Service issues are often detected too late
Operations teams frequently investigate performance degradation only after alarms are triggered or subscribers report poor service experiences.
Predict Service Issues Before Subscribers Experience Them
We combine AI-driven analytics, real-time service monitoring, and intelligent automation to detect, diagnose, and resolve service degradation before it impacts customer experience or business performance.
Challenges
Industry Challenges
Operational data is fragmented across multiple systems
Network events, application performance, customer experience metrics, and operational alarms often exist in separate platforms, making troubleshooting slow and complex.
Modern telecom networks are increasingly difficult to assure
Multi-vendor environments, cloud-native architectures, virtualised network functions, and 5G deployments create operational complexity that traditional assurance platforms struggle to manage.
Maintaining service quality while controlling operational costs is a constant challenge
Operators need continuous visibility, intelligent prioritisation, and faster resolution to meet SLA commitments without increasing operational overhead.
Product Overview
AI-Powered Service Assurance for Modern Telecom Networks
Service Assurance provides continuous visibility into network, application, and subscriber performance, enabling operators to identify service degradation before customers are affected. Powered by Agentrix, the platform combines real-time telemetry, Deep Packet Inspection (DPI) insights, and AI-driven analytics to correlate events, identify probable root causes, and recommend the most effective remediation actions.
The Outcomes Are Clear
01
Earlier issue detection
02
Faster resolution
03
More reliable services
Capabilities
Product Capabilities
Real-Time Service Health Monitoring
Continuously monitor network performance, service quality, and customer experience across multiple technologies, domains, and operational environments.
AI-Powered Root Cause Analysis
Automatically correlate alarms, telemetry, and traffic intelligence to identify the most probable cause of service degradation and reduce manual investigation.
Predictive Service Analytics
Apply machine learning models to identify emerging performance issues and forecast service degradation before subscribers are impacted.
Intelligent Alarm Correlation
Consolidate thousands of network events into prioritised operational incidents with contextual relationships and business impact.
Automated Remediation Recommendations
Recommend the most appropriate corrective actions using AI-driven operational intelligence, historical incident analysis, and configurable business policies.
Subscriber Experience Intelligence
Combine network performance with application and subscriber insights to understand how operational issues affect the customer experience.
Unified Service Intelligence Dashboard
Provide a single operational view of service health, SLA compliance, incident trends, and performance KPIs across the network.
Multi-Domain Service Assurance
Deliver consistent service assurance across radio, transport, core, cloud, virtualised infrastructure, and emerging 5G environments.
Process
How It Works
01
Continuously Monitor Service Performance
The platform ingests telemetry, KPIs, alarms, and subscriber experience data from across the telecom network in real time.
02
Correlate Operational Intelligence
Agentrix automatically correlates network events, application behaviour, historical incidents, and service dependencies into a unified operational context.
03
Diagnose the Root Cause
AI models analyse operational patterns to identify probable root causes, eliminate false positives, and prioritise incidents based on business impact.
04
Recommend Corrective Actions
Operations teams receive intelligent remediation recommendations that accelerate investigation and reduce operational effort.
05
Continuously Improve Assurance
Operational outcomes are fed back into the analytics engine, enabling increasingly accurate predictions and recommendations over time.
Results
Key Outcomes
Detect Issues Earlier
Identify emerging service degradation before it develops into customer-impacting incidents.
Reduce Mean Time to Resolution (MTTR)
Accelerate fault isolation and incident resolution through AI-assisted root-cause analysis and intelligent prioritisation.
Improve Service Availability
Maintain consistent service quality through continuous monitoring and proactive operational intelligence.
Strengthen SLA Performance
Monitor service commitments in real time and respond faster to issues that threaten operational targets.
Increase Operational Efficiency
Reduce manual investigation, minimise alarm fatigue, and enable operations teams to focus on the incidents that matter most.
Deliver Better Customer Experiences
Improve application responsiveness, service reliability, and subscriber satisfaction through proactive service assurance.