Case Study
Overview
Telecom operators faced network outages and QoS disruptions due to reactive maintenance practices. INNOIRA deployed ML-powered predictive analytics to anticipate failures and automate repair workflows.
BUSINESS CHALLENGES
- Reactive network fixes causing expensive outages and customer dissatisfaction
- Massive sensor and environmental data difficult to analyze manually
- No mechanism to predict equipment failures
SOLUTION IMPLEMENTED
- ML models ingest sensor data, alarm logs, and weather patterns to predict failures 7 days earlier
- Automated work order creation with RPA routing tasks to field teams
- Proactive resource allocation reducing downtime
Impact Delivered
40%
Downtime Reduction
Major improvement in network stability
20%
Maintenance Savings
Lower cost through planned interventions
99.99%
Uptime
Superior network continuity