Abstract:
The paper presents the development of a Knowledge-based Intelligence for Sustainability Assessment (KISA) system for the comprehensive assessment of the sustainability of Russian regions, which uses a large language model (LLM) with retrieval-augmented generation (RAG) technology and Rosstat data. KISA automatically selects relevant indicators based on users’ textual queries, determines their weights, and calculates regional ratings, overcoming the limitations of traditional methods associated with high resource costs, subjectivity, and low adaptability. The system reduces the time required for rating formation to 10 minutes – 140 times faster than existing approaches; financial costs are reduced by a factor of 16 due to the minimization of expert participation. The agreement with expert evaluations is 68%, confirming the validity of the method. KISA provides a web interface with map visualization, enhancing flexibility in analysis; the possibility of improvement through the addition of new sources ensures the continuous incorporating experts’ experience. The results of the study contribute to the improvement of regional sustainability assessment and can be used in management decision-making.
Keywords:sustainability assessment, Russian regions, artificial intelligence, large language model LLM, retrieval-augmented generation RAG