Billing disputes such as bill shock, invoice errors, and partner charge discrepancies remain one of the most manual, time-consuming, and inconsistent processes in telecom operations. Slow resolution, repetitive investigations, and human error drive customer dissatisfaction, increase churn risk, and lead to revenue leakage and high operational costs. The Agentic-AI Powered Autonomous Billing Dispute Management Catalyst introduces a lightweight, multi-agent AI solution that automates the end-to-end dispute lifecycle—from proactive detection to resolution execution. Leveraging agentic AI, the solution ensures data-backed, consistent decision-making while balancing speed, compliance, and human oversight. The platform proactively detects billing anomalies and potential disputes before customers escalate issues. It supports frictionless, omnichannel intake of complaints across chat, email, and voice, and performs autonomous root-cause analysis by correlating invoice data, billing records, mediation outputs, and partner charges. Based on this analysis, the system intelligently proposes resolutions—such as credits, adjustments, or rollbacks—and uses aggregate confidence scoring to either auto-execute actions or route them to a human-in-the-loop for approval. Built on a multi-agent architecture and integrated with BSS systems via TM Forum Open APIs, the Catalyst demonstrates how dispute management can shift from manual case handling to governed, autonomous workflows. Success is measured through improved detection and resolution accuracy, reduced handling time, higher automation and first-contact resolution rates, improved customer satisfaction, lower operational costs, and stronger revenue protection. By transforming billing dispute management into an intelligent, auditable, and autonomous capability, the Catalyst helps CSPs enh