Inspiration
Traditional resume builders are overly complicated, forcing users through rigid templates and multi-step wizards. We wanted to create something that makes managing resumes as simple as managing files—fast, flexible, and intelligent.
What it does
RMS lets users upload one master resume, organize target roles and companies, and automatically generate AI-tailored versions. Instead of recreating resumes each time, users manage and optimize a single base document.
How we built it
RMS lets users upload one master resume, organize target roles and companies, and automatically generate AI-tailored versions. Instead of recreating resumes each time, users manage and optimize a single base document.
Challenges we ran into
• Designing a smooth AI integration pipeline between frontend and backend
• Handling file uploads and structured data extraction from various resume formats
• Ensuring generated resumes maintain formatting consistency
Accomplishments that we're proud of
• Built a fully functional prototype within a hackathon timeframe
• Integrated AI to intelligently tailor resumes with context awareness
• Designed a minimalist yet powerful resume management workflow
What we learned
We learned how to effectively integrate AI APIs with full-stack applications, optimize prompt design for structured outputs, and create a better UX by focusing on simplicity over feature overload.
What's next for RMS - Resume Management System
• ATS keyword optimization suggestions • Cloud resume storage with version tracking • Analytics showing which resume versions perform best • Better resume formatting using rendercv • Built-in Latex-textEditor • Add different graphs for different seasons of application (e.g., Winter, Summer, Spring)
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