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    RCA Network Operations Agent

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    Multi-Agent AI Root Cause Analysis (RCA) for Telecom Networks is an AWS-native solution that automates fault diagnosis across complex telecom infrastructure, including RAN, core, and transport networks. Using a multi-agent AI architecture powered by Amazon Bedrock, the solution ingests alarms, KPIs, topology, and logs into a dynamic network knowledge graph to rapidly identify probable root causes. Specialized AI agents analyze cross-domain data and are orchestrated by a supervisor agent to deliver explainable RCA outcomes, recommended actions, and automated ticket creation. Built on scalable AWS services such as Amazon EKS, EventBridge, and Neptune, the solution significantly reduces MTTR, improves SLA compliance, and enables proactive, auditable network operations at scale.

    Overview

    Telecom Network Root Cause Analysis Challenge

    Telecom networks span complex RAN, core, and transport domains, generating large volumes of alarms, KPIs, logs, and topology data. Root cause analysis is often manual and siloed, requiring engineers to correlate multiple data sources under time pressure. This leads to long MTTR, SLA violations, and rising operational costs. Traditional rule-based monitoring struggles with cascading failures and dynamic 5G environments, limiting visibility and reliability as networks scale.

    Our Solution: Multi-Agent AI-Driven Telecom RCA

    The Multi-Agent AI Root Cause Analysis (RCA) solution is an AWS-native platform that automates fault diagnosis across telecom networks. Built on Amazon Bedrock, Amazon EKS, EventBridge, and Amazon Neptune, it ingests real-time telemetry into a dynamic network knowledge graph. A supervisor AI agent orchestrates domain-specific agents across RAN, core, transport, and maintenance to correlate events and identify root causes in minutes.

    Event-driven workflows trigger agentic RCA runbooks for anomaly detection and analysis. The solution generates explainable RCA reports with evidence and recommended actions, and integrates with OSS/BSS and ITSM systems such as ServiceNow or Slack. The architecture is scalable, auditable, and supports hybrid and edge deployments via AWS Outposts.

    Key Benefits & Business Outcomes

    1. Dramatic MTTR reduction by automating cross-domain fault correlation and root cause identification

    2. Improved SLA compliance through faster incident response and proactive issue detection

    3. Reduced operational overhead by minimizing manual triage and dependence on tribal expertise

    4. Explainable and auditable RCA with full visibility into agent decisions and data sources

    5. Scalable, event-driven architecture that handles alarm spikes and growing network complexity

    6. Extensible multi-agent framework allowing new domain agents and workflows to be added without re-architecture

    Ideal Users / Organizations

    Network Operations (NOC) teams, telecom service providers, managed network operators, SRE and DevOps teams, and network engineering organizations operating 4G/5G RAN, core, and transport networks. The solution is ideal for enterprises seeking to modernize network operations, reduce outage impact, improve service reliability, and implement scalable, AI-driven RCA using AWS-native services.

    Highlights

    • Automated, multi-agent RCA across RAN, core, and transport networks, correlating alarms, KPIs, logs, and topology to identify probable root causes in minutes without manual triage.
    • Explainable AI diagnostics powered by Amazon Bedrock, using domain-specific agents and a network knowledge graph to deliver auditable RCA reports with evidence and recommended actions.
    • AWS-native, event-driven architecture built for scale and reliability, leveraging Amazon EKS, EventBridge, and Neptune to handle alarm spikes, support hybrid/edge deployments, and integrate seamlessly with OSS/BSS and ITSM systems.

    Details

    Delivery method

    Deployed on AWS
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