About
Our client, a leading telecom provider faced challenges in extracting meaningful insights from the network data, proactively managing network performance and correlating events with network issues. Additionally enhancing customer experience at high-traffic locations has been increasingly critical to ensure customer satisfaction and reducing churn.
The challenge
Operational and technical obstacles preventing effective network management.
The provider's existing systems were siloed, involving multiple isolated tools and manual processes, which further complicated the situation.
- Prolonged data insights -The difficulty in extracting meaningful insights from the vast amounts of network data delayed the identification and resolution of issues. This adversely affected customer service levels and satisfaction.
- Siloed systems- Existing systems were siloed which hindered the integration of necessary analytics with critical tools. As a result this lack of cohesive understanding of network performance mpacted proactive network management.
- Complex KPI selection- Selecting appropriate Key Performance Indicators (KPIs) for effective performance assessment emerged as a complicated task. Engineers faced the challenge of isolating the most relevant indicators amidst a myriad of data points.
- Inefficiencies in customer experience- Efforts to enhance customer experience, particularly in high-traffic locations, were significantly compromised. The existing tools could not effectively correlate events with network issues, undermining the organization's ability to maintain a high standard of quality in customer interactions.
The solution
NetSight, an AI-powered virtual network troubleshooting system.
The solution incorporated a series of innovative components designed to deliver actionable insights:
- A data ingestion platform collected mobile RAN data, facilitating the integration and processing of critical network information.
- Retrieval Augmented Generation (RAG) was implemented for contextual analysis, aiding in the extraction of relevant insights from data.
- The AI LLM integration enabled the analysis of network performance metrics, improving overall visibility and response times.
- Advanced visualization capabilities were provided through Vertex AI and Looker, allowing for dynamic report generation and visualization of data.
NetSight targeted three specific user personas, Director of RAN, RAN Engineer, and Optimization Engineer, streamlining operations and enabling efficient data management tailored to their responsibilities.
Real-time anomaly detection and root cause analysis
NetSight leverages advanced machine learning algorithms to continuously analyze network data streams to detect anomalies in near real-time. Whether it's an unexpected latency spike or an unusual traffic pattern, NetSight instantly identifies these deviations. NetSight doesn't just flag issues; it delves deeper into pinpointing the root cause, leveraging its knowledge base and understanding of network behavior.
Event correlation
The solution is able to correlate mass events in the network cluster with performance spikes. This significantly reduces diagnostic time which enables faster resolution and minimizes the impact of service disruptions on the customer's quality of experience (QoE).
The impact
Quantifiable outcomes and strategic benefits.
The implementation of NetSight resulted in significant improvements in operational efficiency and customer satisfaction.
- Competitive edge- By enabling faster resolution of customer issues and enhanced Quality of Experience, customer churn was reduced.
- Proactive network management- Transformed traditional reactive strategies into dynamic responses capable of adapting to emerging challenges.
- Enhanced customer experience- Substantial improvements in customer experience, by reducing the time required to identify the root cause and resolve network issues.
- Resource optimization- The ability to correlate network issues with external events and deliver comprehensive visibility allowed for more effective resource allocation and management, which in turn elevated overall service quality.
- Empowered engineering teams- By leveraging advanced data-driven insights, its engineers were equipped to tackle challenges swiftly, ultimately playing a crucial role in fostering enhanced customer loyalty and satisfaction.
Generative AI will play an increasingly important role by creating an even more fluid operational landscape characterized by real-time data integration and automated issue resolution.
