CareerAlytics Placement Engine

Every day, as technology advances, manual tasks are swiftly being taken over by more efficient and automated systems. Colleges are adopting this digital system to improve their college-related placement activities. This system provides an AI platform that benefits both the college and the students to enhance their placement operations. The application provides two separate dashboards for students and placement officers. Students can register and login to the system and can see all the jobs opportunities and apply for these jobs only when they meet their required criteria. Students can view the details of all the students placed year-wise and branch-wise. This system also provides a platform where students can interact with placed students and get information about the company placement and its process. The application offers students a platform where they can upload their resumes and receive improvement suggestions on their resumes, and they will get job recommendations based on their skills and tech-stack mentioned in their resumes. The system provides a platform where students can generate resumes based on their tech stack and skills, make necessary changes, and generate a resume. The application offers students a platform where they can prepare topic-based questions for interviews and can also ask follow-up questions and their details using AI. The platform helps students prepare for their interviews, where they can prepare for both written and AI-based interviews and receive feedback on each answer and overall interview performance, with the system indicating areas of improvement. Placement officers can login to the system and manage and see detailed reports of placement branch-wise and year-wise placement percentages. Placement officers can create company visits and can reject or approve the applications based on their selection in the company. The platform also provides a comprehensive analytics dashboard where every placement detail is shown using graphs and charts, which helps in detailed reviews. The technologies used for this are Spring Boot and GROQ AI for the backend and React for the frontend.