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Ecological Niche Modelling (ENM) is a crucial approach for understanding and predicting the distribution and behavior of species based on environmental conditions such as temperature, precipitation, or soil composition. Despite recent advances in artificial intelligence (AI), no dedicated tool currently exists that combines scientific rigor with interactive, user-friendly design for ENM. In this study, we present a new Mathematical model designed to support the scientific community in conducting robust ENM analyses. Our model, called ScorUS, leverages state-of-the-art frameworks, including large language models and agentic systems for data collection and analysis (notably Google’s Gemini 2.5), to build a multi-agent system that enables interactive and reliable modelling workflows. To ensure scientific validity, the system incorporates automated data collection pipelines that retrieve species occurrence data from GBIF and climate data from sources such as WorldClim.