Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{196664,
        author = {Siddhant Gondane and Anuj Pande and Aryan Rathod and Shaivik Shende and Anand Chaudhari and Sunil Gupta},
        title = {Intelligent Campus Assistant: A Hybrid Agentic Retrieval-Augmented Generation Architecture for Dynamic Information Retrieval in Higher Education},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {4444-4448},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196664},
        abstract = {Implementation of Artificial Intelligence (AI) in terms of higher education administration is a paradigm shift with the stagnant information repositories being replaced by an interactive and conversational-based interface. Nonetheless, current conversational AI applications in the university setting have a bottleneck of freshness. Although traditional Retrieval-Augmented Generation (RAG) is useful in managing high inertia data, e.g., academic regulations and course syllabi, it often misses capturing low inertia real time updates like an impromptu schedule change, an event announcement or emergencies because of the latency incurred during the indexing of vectors and the stochastic nature of semantic retrieval. The concept proposed in this paper is that of the Intelligent Campus Assistant, a new conversational agent which uses a Hybrid Data Architecture and a Tool-Calling Agentic framework. In contrast to weak ReAct-based agents that tend to get stuck in reasoning loops and hallucinate, our system makes use of the deterministic tool-calling properties of modern Large Language Models (in the case Llama 3) to route queries dynamically between a static vector database (ChromaDB) and a dynamic, real time, and controllable by an administrator notice store. We suggest a scalable solution to the problem of the long tail of administrative student queries by decoupling the consumption of long-term knowledge and short-term updates and coordinating them with the help of a logic-aware agent. This paper has described the dual-source retrieval system and how stochastic reasoning is replaced by structured invocation of tools and the consequences of this architecture to institutional resilience, information trustworthiness and administrative efficacy.},
        keywords = {Retrieval-Augmented Generation (RAG), Agentic AI, Tool-Calling Framework, Large Language Models (LLMs), Vector Databases (ChromaDB), Real-Time RAG, Semantic Search Hallucination Mitigation, Llama 3.},
        month = {April},
        }