Conversational agent with integrated tracking based on generative AI considering the effect of document order and structure

This article describes the development of a conversational agent for managing and tracking academic procedures. Based on requirements analysis, the essential components were defined to provide real-time updates on processes and improve the user experience. The development phases included dialogue flow design, training with Generative Artificial Intelligence (GAI), implementation of a data warehouse, generators, database integration, a web interface, and a module. Follow-up. A crucial aspect was the importance of data order and structure. Standardization and organization of training content are fundamental to ensuring the accuracy and relevance of responses. The solution coherently articulates the components, ensuring robust interconnections. The follow-up module expands the agent's capabilities, offering comprehensive, efficient, and personalized interaction. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1267Dimensions.Open Alex.