Client Overview

A large telecom operator managing nationwide network infrastructure, customer operations, and service quality across millions of subscribers.

The leadership team struggled with siloed KPIs across network systems, CRM, billing platforms, OSS/BSS, and customer experience tools — making it difficult to gain a real-time, unified view of operational performance.

The Challenge

The telecom operator faced growing operational complexity with no unified way to monitor network health, predict outages, or understand customer-impacting issues. Leaders depended heavily on analysts to stitch together reports, slowing decisions and hiding early warning signals.

Key challenges included:

• Slow decision cycles due to analyst-driven reporting
• KPIs scattered across NMS, CRM, OSS/BSS, billing, and ticketing platforms
• Static dashboards unable to detect real-time spikes in outages or congestion
• Reactive operations caused by lack of predictive and prescriptive intelligence
• No self-service insights for CXOs or operations managers
• Early churn and quality issues buried in operational noise

Our AI Solution

We deployed an AI-Powered Analytical Dashboard purpose-built for telecom KPIs, network performance, and customer experience analytics.

Key Capabilities

• AI-driven insights pinpointing root causes (e.g., "Spike in call drops due to tower load in Zone 4")
• Predictive alerts for outages, congestion, and churn risk
• Conversational Q&A: Executives ask questions in plain language
• Cross-domain data integration: OSS/BSS, CRM, billing, NMS
• Agentic workflows performing correlation, forecasting & what-if analysis
• Board-ready summary generation for network KPIs, customer care, and revenue operations

Impact & Key Results

After deploying the AI-powered operations dashboard, the telecom operator saw a fundamental shift from reactive monitoring to proactive, insight-driven decision-making. Network and customer experience issues that previously went unnoticed became visible instantly, enabling faster interventions and improved service quality across all channels.

Key results included:

• Dramatically faster decisions, with leaders receiving instant answers through natural language instead of waiting for analyst-created reports
• Significant efficiency gains (40-60%) as proactive anomaly detection reduced firefighting and manual investigation
• Improved network uptime, as predictive alerts helped identify congestion and outage risks before they impacted customers
• End-to-end visibility across network operations, customer experience, billing, and service performance
• Reduced customer churn, driven by early detection of deterioration in service quality
• Greater self-sufficiency for CXOs and ops managers, who could explore insights without relying on data teams

Call to Action

Transform telecom operations with AI-driven network & customer intelligence — Connect with us.