Retrieval-augmented generation based orchestrated multi-agent system for intelligent student support

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Authors: Kavitha Soppari, B Anjan Kumar, Mohd Adnan, Anurag Sharma
Cited by: 0

Abstract

The AI-Powered Multi-Agent College Support System delivers intelligent conversational assistance via a LangGraph orchestration framework that intelligently routes natural language queries through a central Orchestration Agent powered by advanced LLM models to four specialized downstream agents. These include the FAQ Agent leveraging FAISS-powered RAG for rapid institutional knowledge retrieval, Email Agent with seamless SendGrid integration for automated notifications, Raise Ticket Agent managing structured support workflows, and Contact Faculty Agent enabling targeted academic communications. The architecture ensures multi-tenant conversation persistence through privacy-isolated session management, robust multi-turn slot-filling for complex interactions, and mandatory confirmation protocols for sensitive operations. Deployed on a scalable Flask/React stack with PostgreSQL for structured data and FAISS for vector search, the system achieves production-grade reliability through intelligent intent classification and collaborative agent specialization, providing comprehensive student support across diverse institutional workflows.

Fields of Study & Subjects

AI in Service Interactions Artificial Intelligence in Education Intelligent Tutoring Systems and Adaptive Learning

Publication details

Journal / source
World Journal of Advanced Research and Reviews
Volume
29
Issue
3
Pages
467–472
Publication date
10 March 2026
Language
EN