Bell’s new AI operations (AI Ops) solution, leveraging Google Cloud’s AI/ML capabilities, enables faster detection and resolution of network problems, improving network performance
Bell is modernizing its network management and shifting from a reactive to proactive approach, resulting in efficiency gains and improved customer experiences
Bell Canada announced its network AI Ops solution built on Google Cloud, which has been successfully deployed and is already revolutionizing how it detects, analyzes, and presents network issues. This AI-driven approach has significantly improved Bell’s mean time to resolution (MTTR), enabling proactive network management that enhances reliability and optimizes the customer experience.
In an era where telecommunications networks face increasing complexity and surging data traffic, traditional management methods struggle to keep pace. Legacy systems often rely on reactive approaches and manual processes, leading to inefficiencies, service disruptions, and customer frustration. Bell’s AI Ops solution shifts network management from reactive troubleshooting to intelligent, proactive optimization—ensuring a seamless and high-performing customer experience.
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Built using Google Cloud’s products and services—including Google Kubernetes Engine (GKE), BigQuery, Pub/Sub, and custom AI/ML models—Bell’s AI Ops solution introduces a new level of network intelligence. The system autonomously correlates network data and customer experiences to better prioritize issues.
While a minor issue at a low-traffic site may not require urgent attention, even a small disruption at a high-traffic site could significantly impact customer experience. Bell’s AI Ops solution, powered by Google Cloud’s Spanner Graph, dynamically assesses network relationships and changes in traffic to wholly understand the customer impact. Additionally, Google’s Gemini multimodal AI models enable rapid incident analysis, historical context retrieval, and streamlined access to vendor documentation for faster issue resolution.
- Proactive Issue Detection – AI-driven automation identifies and prioritizes network issues before they escalate, reducing service disruptions.
- Accelerated Remediation – Automated network monitoring dramatically improves MTTR, resulting in faster recovery from outages.
- Real-Time Observability – Advanced analytics provide real-time insights into network performance, allowing Bell to address potential issues before customers are affected.
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Since partnering with Google Cloud, Bell has seen a 75% increase in software delivery productivity, streamlining its development processes and accelerating time to market. Additionally, it’s achieved a 25% reduction in customer-reported issues, greatly enhancing customer experience and demonstrating the reliability of its solutions. This improvement reflects the ongoing rollout of Google Cloud’s suite of products and services, with AI Ops playing a significant role. This is further underscored by Bell’s consistent achievement of a 99.8% service-level agreement (SLA) compliance rate for data availability and timeliness, highlighting the robust and dependable nature of its infrastructure.
“This initiative significantly enhances the customer experience by revolutionizing how Bell identifies and prioritizes network and service anomalies. By leveraging Google Cloud’s AI, we are achieving greater accuracy and speed in resolving issues, accelerating our progress towards autonomous networks and continuously improving operations for an exceptional customer experience.” Mark McDonald, Senior Vice President, Networks, Bell.
“This new network AI Ops solution isn’t just about incremental improvements; it’s a fundamental shift in how networks are managed. By combining Bell’s deep network expertise with Google Cloud’s technology, we’re enabling a new era of intelligent network operations.” Angelo Libertucci, Global Industry Lead, Telecom Strategies & Solutions, Google Cloud.
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Source – PR Newswire
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