints. The solution also draws on system and service metrics, account management and event triggers. Then it generates remedial actions, on the fly, derived from robotic process automation (RPA), and provides feedback on the success of the remedy to refine future responses.

Outcomes

  • Reduction in OpEx 75% e.g. fewer incremental human resources; annual maintenance costs cut as most Level 1 & 2 problems fixed by AIOPS
  • Working days saved annually 75 will increase with addition of new launch platform
  • Automation complaints handled in 15'' max from digital CRM to the application provider
  • Improvement in efficiency 50% from overall monitoring

Deep learning and neural networks

The backend is powered by machine learning and an offshoot of it, deep learning. Machine learning uses processes like predictive models, while deep learning uses artificial neural networks which are designed to imitate how humans think and learn.

The AIOps solution interprets, triggers responses, and communicates with other systems to perform a vast variety of repetitive tasks, resolve issues and give feedback, equipped with a fully automated continuous integration/continuous delivery (CI/CD) toolchain powered by a modular microservices-oriented architecture.

The operator summarizes the benefits it gained as better risk mitigation, customer experience, decisions and productivity, plus failsafe business continuity.

TM Forum assets used

Open APIs

  • REST based
  • Plug and play
  • Tried and tested

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Open Digital Architecture (ODA)

  • Industry blueprint
  • Modular, cloud-based
  • Orchestrated using AI

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AIOps toolkit

  • Monitoring & event management
  • Practical framework
  • Capacity management

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