Modern telecom networks face frequent and complex faults, from hardware failures to software misconfigurations that disrupt services and increase operational costs. Recent progress in large language models (LLMs) offers a new opportunity: applying reasoning-capable AI to automatically detect, interpret, and explain the root causes of network issues.
The AI Telco Troubleshooting Challenge aims to accelerate innovation in applying LLMs for Root Cause Analysis (RCA) within telecom networks. By tackling real-world datasets and unseen fault conditions, participants will contribute to:
- Reducing network downtime and operational costs through intelligent fault analysis.
- Developing models that generalize across diverse network scenarios and environments.
- Enabling scalable, autonomous, and resilient telecom systems through reasoning-driven AI.
- Exploring small, edge-trainable models (SLMs) that offer efficient performance and lower deployment barriers.










