Students and professionals today face significant challenges when navigating their career trajectories due to the extreme fragmentation of guidance tools. Existing platforms typically offer either scattered college searches, rigid keyword-based job portals, or static personality quizzes, leaving users without a cohesive, actionable pathway. To resolve this, we developed the AI Career System—a centralized, intelligent web application utilizing a 3-Tier MVC architecture. The system integrates five core modules: an AI Resume Builder using dynamic PDF rendering, a localized College Finder, a Real-Time Job Portal, a Machine Learning-powered Career Recommendation engine, and a Generative AI Chatbot. By implementing Scikit-learn for TF-IDF vectorization and Cosine Similarity, the system shifts from basic keyword querying to mathematical intent-matching. System testing demonstrated high accuracy in career matching and sub-second rendering speeds for dynamic PDF generation, proving that combining local Machine Learning with external Generative APIs creates a highly effective, unified career guidance ecosystem.
Naikwadia et al. (Sat,) studied this question.