📄 AI-ATS Engine

AI-ATS Engine is a full-stack AI-powered Applicant Tracking System (ATS) that evaluates resumes against job descriptions using natural language understanding models and provides insightful match scores, skill highlights, and feedback to improve candidacy. It is designed to assist job seekers and recruiters alike in streamlining the resume review process.

Live Demo: https://jobmatch-ai-beta.vercel.app/

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🔍 Project Overview

An Applicant Tracking System (ATS) is software that helps handle recruitment workflows, resume parsing, candidate matching, and evaluation intelligently. AI-ATS Engine extends this concept by integrating AI models to analyze text semantics, quantify resume-to-job matches, and provide actionable guidance.

This project contains:

• Frontend: User interface for resume upload, job description input, and AI feedback visualization
• Backend API: RESTful Node.js server processing inputs, integrating AI scoring logic
• AI Integration: Utilizes NLP/LLM services for semantic comparison and insights
• Database Support: (Optional) Storage for users, resumes, and historic reports

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🧠 Key Features

• ✅ AI-Driven Resume Evaluation
  Compare resume text against a job description using semantic similarity and keyword relevance.

• ✅ Match Score Generation
  Produce a percentage match and confidence level.

• ✅ Skill & Keyword Highlighting
  Identify missing skills and important keywords relevant to the role.

• ✅ User-Friendly UI
  Upload resumes, input job descriptions, and view intelligent insights.

• ✅ Extendable API
  Modular backend routes to add new models, analytics, or storage.

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📦 Architecture

├── client/                   # Frontend (React)
│   ├── public/
│   └── src/
├── controllers/              # Route logic
├── middleware/               # Auth, error handling
├── models/                   # Data schemas
├── routes/                   # API endpoints
├── server.js                 # Express server entry
├── .env.example              # Environment config example
└── package.json              # Backend dependencies

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🛠️ Tech Stack

Layer	Technology
Frontend	React, HTML, CSS
Backend	Node.js, Express
AI / NLP	OpenAI / Gemini (env-configurable)
Database	(Optional) MongoDB / PostgreSQL
Deployment	Vercel, Render / Heroku

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🚀 Installation – Setup

1. Clone the Repository

git clone https://github.com/Yeshwanth-kr/ai-ats-engine.git
cd ai-ats-engine

2. Backend Setup

npm install

Create a .env file based on .env.example:

PORT=5000
OPENAI_API_KEY=your_api_key_here

Start the backend server:

npm run start

3. Frontend Setup

cd client
npm install
npm run start

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📌 Usage

1. Upload Resume
   Upload your resume in PDF or text format using the application interface.

2. Provide Job Description
   Paste the job description of the role you are targeting into the input field.

3. Run AI Analysis
   Click the Analyze button to evaluate the resume against the job description.

4. Review Results
   The system will generate:

   • Resume–job match score
   • Missing or weak skills
   • Keyword alignment insights
   • Actionable suggestions to improve the resume

Sample Output

Resume Match Score: 82%
Missing Skills: React, Docker
Suggestions:
- Add measurable achievements
- Include role-specific keywords

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🧪 Testing

Testing support can be added using frameworks like Jest or Cypress.

npm run test

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📈 Roadmap

• Improve AI matching accuracy
• Recruiter analytics dashboard
• Authentication and user profiles
• Batch resume analysis
• Resume history and reports

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🤝 Contributing

Contributions are welcome.

1. Fork the repository
2. Create a feature branch

   git checkout -b feature/my-feature

3. Commit your changes

   git commit -m "feat: add new feature"

4. Push to your branch and open a Pull Request

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📜 License

This project is licensed under the MIT License.

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📞 Contact

Yeshwanth Krishna

• LinkedIn: linkedin.com/in/Yeshwanth-Kr
• GitHub: github.com/Yeshwanth-kr
• Portfolio: yeshwanth.online