Personal Portfolio Builder Using Mern Stack with AI Integration
1st Kalva Ajay Kumar
Engineeringdept. of Computer Science Engineering
Parul University Vadodara, India 2303031257001@paruluniversity.ac.in
2nd Namburu Yogi Venkata Satyanarayana
Engineeringdept. of Computer Science Engineering
Parul University Vadodara, India 2203031250065@paruluniversity.ac.in
3th Karri Jeevan Kumar
Engineeringdept. of Computer Science Engineering
Parul University Vadodara, India 2203031250043@paruluniversity.ac.in
4rd Pentyala Navyanth
Engineeringdept. of Computer Science Engineering
Parul University Vadodara, India 2203031250073@paruluniversity.ac.in
Abstract—The rapid proliferation of digital platforms has heightened the need for individuals to establish a personalized online presence, making portfolio websites increasingly vital for professionals, freelancers, and students. This paper presents the design and implementation of a Personal Portfolio Builder leveraging the MERN stack—MongoDB, Express.js, React, and Node.js—integrated with Artificial Intelligence (AI) capabilities. The system provides an intuitive, interactive interface that allows users to dynamically generate and customize their personal portfolios without requiring extensive programming knowledge. The AI component enhances the platform by offering intelligent content recommendations, identifying and emphasizing users’ key skills and achievements, and optimizing portfolio layout for improved visual appeal and usability. Users can select from pre- designed templates or receive AI-driven layout suggestions based
on best practices.
A detailed analysis of functional and non-functional require- ments ensures that the system meets performance, reliability, and scalability standards. UML (Unified Modeling Language) diagrams, including use case, class, and sequence diagrams, illustrate the system architecture, highlighting the interactions between front-end components, back-end APIs, and the AI engine.
The proposed framework reduces development time by au- tomating key aspects of portfolio creation, provides personalized customization through AI-driven suggestions, and ensures scal- ability and maintainability for diverse user needs. Overall, this system represents a next-generation solution for creating highly customizable and intelligent digital portfolios, bridging the gap between technical skill, design aesthetics, and user convenience.
Index Terms—MERN Stack, Personal Portfolio, Artificial In- telligence, Web Application, System Design, Automation
