Campus Pathfinder: Practice of Automated Triage for Intelligent Service Desk Agents in Higher Education

Campus Pathfinder is an intelligent autonomous agent system for university service desks. It aims to automatically collect student needs and classify the urgency of requests through natural language dialogue, addressing issues such as long queues during peak hours, limited manual capacity, low information collection efficiency, and difficulty in identifying urgent requests in traditional service desks, thereby realizing the automation and intelligence of service desk workflows. This article will introduce the project from aspects of background, core capabilities, technical architecture, application value, etc.

University service desks are important entry points for students to obtain academic consultation, administrative affairs, technical support, mental health, and other assistance. However, the traditional model faces many challenges: long waiting times during peak hours, limited manual reception capacity, low information collection efficiency, and difficulty in quickly identifying urgent requests. The Campus Pathfinder project is an intelligent agent system designed to optimize the initial reception and triage workflow of university service desks. It collects key information through natural language dialogue with students, understands needs, classifies urgency levels, and realizes intelligent allocation of service resources.

The core capabilities of Campus Pathfinder include natural language dialogue and secure information collection.

• Natural Language Dialogue: Adopts dynamic guided dialogue (not static forms), supports colloquial, incomplete sentences, and even emotional expressions. It adjusts subsequent questions based on students' answers (e.g., course selection issues → ask about specific conflict types; anxious emotions → prioritize assessment for urgent psychological support), creating a friendly atmosphere to improve participation and information quality.
• Secure Information Collection: Emphasizes privacy protection, using identity verification (student ID/campus card, etc.), encrypted data transmission and storage, the principle of least privilege (only collecting necessary information), and supports interaction log auditing and student information deletion, complying with regulations such as GDPR and CCPA.

Demand understanding and classification are key to intelligent triage. The system maintains a multi-dimensional classification system (major categories and subcategories such as academic consultation, administrative affairs, technical support, mental health, and emergency situations) and identifies real intentions based on semantic understanding (not just keyword matching). Urgency assessment judges priority by analyzing keywords (e.g., urgent, emergency) and context (e.g.,临近 final exams), and high-priority requests are immediately routed to human specialists or emergency channels.

The automated triage function optimizes resource allocation:

• Self-service: Directly provides FAQ queries, operation guides, or resource links for common issues to reduce the pressure on front-line staff.
• Manual routing: Routes requests requiring human intervention to the most suitable personnel/department based on service category, professional field of staff, current load, and student preferences.
• Appointment scheduling: Non-urgent requests can be scheduled for subsequent consultation times, synchronized to the relevant personnel's calendar to avoid peak-hour congestion.

The technical architecture adopts a modular design:

• Dialogue Management Engine: Maintains dialogue state, manages processes, and handles multi-turn interactions (supports conditional branches, loop confirmation, and context inheritance).
• Natural Language Understanding Module: Based on large language models, provides intent recognition, entity extraction, and sentiment analysis capabilities, and understands university-specific terminology through domain adaptation training.
• Knowledge Base System: Stores service information, FAQs, and operation guides, supports fast retrieval and dynamic updates (learning and optimizing from historical dialogues).
• It also includes a classification and routing engine and an external service integration layer.

Application scenarios cover various university services: handling course selection/credit calculation consultations during registration and enrollment seasons, identifying anxious emotions and providing psychological support during exam weeks, and processing technical failures/facility maintenance requests in daily operations. The project value is reflected in: improving service efficiency and reducing waiting time, optimizing resource allocation to allow professionals to focus on high-value work, providing 7x24 instant responses, and accumulating data insights to understand student demand trends.

Future development directions include: multilingual support for international students, voice interaction to enhance communication naturalness, predictive analysis to proactively identify students in need of help, and deep integration with campus systems to provide personalized services. Campus Pathfinder provides a practical intelligent agent solution for institutions, demonstrating the application potential of AI in the field of educational services.