An enterprise-grade ATS simulation engine that reverse-engineers resume scoring logic
from platforms like Workday, Taleo, iCIMS, Greenhouse, Lever, and SuccessFactors.
Built with React 19, TypeScript, and powered by Google Gemini 1.5 Flash.
🚀 Live Demo · Report Bug · Request Feature
📑 Table of Contents
Traditional resume checkers give you generic advice. ATSify gives you deterministic simulation.
It analyzes resume depth, formatting risks, and keyword density against a specific job description, then generates parallel compatibility scores across 6 major enterprise ATS platforms simultaneously. The AI-driven Intelligence Scanner identifies future-dated entries, quantified achievement gaps, and formatting hazards that prevent recruiters from ever seeing your data.
- 🎬 Cinematic Startup — Multi-phase holographic initialization sequence (Globe → Data Extraction → System Ready)
- 🖥️ Multi-System Simulation — Parallel scoring for Workday, Taleo, iCIMS, Greenhouse, Lever, and SuccessFactors
- 🔍 Deep Skill Parsing — NLP-powered keyword extraction with TF-IDF scoring and skills taxonomy matching
- 📊 Priority Focus Areas — Interactive, expandable analysis of Formatting, Experience Quality, and Section Structure
- 🤖 AI-Powered Insights — Gemini 1.5 Flash for nuanced understanding of experience impact beyond keyword matching
- 🔐 Persistence — Firebase Auth + Firestore for user accounts and scan history
- 📄 Export — PDF report generation via jsPDF + html-to-image for offline review
- 📱 Responsive — Optimized for ultra-wide displays (1600px+) and fully responsive down to mobile
| Layer | Technology |
|---|---|
| Frontend | React 19, TypeScript, Vite 6 |
| AI Engine | Google Gemini 1.5 Flash (@google/genai) |
| Auth / DB | Firebase Auth, Firestore |
| Styling | Tailwind CSS v4, Motion (Framer Motion) |
| NLP | Custom TF-IDF, tokenizer, skills taxonomy, synonym matching |
| pdfjs-dist (parse), jsPDF + html-to-image (export) | |
| Icons | Lucide React |
| Server | Express (dev proxy + production serve) |
| Tooling | tsx, TypeScript, Vitest |
| Deployment | GitHub Pages (CI/CD via Actions) |
flowchart TD
A["App Init"] --> B["IntroScreen (Cinematic)"]
B --> C["SignInPage / Landing"]
C --> D["ScannerSection"]
D --> E["PDF / DOCX / Text Parser"]
E --> F["NLP Pipeline (TF-IDF + Taxonomy)"]
F --> G["Gemini AI Metadata Extraction"]
G --> H["Deterministic Scorer Engine"]
H --> I["Platform-Specific Rules (×6)"]
I --> J["Results Dashboard"]
J --> K["Firestore Persistence"]
J --> L["PDF Export Engine"]
Prerequisites
- Node.js 20+
- Gemini API Key (get one here)
- Firebase Project (optional — for auth & persistence)
Install and run
git clone https://github.com/Rudra-P9/ATSify.git
cd ATSify
npm install
npm run devThe dev server starts at http://localhost:3000 with Vite HMR via the Express proxy.
Build for production
npm run build
npm run previewCreate a .env file in the project root (see .env.example):
# Required — Gemini AI
GEMINI_API_KEY=your_gemini_key_here
# Optional — Firebase (for auth & scan history)
VITE_FIREBASE_API_KEY=...
VITE_FIREBASE_AUTH_DOMAIN=...
VITE_FIREBASE_PROJECT_ID=...| Script | Description |
|---|---|
npm run dev |
Start Express + Vite dev server on port 3000 |
npm run build |
Production build via Vite |
npm run preview |
Preview the production build locally |
npm run lint |
TypeScript type-checking (tsc --noEmit) |
npm run test |
Run tests with Vitest |
npm run clean |
Remove the dist directory |
ATSify/
├── api/
│ └── analyze.ts # Gemini analysis serverless handler
├── src/
│ ├── components/
│ │ ├── features/
│ │ │ ├── IntroScreen.tsx # Multi-phase holographic entry
│ │ │ ├── ScannerSection.tsx
│ │ │ ├── JDInput.tsx
│ │ │ ├── ResumeTextInput.tsx
│ │ │ └── SignInPage.tsx
│ │ ├── layout/
│ │ │ ├── Footer.tsx
│ │ │ └── StaticPage.tsx
│ │ └── ui/
│ │ ├── Loading.tsx # "Reactor Core" scan animation
│ │ ├── PlatformCard.tsx
│ │ ├── PlatformGrid.tsx
│ │ └── ScoreHeader.tsx
│ ├── lib/
│ │ ├── gemini/ # Prompts & metadata extraction
│ │ ├── nlp/ # TF-IDF, tokenizer, skills taxonomy
│ │ ├── parser/ # PDF, DOCX, section & contact extraction
│ │ ├── pipeline/ # Main analyzeResume orchestrator
│ │ ├── platforms/ # Workday, Taleo, iCIMS, Greenhouse, Lever, SAP
│ │ ├── report/ # Report generation & thresholds
│ │ ├── scorer/ # Keyword, format, experience, education, section scoring
│ │ └── utils.ts
│ ├── store/ # State management (analysis, resume, scores, JD library)
│ ├── App.tsx
│ ├── main.tsx
│ └── index.css # Tailwind v4 + custom animations
├── server.ts # Express dev server with Vite middleware
├── firestore.rules # Security rules
├── firebase-blueprint.json # Data structure reference
├── .github/workflows/
│ └── deploy.yml # GitHub Pages CI/CD
├── vite.config.ts
├── tsconfig.json
└── package.json
The app deploys automatically to GitHub Pages on every push to main via the included GitHub Actions workflow.
The workflow runs npm ci → npm run build → uploads the dist/ artifact → deploys to Pages. The GEMINI_API_KEY is injected from repository secrets at build time.
For self-hosted or alternative deployments, the Express server in server.ts serves the built assets in production mode and can be deployed to any Node.js hosting provider.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'feat: add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
|
Rudra Patel Computer Science — University of South Carolina Portfolio • LinkedIn • GitHub • Email |
| ⭐ If ATSify helped you land an interview, consider starring the repo! | |
Distributed under the MIT License. See LICENSE for more information.
- Email: rudra.patel70@yahoo.com
- LinkedIn: linkedin.com/in/rudrap9
- Portfolio: rudrap9.vercel.app
- Instagram: @rudra_p9
- Buy Me a Coffee: buymeacoffee.com/rudrap9