ResumeBoost AI

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  Home page / hero screen — ResumeBoost AI Pro dashboard — land more interviews with a fully offline AI career toolkit

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  Resume Analyzer results — Resume Analyzer: instant scoring for impact, ATS-readiness, and readability using rule-based NLP

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  Resume Analyzer breakdown cards — Detailed writing quality breakdown — action verbs, weak verbs, passive voice, and filler word detection

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  ATS matched/missing keyword chips — Keyword match visualization showing ATS compatibility score and keyword density

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  ATS Job Match page — ATS Job Match: paste any job description to see matched vs. missing keywords instantly

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  Resume Rewrite before/after — Resume Rewrite engine: weak bullet points automatically strengthened with powerful action verbs

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  Interview Coach questions — Interview Coach: HR, Technical, and Behavioral questions generated by difficulty level

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  Career Roadmap 30-day plan — Personalized 30-day Career Roadmap generated from your resume analysis results

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  Career Dashboard — Career Dashboard: a full readiness snapshot — resume quality, ATS score, communication, and confidence

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  Job Scam Detector — Job Scam Detector flags red flags like urgency pressure, fake recruiters, and payment requests

Inspiration

Job hunting can be stressful, especially for students and first-time job seekers. Many people struggle to write strong resumes, pass Applicant Tracking Systems (ATS), identify fake job offers, and prepare for interviews. I wanted to build a simple tool that makes these tasks easier and helps people feel more confident in their job search.

What it does

ResumeBoost AI is an all-in-one career assistant with four main features:

• Resume Bullet Checker that analyzes resume bullet points and suggests stronger improvements.
• ATS Resume Matcher that compares a resume with a job description and identifies missing keywords.
• Job Scam Detector that checks job advertisements for common scam warning signs.
• Interview Preparation that generates interview questions based on a job description.

The application works locally using rule-based text analysis without requiring external AI APIs.

How we built it

I built ResumeBoost AI using Python and Streamlit. The application uses regular expressions and rule-based natural language processing techniques to analyze text and provide useful feedback. GitHub was used for version control, and Streamlit Cloud was used to deploy the application.

Challenges we ran into

One of the biggest challenges was building and debugging the project using only an Android phone. I also had to solve deployment issues, GitHub Codespaces limitations, and several bugs while developing the application. These challenges taught me a lot about debugging, Git, and deploying Python applications.

Accomplishments that we're proud of

• Built a complete career toolkit in one application.
• Successfully deployed the project online.
• Combined resume analysis, ATS matching, scam detection, and interview preparation into a single platform.

• Completed the project despite developing on a mobile phone.

  What we learned

  This project improved my Python programming, Streamlit development, debugging, GitHub workflow, deployment, and problem-solving skills. It also taught me how to design software that solves real-world problems.

  What's next for ResumeBoost AI

  Future improvements include:

• AI-powered resume optimization with personalized suggestions.

• Cover letter generator tailored to specific job descriptions.

• LinkedIn profile analyzer with optimization tips.

• Personalized career recommendations based on user skills.

• Support for multiple languages.

• Advanced ATS scoring and industry-specific resume feedback.

Built With

• ai
• analysis
• ats
• career
• expressions
• github
• language
• natural
• processing
• python
• regular
• resume
• rule-based
• streamlit
• text