careerzen 🧘‍♂️

AI-Powered Resume Optimization & Intelligent Interview Prep

Live Demo | Report Bug | Request Feature | Contributing Guide

---

⚡ Overview

careerzen is a next-generation, open-source career tool designed to help you land your dream job efficiently. It leverages Google's Gemini 3.0 Flash Preview to analyze your resume against job descriptions, producing an instant ATS match score and optimization tips.

But it doesn't stop there. careerzen features an AI Interview Coach that uses Sarvam AI for advanced Speech-to-Text (STT) processing, allowing you to practice mock interviews by speaking your answers out loud before receiving real-time AI feedback.

---

🌟 Visual Workflow Guide

Our clean, modern interface makes it incredibly simple to optimize your application.

1. Resume Match Analysis

Simply drag and drop your Resume (PDF/Word) and paste the Job Description (Text/Screenshot). Our AI engine does the rest.

2. AI Interview Coach (with Sarvam STT)

Practice tailored interview questions specifically targeted at your weak spots. Speak your answers naturally using our Sarvam AI Speech-to-Text integration.

---

🧠 System Architecture

Beneath the simple UI lies a robust, multimodal AI architecture. Here is how the text and audio logic flows:

graph TD
    %% Styling
    classDef user fill:#3b82f6,stroke:#1e40af,stroke-width:2px,color:#fff,rx:8px,ry:8px;
    classDef ai fill:#a855f7,stroke:#7e22ce,stroke-width:2px,color:#fff,rx:8px,ry:8px;
    classDef ext fill:#10b981,stroke:#047857,stroke-width:2px,color:#fff,rx:8px,ry:8px;
    classDef db fill:#f59e0b,stroke:#b45309,stroke-width:2px,color:#fff,rx:8px,ry:8px;

    %% Nodes
    UserUpload["User Uploads Resume<br>(PDF/DOCX)"]:::user
    UserJob["User Provides Job Listing<br>(Text/Image)"]:::user
    UserSpeech["User Speaks Answer<br>(Voice Audio)"]:::user
    
    Parser["Text/OCR Parsing Engine"]:::ext
    SarvamSTT["Sarvam AI<br>Speech-to-Text API"]:::ai
    Gemini["Google Gemini 3.0<br>Flash AI Engine"]:::ai
    
    Analysis("ATS Optimization Analysis"):::ext
    Questions("Generated Interview Scenarios"):::ext
    Feedback("Voice Answer Feedback"):::ext
    
    DB[(PostgreSQL + Prisma)]:::db
    Dashboard(User Dashboard UI):::user

    %% Edges
    UserUpload --> Parser
    UserJob --> Parser
    UserSpeech --> SarvamSTT
    
    Parser --> |Parsed Text| Gemini
    SarvamSTT --> |Transcribed Text| Gemini
    
    Gemini -.-> |Calculates| Analysis
    Gemini -.-> |Creates| Questions
    Gemini -.-> |Evaluates| Feedback
    
    Analysis --> DB
    Questions --> DB
    Feedback --> DB
    
    DB --> Dashboard

Loading

---

✨ Core Features Matrix

Feature	Description	Why It matters
🎯 Instant ATS Score	Detailed parsing against job requirements	Stop guessing if your resume will pass the filters
🖼️ Multimodal OCR	Upload PDF/DOCX or Images of job postings	Total flexibility no matter where you find the job
🎙️ Voice Mock Interviews	Uses Sarvam AI to transcribe spoken answers	Practice physically speaking out loud, not just typing
🤖 Dynamic AI Coach	Uses Gemini to provide constructive feedback	Iteratively improve how you sell your experiences
👨‍💻 Modern Dashobard	Fully responsive dashboard with history tracking	Maintain a central hub for your job hunt

---

🛠️ Technology Stack

We've built careerzen using modern, production-ready tools:

Click to expand Tech Stack

• Frontend: Next.js 16 (App Router), React 19, Tailwind CSS v4
• Animations: Framer Motion, GSAP
• Database: PostgreSQL, Prisma ORM
• Authentication: Clerk Auth
• AI / LLM: Google Gemini-3-Flash-Preview (@google/genai)
• Speech-to-Text: Sarvam AI
• Parsing Utilities: pdf2json, mammoth, @react-pdf/renderer

---

🚀 Local Development Setup

Want to run careerzen on your own machine? Follow these step-by-step instructions.

Prerequisites

Before you begin, ensure you have the following installed:

• Node.js (v20+ recommended)
• Git
• A Google Gemini API Key
• A Sarvam AI API Key

Installation Steps

1. Clone the repository

   git clone https://github.com/aniruddhaadak80/smart-resume-analyzer.git
   cd smart-resume-analyzer

2. Install dependencies

   npm install

3. Configure Environment Variables
   Create a .env.local file in the root directory. You will need to populate it with your specific API credentials:

   # Database (PostgreSQL)
   DATABASE_URL="your_database_connection_string"
   
   # Clerk Authentication
   NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=your_clerk_pub_key
   CLERK_SECRET_KEY=your_clerk_secret_key
   
   # AI Services
   GEMINI_API_KEY=your_gemini_api_key
   SARVAM_API_KEY=your_sarvam_api_key

4. Initialize the Database
   Push the Prisma schema to your connected database:

   npx prisma generate
   npx prisma db push

5. Start the Development Server

   npm run dev

   Your app will now be running at http://localhost:3000.

---

🤝 Contributing

We ❤️ our contributors! Whether it's squashing bugs, adding new integrations, or fixing typos, we'd love your help.

Please read our comprehensive CONTRIBUTING.md guide to learn how to:

1. Fork the repo and set up your branch
2. Find beginner-friendly "good first issues"
3. Submit a Pull Request properly

---

© 2026 careerzen. Built with ❤️ and Open Source logic.