AI‑Accelerated Network Optimization to Intelligent Maintenance addresses the growing operational crisis caused by rapid network scale expansion and increasingly dynamic service complexity. Traditional manual operations and maintenance models are no longer sufficient, leaving customers constrained by three systemic contradictions: low network efficiency, high O&M complexity, and delayed fault response. These challenges manifest in suppressed traffic, slow fault localization, and heavy reliance on expert intervention, all of which limit service quality and business growth.
The solution delivers clear and measurable business value by transforming CSPs from “pipeline providers” into intelligent service ecosystem builders. By automating network and service optimization, it reduces base station quality issue localization from hours to minutes, shortens service optimization cycles from one week to one day, and compresses network optimization from 24 hours to just 15 minutes. These efficiency gains directly release suppressed traffic, improve network utilization, and drive revenue growth while significantly accelerating operational response speed.
Innovation is realized through the use of AI‑driven capabilities that enable network‑level and service‑level optimization. The solution deploys intelligent agents for IP optimization, natural language dialog, intelligent risk analysis, intelligent path navigation, and real‑time poor‑QoE awareness. It achieves automatic optimization across 11 scenarios and end‑to‑end closed‑loop automation in 9 scenarios, reducing manual intervention and addressing long‑standing challenges such as invalid work orders, slow fault localization, and complex cross‑domain coordination.
The solution leverages telecom foundation models and network digital maps to automate network awareness, analysis, and optimization. It combines a seven‑layer network model, real‑time traffic heatmaps, graph‑based path navigation, predictive maintenance through time‑series modeling, and an AI Copilot using natural language to simplify operations. Success is measured through released traffic suppression, revenue growth, major reductions in optimization time, and expanded automation coverage—demonstrating how AI‑accelerated intelligent maintenance delivers both operational excellence and sustainable commercial impact.
