AI agents autonomously bridge data gaps between EMS, GIS, and CRM systems to slash MTTR and optimize performance across complex fiber infrastructures.
Unryo, a leader in Agentic AI for IT and network operations, detailed how its AI framework is solving the most persistent challenges in Gigabit Passive Optical Network (GPON) and Fiber-to-the-Home (FTTH) operations. By automating the correlation of fragmented data across siloed systems, Unryo allows operators to move from manual troubleshooting to autonomous network intelligence.
Orchestrating Data Across the Fiber Stack
GPON environments are notoriously difficult to monitor due to the “blind spots” created by passive optical components and data trapped in separate EMS, GIS, and CRM systems. Unryo’s Agentic AI acts as a digital engineer, interacting directly with these disparate sources to reconstruct real-time dependencies and pinpoint root causes.
Key Capabilities:
– Dynamic Topology Reconstruction: The platform automatically builds a live dependency graph linking physical entities (Metro → OLT → Splitter → ONT) to logical customer services and SLA commitments.
– Automated Root-Cause Investigation: Agents execute sophisticated engineering workflows, such as isolating power degradation, validating OLT port saturation, and detecting optical drift before failure occurs.
– Conversational Diagnostics: Technicians can interact with the network via a context-aware chat interface. Instead of navigating dashboards, they can ask, “Identify all customers affected by the attenuation spike on splitter Z,” and receive a structured explanation backed by live evidence.
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– Business-Aware Remediation: Unryo quantifies service impact in real-time, calculating exact SLA/SLO risk and allowing operations teams to prioritize repairs based on business-criticality rather than just alarm volume.
Strategic Operational Impact:
By unifying the observability stack into a single end-to-end view, Unryo delivers measurable gains in operational efficiency:
– 80% Reduction in MTTR: AI agents identify root causes and propose remediations within seconds.
– 30% Less Downtime: Predictive detection of optical degradation prevents outages before they impact the subscriber.
– 60% Tool Consolidation: Streamlines fragmented monitoring environments into a unified operational framework.
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