NIRNAYA: An AI-Driven Intelligent Support Ticketing and Decision System

Internal IT support is an essential part of the daily operation of modern organizations. However, a considerable portion of the support process still depends on manually reading requests, identifying their type and urgency, selecting the appropriate department, and assigning them to suitable support personnel. These activities can become time-consuming when ticket volumes increase and may also result in inconsistent decisions for similar requests. The proposed system, NIRNAYA, is an AI-driven internal IT Service Management (ITSM) platform designed to assist support teams during the decision-intensive stages of ticket handling. The system uses natural language processing to analyze employee requests and generate recommendations for ticket classification, priority, department routing, and agent assignment. It also provides ticket summarization and initial resolution assistance. The platform combines a React-based user interface, Node.js/Next.js application services, PostgreSQL for persistent data storage, AI-based language processing services, and WebSocket-based real-time communication. SLA monitoring, notifications, ticket history, and operational analytics are integrated into the same workflow. A key aspect of NIRNAYA is its human-in-the-loop design. AI-generated recommendations are presented to support personnel for validation rather than being treated as final decisions. This allows the proposed system to reduce repetitive triage work while preserving human control over ticket handling. The proposed architecture incorporates AI-assisted ticket processing, structured data management, SLA monitoring, real-time communication, and operational analytics within a unified IT support workflow. NIRNAYA is presented as a system design and prototype; quantitative evaluation of prediction accuracy and operational performance is identified as an area for future work.