📄 DocSmart — AI CV & Document Analyzer
📄 DocSmart — AI CV & Document Analyzer
Upload a CV. Paste a job description. Get a match score, missing skills, and improvement suggestions. The project everyone in the cohort will actually use.
Group size: 3-4 · Duration: 1 week · Awards: 5 categories
🎯 What you’re building
A Streamlit app where users:
- Upload their CV (PDF or image) → Textract extracts the text
- Paste a job description
- Comprehend extracts entities + key phrases
- Your matching engine compares CV skills to job-description skills
- Returns: match score (0-100), green chips for matched skills, red chips for missing, blue for extras
- Plus 3-5 personalized improvement suggestions
🛠️ AWS services
- EC2 — Streamlit app
- Textract — read CVs from PDFs and images
- Comprehend — entities + key phrases
- S3 — temporary document storage
👥 Team roles
- UI Lead — the upload form + score visualization + skill chips
- Textract Engineer — PDF/image handling + text cleaning
- Matching Engineer — the skills taxonomy + scoring algorithm + suggestions logic
- AWS & Polish Lead — EC2/IAM + demo prep
📖 The full walkthrough
Open GroupProject3_DocSmart_CV_Analyzer.html in your browser. It’s an 8-phase guided build with code, AWS setup, EC2 deployment, polish checklist, demo prep, and award criteria.
The walkthrough is self-contained — no internet needed once you have the file.
💡 Strategic tip for this project
Use your own team’s CVs as test data. Four CVs in hand on day 1, more than any other team. Anonymize them, run them through your own app — your suggestions will be smarter than teams using public sample CVs.
🏅 Awards (5 categories)
| 🎨 Most Polished | 💡 Most Innovative | 🎤 Best Demo | 📚 Best Documentation | ❤️ People’s Choice | |—|—|—|—|—|
Read the 🏆 Awards section of the walkthrough for what specifically wins each one for THIS project.