The field of recruiting is encountering considerable difficulties in effectively searching for qualified candidates. Numerous individuals employ broad-spectrum techniques that might not be relevant to their targeted roles. At the same time, employers waste countless hours evaluating applications that can lack actual competencies. Current systems frequently fail to provide appropriate feedback, neglecting other vital qualities like communication, logical reasoning, and cultural fit. In this paper, we introduce PrepWise, a system powered by artificial intelligence that creates personalized interviews that enable recruiters to better evaluate candidates. PrepWise uses the contents of a resume and a desired position to generate pertinent interview questions, followed by the evaluation of the candidate’s answers through a structured rubric. Our platform is modular and consists of a React frontend, a Node.js backend, and a PostgreSQL database. We leverage large language models through the OpenRouter API to provide candidates with feedback based on multiple criteria, including technical proficiency, communication, and problem-solving skills. Additionally, PrepWise supports various functions such as parsing resumes, finding suitable jobs, and monitoring individual performance. Our experiments show that our platform improves candidates’ interview preparedness and skill recognition.

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