Saieda's Summer Research - Chameleon Concierge: Retrieval-Augmented Generation (RAG) To Enhance Open Testbed Documentation

Chameleon Concierge uses Retrieval-Augmented Generation to help researchers navigate complex open science testbed documentation. When designing experiments, researchers struggle to find technical solutions across multiple documentation sources, often leading to support tickets or project abandonment. Our custom LLM search service generates accurate, cited responses to natural language queries. Results show RAG models perform comparably to proprietary LLMs while bridging the gap between researcher knowledge and static documentation, improving research productivity and infrastructure operations.

Moreover, this poster was also accepted to ACM-SRC (student research competition) for SC25!