An Interactive Alumni Website for Educational Institutions
The Alumni Management System plays a crucial role in strengthening the relationship between educational institutions and their graduates. This research paper presents the design and development of a web-based Alumni Management System that provides a centralized platform for managing alumni data, enhancing communication, and fostering professional networking. The proposed system integrates a structured alumni database containing academic records, career achievements, and contact information, enabling efficient data retrieval and management. The system incorporates key modules such as alumni directory, event management, and communication tools. These features facilitate updates about reunions, seminars, and networking events, thereby improving alumni engagement. Additionally, the platform supports secure access and user-friendly interfaces, ensuring accessibility for both administrators and alumni. In addition, the system integrates an intelligent chatbot module designed to provide real-time assistance to students by addressing queries related to career opportunities, alumni interaction, and platform usage. This feature enhances user experience by offering instant support, reducing dependency on manual communication, and improving system accessibility. Overall, the proposed solution ensures secure access, scalability, and improved user engagement, effectively bridging the gap between students and alumni while supporting institutional growth and long-term collaboration. By leveraging modern web technologies, the system enhances institutional connectivity, promotes knowledge sharing, and builds a collaborative alumni ecosystem. The proposed solution addresses the limitations of traditional alumni tracking methods and provides a scalable and efficient approach for long-term alumni relationship management.
Authors
- Vaishnavi Gawande
- Ankita V. Pande
- Gauri Kutarmare
- Shejal Kolhe
- Dhanshri Wangal
- Shrutika Badode
Institutions
- Sant Gadge Baba Amravati University (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-04-02
- DOI
- https://doi.org/10.5281/zenodo.19379008
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00