Smart Career Assistance Portal Using AI and Real-Time Industry Insights

Abstract

As industries evolve rapidly, students and early-career professionals face increasing challenges in aligning their academic profiles with current market demands. Traditional career guidance systems often lack personalization, adaptability, and real-time insights. This paper presents an AI-powered career guidance platform designed to bridge this gap by offering an integrated set of tools, including an ATS-optimized resume builder, an intelligent cover letter generator, mock interview preparation, and weekly-updated industry insights. Built using Next.js and Shadcn UI, the platform features a responsive and intuitive user interface. Upon email-based login via Clerk authentication, users complete a profile form that captures their industry, specialization, experience, skills, and professional bio. The system then generates a dynamic dashboard displaying in-demand skills and salary trends using data fetched weekly through Inngest. Resume generation is fully customizable and enhanced with AI-generated content tailored to the user’s domain. The intelligent cover letter module analyses job descriptions to craft role-specific documents. A mock interview module presents domain-aligned quizzes, tracks user progress across sessions, and provides AI-driven improvement suggestions. Content generation is powered by the Gemini API, a transformer-based model developed by Google. At the same time, a custom matching algorithm scores how well a user’s skills align with various job roles. Preliminary evaluations indicate improved job readiness, user engagement, and satisfaction. By unifying real-time labour analytics with AI-enhanced preparation tools, this system supports informed career decision-making and offers a scalable, personalized solution for modern employability challenges.

Introduction

Problem:
Career decision-making is challenging due to the dynamic job market and generic, outdated traditional career guidance systems that do not personalize advice or reflect real-time industry needs. Graduates often struggle to align their skills with employer demands and prepare effective applications.

Solution:
The paper proposes a Smart Career Assistant Portal that integrates AI-driven features to provide personalized, real-time career support. Key features include:

• ATS-optimized Resume Builder: Generates tailored resumes matching user profiles and industry standards.

• Personalized Cover Letter Generator: Creates job-specific cover letters by analyzing job descriptions.

• Mock Interview System: Offers role-specific practice questions, tracks performance, and gives feedback.

• Industry Insights Dashboard: Displays weekly-updated labor market trends, in-demand skills, and salary data.

Technology Stack:
Built with React 19, Next.js 15 (frontend/backend), TailwindCSS, ShadcnUI for UI, NeonDB with Prisma ORM for database, and uses Gemini API for AI content generation. Inngest handles automated data updates; Clerk provides secure user authentication.

Methodology:
Users authenticate and complete profiles detailing industry, skills, experience, and goals. AI modules generate personalized career content based on this data. The platform continuously updates industry trends to ensure relevant recommendations. A simple matching algorithm evaluates skill fit with job roles.

Evaluation and Results:
Tested with final-year engineering students, the platform demonstrated:

• Efficient generation of customized, ATS-friendly resumes and cover letters.

• Effective mock interview practice with iterative feedback improving user confidence.

• Up-to-date labor market insights helping users adapt skills.

• Skill gap analysis offering targeted career development suggestions.

Advantages and Applications:

• Modular, scalable, and SEO-optimized web architecture enables fast, responsive user experience.

• Type-safe backend reduces errors and improves maintainability.

• Suitable for real-time, personalized career guidance and job readiness tools.

Conclusion

The Smart Career Assistant Portal presented in this paper demonstrates the effectiveness of integrating artificial intelligence with real-time labour market analytics to enhance career readiness among students and early professionals. Unlike traditional guidance methods, this system personalizes the user experience by leveraging technologies such as Next.js, Prisma ORM, NeonDB, Gemini API, and Inngest. It enables secure onboarding, profile completion, and access to tools including an ATS-optimized resume builder, intelligent cover letter generator, industry insights dashboard, and mock interview module. The AI adapts content to each user’s profile, offering tailored outputs and actionable suggestions based on individual inputs and preferences.Pilot testing demonstrated increased user satisfaction, faster resume preparation, and better alignment with job applications. By identifying skill gaps and updating trends weekly, the system supports both short-term readiness and long-term career growth. This study affirms the role of AI in bridging the gap between academic learning and modern employability in a dynamic job market.

References

[1] M. Jawhar, J. R. Miller, Z. Bitar, and S. Jawhar, \"AI-Powered Customized University and Career Guidance,\" 2024 Intermountain Engineering Technology and Computing (IETC), Salt Lake City, UT, USA, 2024, pp. 157-161, doi: 10.1109/IETC61393.2024.10564423. [2] M. Ghuge, A. Kumari, T. Kamble, V. Raikwar and A. Mandrawliya, \"Envisioning Tomorrow: AI Powered Career Counseling,\" 2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Bengaluru, India, 2023, pp. 377–383, doi: 10.1109/ICIMIA60377.2023.10426016. [3] S. Prathibha, G. Shamini, S. Dharshini, and U. Rusitha, \"Careex – An AI Assisted Career Guidance and Eligibility Prediction System,\" 2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS), Chennai, India, 2023, pp. 1–6, doi: 10.1109/ICCEBS58601.2023.10448609. [4] S. Shilaskar, S. Bhatlawande, P. Sawle, S. Gupta, and R. Buche, \"Conversational AI for Career Counseling,\" 2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon), Pune, India, 2024, pp. 1–4, doi: 10.1109/MITADTSoCiCon60330.2024.10575379. [5] N. N. B. Norazri, F. Mohamed, I. F. A. M. Albakri, V. S. Chan, M. K. Mokhtar and M. N. A. Nor’a, \"Simventure: Utilizing First Person Player Technology for Career Guidance in High Schools,\" 2024 International Conference on TVET Excellence & Development (ICTeD), Melaka, Malaysia, 2024, pp. 38–43, doi: 10.1109/ICTeD62334.2024.10844602. [6] A. Deshpande, A. Navatre, A. Dubey, U. Gurav, A. Dhavale, and A. K. Chanchal, \"Implementation of an NLP-Driven Chatbot and ML Algorithms for Career Counseling,\" 2024 7th International Conference on Inventive Computation Technologies (ICICT), Kolhapur, India, 2024, pp. 853–859, doi:10.1109/ICICT60155.2024.10544511. [7] A. T. K. Arshad, D. Mohammed, A. Arjun, A. M. Anshad, and J. C. A., \"VocaVisionary: A Career Guidance Chatbot,\" 2024 Second International Conference on Advances in Information Technology (ICAIT), Malappuram, India, 2024, pp. 1–6, doi:10.1109/ICAIT61638.2024.10690595. [8] R. Kumbhar, M. M. Maddel and Y. Raut, \"Smart Model for Career Guidance Using Hybrid Deep Learning Technique,\" 2023 1st International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP), Pune, India, 2023, pp. 1–6, doi: 10.1109/IHCSP56702.2023.10127152

Copyright

Copyright © 2025 Sameeha Afrin A, Rasheeda Reeshman M, Safrin Shahana A, Revathi D, Sugantha S. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.