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AI & Full StackDec 2025 – Mar 2026

Smart Resume AI

Edunet Foundation

PythonStreamlitPostgreSQLSQLAlchemyGroq APIDockerbcrypt

01 Explanation

An AI-powered career optimization platform that helps job seekers beat Applicant Tracking Systems and land their dream jobs — targeting 95%+ ATS compatibility with real-time scoring. Most people don't know their resume is getting rejected by a machine before a human ever reads it. This project makes that invisible problem visible and actionable.

02 Implementation

75% of resumes get rejected by ATS bots before reaching a real recruiter. I wanted to build something that gives job seekers a real ATS score with specific, actionable feedback — not a vague 'add more keywords' suggestion. Orchestrated a full-stack architecture using Python and Streamlit on the frontend, securely powered by PostgreSQL and containerized with Docker. Developed an AI Resume Builder and Cover Letter Generator tailored directly to job descriptions using the Groq API. Overcame complex AI prompt engineering and latency constraints to provide accurate, real-time keyword matching and scoring. Passwords are hashed with bcrypt and database migrations handled cleanly through Alembic.

03 Issue Resolution

Solved the critical problem where 75% of resumes get rejected by typical ATS bots before reaching humans. Overcame complex AI prompt and latency constraints to provide accurate, real-time keyword matching and scoring for candidate portfolios. Mitigated data security concerns with bcrypt password hashing and role-separated admin and user systems.