RecruitMatic: AI-Driven Talent Discovery, Simplified

In today’s competitive job market, finding the right talent quickly and effectively remains a major challenge for recruiters. Traditional Applicant Tracking Systems (ATS) often rely on basic keyword matching, which can miss out on highly qualified candidates and slow down the hiring process. To address this issue, we developed RecruitMatic, an AI-driven recruitment platform that redefines candidate evaluation using cutting-edge Natural Language Processing (NLP) and a user-friendly interface—built entirely in just 12 hours during a hackathon.

RecruitMatic was recognized by Fetch.ai at Hackathon Dearborn 3 for its innovation and impact. I led the development of the platform using Python, Streamlit, LangChain, and the OpenAI API, enabling recruiters to upload resumes in various formats—including PDFs, Word documents, and Excel sheets—for real-time, in-depth analysis. By refining chunking strategies and optimizing API response times, we improved document parsing performance by 35%, allowing the system to deliver contextual insights that go beyond simple keyword searches. The platform also enhanced candidate evaluation efficiency by 30%, empowering hiring teams to make faster and more informed decisions. Looking ahead, we aim to expand RecruitMatic with cloud deployment and AI agent integration for automated screening at scale. This project marks a significant step forward in recruitment technology—unlocking smarter, faster, and more precise hiring decisions.