Tools for Building a Chatbot for the Admissions Commission of an University

In the context of the rapid digitalization of educational processes, automation of interaction with applicants is becoming a priority task for universities. This article is devoted to the analysis of various approaches to the development of chatbots for the admissions committee. Both traditional methods based on rules and keywords, and modern technologies using machine learning and large language models are considered. Particular attention is paid to comparing the accuracy, relevance and naturalness of responses, as well as implementation and support costs. The study shows that modern neural network models are significantly superior to classical approaches in a number of key parameters, but require large resources and constant Internet access. Combining classical and neural network methods can be the optimal solution, allowing you to effectively use the strengths of both approaches, while ensuring high quality and efficiency of interaction with applicants.