InterviewIQ is a state-of-the-art, AI-powered mock interview preparation platform designed to help candidates build confidence, refine their communication skills, and ace real-world job interviews. By combining AI-driven resume parsing, customized question generation, interactive voice-synchronized avatars, and instant performance feedback, InterviewIQ.AI acts as a personal, 24/7 mock interviewer.
🔗 Live Website: https://interviewiq-client-tbtt.onrender.com/
- 📄 AI Resume Analyzer: Upload your resume in PDF format. The backend extracts text using
pdfjs-distand leverages OpenAI'sgpt-4o-mini(via OpenRouter) to identify your roles, experience level, core projects, and technical skills automatically. - ⚙️ Customizable Interview Sessions: Set up tailored mock interviews. Choose your target role, experience, and mode (Technical or HR), or use the auto-extracted resume details.
- 🎭 Real-Time Voice & Video Avatars:
- Live animated female/male AI avatars (
female-ai.mp4/male-ai.mp4) that are synchronized with the Speech Synthesis. - Interactive speech options using the browser's Web Speech API (
webkitSpeechRecognitionfor speech-to-text response tracking andspeechSynthesisfor natural voice pacing). - Time-limited questions categorized by a structured difficulty curve:
- Question 1 & 2 → Easy (60-second limit)
- Question 3 & 4 → Medium (90-second limit)
- Question 5 → Hard (120-second limit)
- Live animated female/male AI avatars (
- 📊 Real-time AI Evaluation: Submissions are graded immediately on a scale of
0-10across three vital categories:- Confidence: Focuses on clarity, speed, and presentation.
- Communication: Evaluates simplicity and structure.
- Correctness: Assesses relevance and accuracy.
- Provides instant, constructive, 10–15 word professional feedback.
- 📈 Rich Analytics Dashboard: Get a breakdown of overall scores, skill evaluations, and performance trends using interactive charts (via
Rechartsandreact-circular-progressbar). - 🗂️ History Tracking: Track past interviews, analyze performance progression over time, and revisit previous reports.
- 📄 Professional PDF Reports: Download structured performance reports containing scores, advice, and detailed question-by-question breakdowns using
jsPDFandjspdf-autotable. - 💳 Built-In Subscription & Payments: Start with 100 free credits (50 credits consumed per interview). Recharge using the integrated Razorpay Payment Gateway (Starter Pack: ₹100 for 150 credits; Pro Pack: ₹500 for 650 credits).
- Framework: React 19 + Vite
- State Management: Redux Toolkit (auth tracking & profile info)
- Routing: React Router DOM (v7)
- Styling: Tailwind CSS (v4)
- Animations: Framer Motion (
motion) - Visual Analytics: Recharts, React Circular Progressbar
- PDF Generation: jsPDF, jsPDF AutoTable
- Browser APIs: Web Speech API (
SpeechSynthesis,webkitSpeechRecognition)
- Runtime: Node.js
- Framework: Express.js (v5)
- Database: MongoDB (via Mongoose ODM)
- Authentication: Firebase Google Authentication (Client SDK) + JWT Cookies (HTTP-only)
- File Upload: Multer
- PDF Parsing: PDFJS-Dist
- Payment Processing: Razorpay Node SDK
- AI Engine: OpenRouter API (
openai/gpt-4o-mini)
interviewIQ/
├── client/ # Frontend Application (Vite + React)
│ ├── public/ # Static Assets
│ ├── src/
│ │ ├── assets/ # Images, icons, and AI avatar videos
│ │ │ └── videos/ # male-ai.mp4 & female-ai.mp4
│ │ ├── components/ # Reusable layouts and step managers
│ │ │ ├── AuthModel.jsx
│ │ │ ├── Footer.jsx
│ │ │ ├── Navbar.jsx
│ │ │ ├── Step1SetUp.jsx # Interview configuration & resume parsing
│ │ │ ├── Step2Interview.jsx # Avatar rendering & Web Speech recognition
│ │ │ ├── Step3Report.jsx # Analytics and PDF export options
│ │ │ └── Timer.jsx # Custom circular time tracker
│ │ ├── pages/ # Main routing views
│ │ │ ├── Auth.jsx # Login gateway using Google
│ │ │ ├── Home.jsx # Dashboard & setup container
│ │ │ ├── InterviewHistory.jsx # List of previous sessions
│ │ │ ├── InterviewPage.jsx # Core test container
│ │ │ ├── InterviewReport.jsx # Report viewer
│ │ │ └── Pricing.jsx # Subscription plan selector & payments
│ │ ├── redux/ # Redux slices and global store
│ │ ├── utils/ # Firebase client helper
│ │ ├── App.jsx # Route mapping & user fetcher
│ │ ├── index.css # Tailwind system configuration
│ │ └── main.jsx # DOM bootstrapping
│ ├── package.json
│ └── vite.config.js
│
└── server/ # Backend API Service (Express)
├── config/ # DB connectors & token signing rules
├── controllers/ # Controller layers
│ ├── auth.controller.js
│ ├── interview.controller.js
│ ├── payment.controller.js
│ └── user.controller.js
├── middlewares/ # Token validators and file upload configuration
│ ├── isAuth.js # JWT cookie authenticator
│ └── multer.js # Local resume storage configuration
├── models/ # Mongoose schemas
│ ├── interview.model.js
│ ├── payment.model.js
│ └── user.model.js
├── routes/ # Express route configurations
├── services/ # Integrations
│ ├── openRouter.service.js # AI prompts and API handler
│ └── razorpay.service.js # Razorpay client instance builder
├── index.js # Server entry point
└── package.json
Before starting the applications, configure the environment files in both the client and server root directories.
Create a file named .env in the server directory:
PORT=8000
MONGODB_URL=your_mongodb_connection_string
JWT_SECRET=your_jwt_signing_secret
OPENROUTER_API_KEY=your_openrouter_api_key
RAZORPAY_KEY_ID=your_razorpay_key_id
RAZORPAY_KEY_SECRET=your_razorpay_key_secretCreate a file named .env in the client directory:
VITE_FIREBASE_APIKEY=your_firebase_api_key
VITE_RAZORPAY_KEY_ID=your_razorpay_key_idFollow these steps to run the application locally.
- Node.js (v18 or higher recommended)
- MongoDB instance (Atlas or local compass setup)
git clone https://github.com/your-username/interviewIQ.git
cd interviewIQ- Navigate to the server folder:
cd server - Install dependencies:
npm install
- Set up the
.envfile as described in the Environment Variables section. - Run the server in development mode:
The server will run on
npm run dev
http://localhost:8000(or your configured port).
- Navigate to the client folder:
cd ../client - Install dependencies:
npm install
- Set up the
.envfile as described in the Environment Variables section. - Run the frontend in development mode:
The app will run on
npm run dev
http://localhost:5173.
graph TD
A[Sign in with Google OAuth] --> B[Dashboard / Home]
B --> C[Configure Interview Settings]
C -->|Optional| D[Upload Resume PDF]
D -->|AI Extracts Profile| E[Generate Questions]
C -->|Manual Inputs| E
E --> F[Start Interactive Session]
F --> G[Avatar Speaks Question]
G --> H[Candidate Speaks/Types Response]
H -->|Submit Answer| I[Real-time AI Feedback]
I --> J{Next Question?}
J -->|Yes| G
J -->|No| K[Finish Session]
K --> L[Generate Analytics Report]
L --> M[Export Performance PDF]
POST /google- Processes Google authentication details sent from the frontend client and returns user details. Sets an HTTP-only token cookie.GET /logout- Clears the authentication token cookie.
GET /current-user- Fetches profile details and remaining credits for the currently authenticated user.
POST /resume- Uploads a PDF resume, parses it, and uses GPT-4o-mini to extract skills, experience, and projects.POST /generate-questions- Generates 5 tailored questions based on configuration, deducting 50 credits from the user's account.POST /submit-answer- Submits a candidate's answer for evaluation. Triggers AI feedback scoring.POST /finish- Computes the aggregate scores (confidence, communication, correctness) and marks the session completed.GET /get-interview- Lists the historical record of interviews for the authenticated user.GET /report/:id- Fetches details and breakdowns of a completed interview.
POST /order- Creates a new payment order using the Razorpay SDK.POST /verify- Validates the webhook/callback signature from Razorpay. Increments user credits on success.