arXiv AI By Jeremias D\"otterl, Martin Kuipers

Preventing Data Hallucinations in Agentic AI for Optical Network Troubleshooting

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An agentic AI system for automated troubleshooting in optical communication networks is demonstrated that integrates data references into the agent architecture to prevent data hallucinations. This integration improves the interpretability and trustworthiness of root‑cause identification and reasoning. The approach addresses a key challenge in deploying AI for network maintenance by reducing erroneous outputs.

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