IBS – IAS Solution

IAS (Intelligent Assurance Service) delivers end-to-end fault self-healing through Al-driven analytics. It shifts network operations from passive maintenance to proactive automation by detecting anomalies and triggering automatic recovery. IAS significantly reduces MTTR and improves network availability.

With the convergence of 5G, gigabit networks, and cloud architecture, traditional manual O&M is no longer sustainable under multi-vendor, multi-domain complexities, facing critical bottlenecks like root causes drowned in alarm storms, reactive fire-fighting, and skyrocketing OPEX. To address these pain points, the global telecom industry has aligned to accelerate toward "zero-touch, closed-loop" high-level Autonomous Networks (AN).

IAS senses live network dynamics through comprehensive monitoring and data quality management, diagnoses network anomalies using AI-driven topology correlation and Root Cause Analysis, and ultimately drives the Automated Provisioning System to achieve agile, closed-loop self-healing.

IAS Suite Architecture

IAS aims to build an AI-based intelligent network assurance platform that integrates full-domain performance management, Centralized fault management and ticket scheduling, thereby enhancing network operational efficiency and customer satisfaction.

Ready-to-use Data Collection Capability

Based on an adapter- and task-driven mechanism, IAS provides a rich set of out-of-the-box (OOTB) adapters that support multi-vendor, multi-technology network access. This enables automated data collection and resource discovery, ensuring data accuracy and real-time performance.

Core Capabilities of IAS

Inspur IAS Suite provides advanced autonomous networks by integrating intelligent monitoring, precise fault handling, and flexible configuration.

Policy-Driven Closed-Loop Service Assurance

By combining unified multi-domain data collection with AI-driven intelligent analysis, it enables an end-to-end closed-loop system. This seamless integration ensures zero-touch service provisioning and automated fault self-healing for highly efficient network operations.

AI Empower: Closed-loop Fault Handling

End-to-end fault management encompasses several key stages: fault identification, fault diagnosis, fault handling, and recovery verification. By leveraging AI and ML technologies, this approach is designed to significantly enhance the efficiency and reliability of network operations.