AI Operations

Transition from reactive to proactive network operations 

Ensure service assurance through proactive monitoring, anomaly detection, and remediation using advanced AI algorithms.

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AI Operations Brief
Service Management & Orchestration
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The Challenges

Service assurance solutions lacking end-to-end visibility and cloud-specific insights lead to prolonged fault resolution times, increased failure rates, and higher operational costs. Furthermore, the complexity of diagnosing faults is made worse by the need to switch between different vendor-supplied systems, resulting in slow and intricate correlation efforts.

The Solution

Rakuten's AI Operations solution approach integrates robust automation for network service assurance and enables future closed-loop network remediation. With core observability, it utilizes real-time streamed data from the network infrastructure to provide a comprehensive view of network and service operations. Strategic implementation of AI/ML identifies trends and patterns in the network performance and faults, facilitating optimized network assurance with AI assistance.

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Benefits of Rakuten AI Operations

Proactive Assurance

Ensure  proactive and automatic remedial actions occur when a network SLA becomes invalid, rather than waiting for breaches due to faults or performance degradation.

Automation

Enable future closed-loop network remediation and optimization, reducing the effort spent by humans in identifying, diagnosing, isolating, and resolving problems.

Scalability

Cloud-native design that scales efficiently as data volume and variety inevitably increase, proactively managing failures and reducing the downtime. 

Cloud Platform

Establish a common foundation that supports the transition from current networks to future autonomous networks, facilitating the rationalization of the service assurance environment.

Rakuten AI Operations Solution Architecture

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