PathBridge 2.0: An AI-driven, GraphQL-enhanced plugin-based academic networking ecosystem for student-alumni collaboration
Abstract
PathBridge 2.0 is a next-generation academic net-working ecosystem created to overcome existing university portals and third-party networking platforms, which tend to lack Personalization, extensibility, and integrated AI support. Modern Students need dynamic mentoring and real-time collaboration. AI-driven guidance in ideation, project development, and academic skill-building, needs which the fragmented existing systems fail to satisfy. PathBridge 2.0 offers a unique, integrated, Module-based solution developed with hybrid REST–GraphQL. architecture that assuredly allows for efficient data retrieval. improved scalability and smooth communication among its microservices. Its plug-in framework is extensible, where an Institution can add or build custom academic tools easily. An AI microservices layer powered by Gemini provides real-time ideation guidance, automated content generation, and personalized academic support. This platform has a plug-in marketplace; mentorship interfaces that are interactive, asynchronous task execution using Redis queues, and secure, cloud-native data storage using Supabase. Tests conducted on a cohort of students and alumni The students show a significant improvement in ideation efficiency. Engagement, Portfolio Development, and Mentor Participation as compared to traditional academic networking systems. With its It features a scalable design, strong extensibility, and is ready for deployment. targeted at institutions, PathBridge 2.0 lays a robust foundation for to facilitate academic collaboration, productivity, and personalization Learning in modern learning environments. Index Terms-GraphQL, FastAPI, Gemini AI, Supabase, Plugin Architecture, Mentorship Platforms, Educational Technology.
Fields of Study & Subjects
Mobile and Web Applications
Artificial Intelligence in Education
Edcuational Technology Systems
Publication details
- Journal / source
- International Conference on Computational Intelligence in Data Science (ICCIDS)
- Pages
- 1–6
- Publication date
- 8 January 2026
- Language
- EN