Inspiration

The inspiration behind ResumePolish came from the challenges job seekers face when applying for internships and jobs. Many candidates struggle to tailor their resumes to specific job descriptions, identify missing keywords, and present their achievements effectively. We wanted to create an AI-powered solution that makes resume improvement easier, faster, and more accessible.

What it does

ResumePolish is an AI-powered resume optimization platform that analyzes resumes against a target job role or job description. It provides a match score, identifies missing keywords, highlights strengths, and rewrites resume bullet points using the Google X-Y-Z formula. Users can also generate a polished version of their complete resume, edit the content, and export it for future applications.

How we built it

We built ResumePolish using React and TypeScript for the frontend, Tailwind CSS for styling, and Node.js with Express for the backend. We integrated Google Gemini AI through the Google GenAI SDK to analyze resumes, improve bullet points, and generate optimized resume content. The application uses API endpoints to connect the user interface with the AI-powered backend.

Challenges we ran into

One of our main challenges was designing prompts that generate structured, relevant, and useful resume feedback. We also needed to handle different resume file formats, maintain a consistent response structure, and present AI-generated results clearly. Ensuring that rewritten content remains truthful to the candidate's actual experience is another important challenge.

Accomplishments that we're proud of

We are proud to have developed a platform that combines resume analysis, keyword identification, bullet-point improvement, and complete resume polishing in one place. The interactive dashboard makes feedback easier to understand, helping users identify areas for improvement and prepare resumes tailored to their career goals.

What we learned

Through this project, we learned how to integrate generative AI into a web application, build API-based communication between frontend and backend components, process resume content, and work with structured AI responses. We also learned the importance of prompt engineering, error handling, and responsible AI use, particularly when generating professional documents.

What's next for ResumePolish

In the future, we plan to introduce direct ATS compatibility checks, support more resume templates and languages, provide deeper job-description matching, and offer personalized career recommendations. We also aim to improve resume parsing, add downloadable formats, and evaluate recommendations against real-world hiring requirements to make ResumePolish a more reliable career-assistance platform.