NETWORK KPI INTELLIGENCE

A predictive network AI built to forecast KPI degradation, tune radio parameters, and keep telecom operators ahead of service impact.

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Case detail
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Project challenges

Managing network quality across thousands of cells demands early degradation detection and precise tuning. KPI data volume posed severe analytical and reporting demands.

  • Spotting degradation before service impact.
  • Consolidating KPI data across thousands of cells.
  • Prioritising field work by real business impact.
  • Tuning parameters without risking live traffic.
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The solution

We engineered a predictive analytics platform integrated into existing network reporting systems. It forecasts KPI degradation, isolates underperforming sites, and recommends parameter changes before deployment.

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The result

Operations gained earlier warning, sharper field prioritisation, and measurably fewer dropped calls.

40

%

Faster degradation detection

24

/7

Real-time KPI monitoring

30

%

Reduction in field escalations

Project information

Date:
Jan 2021
Client:
Major Telecom Vendor
Industry:
Telecom
Services:
Machine Learning, Dashboard Engineering, Security Audits
Technology stack:
Python, Scikit-learn, AWS Lambda, MySQL

"We stopped reacting to yesterday's KPIs. The team now knows which sites to touch before Monday."

Abdullah
Head of Network Operations
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