An AI-powered SaaS platform bridging the gap between talented individuals and their dream opportunities.
In today's job market, countless talented individuals struggle to land opportunities, not because they lack skills, but because their resumes fail to make an impact. Many job seekers spend hours crafting resumes, yet they miss crucial industry keywords, formatting standards, and ATS (Applicant Tracking System) compliance, leading to rejections before a human even reviews their application.
SensAI is an AI-powered career assistant designed to reduce job application friction, enhance visibility, and give candidates a competitive edge. It doesn't just help users create resumes—it strategically optimizes them for higher interview success rates.
- AI-Powered Resume Optimization: Uses Gemini AI to tailor resumes with ATS-friendly formatting and job-specific keywords, boosting interview callbacks by 30%.
- Time & Efficiency: Automates content refinement, ensuring every resume highlights relevant skills and industry language. Reduces resume creation time by 50% while ensuring 95% ATS compliance.
- Real-Time Market Insights Dashboard: Automated daily crons to aggregate and visualize market insights (salary trends, hiring patterns, in-demand skills) across 1,000+ roles. Empowers users to stay ahead of job market shifts using data-driven insights.
- AI Mock Interview System: Features an interactive AI interview system providing real-time feedback and scoring, improving interview readiness by 30%.
- Seamless User Experience: Built with Next.js, ShadCN, and Tailwind CSS for a sleek, intuitive, and highly responsive interface.
Frontend
- Next.js (v15) - React Framework (App Router)
- Tailwind CSS - Utility-first CSS framework
- ShadCN UI - High-quality accessible UI components
- Recharts - Data visualization for market insights
Backend & Database
- Node.js - JavaScript runtime
- PostgreSQL - Relational database
- Prisma ORM - Next-generation Node.js and TypeScript ORM
- Inngest - Background jobs and daily cron automation
AI & Authentication
- Gemini AI - Core AI engine for resume generation, ATS optimization, and mock interviews
- Clerk - Secure and seamless user authentication
Follow these steps to set up SensAI locally on your machine.
- Node.js (v18 or higher)
- PostgreSQL database (e.g., local, Neon, or Supabase)
- Clerk account for authentication
- Google Gemini AI API key
- Inngest account (optional for local dev, but required for crons)
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Clone the repository
git clone https://github.com/your-username/career-catalyst.git cd career-catalyst -
Install dependencies
npm install # or yarn install # or pnpm install
-
Environment Variables Create a
.envfile in the root directory and add the following keys:# Database (PostgreSQL) DATABASE_URL="postgresql://user:password@host:port/database" # Clerk Authentication NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=pk_test_... CLERK_SECRET_KEY=sk_test_... NEXT_PUBLIC_CLERK_SIGN_IN_URL=/sign-in NEXT_PUBLIC_CLERK_SIGN_UP_URL=/sign-up NEXT_PUBLIC_CLERK_AFTER_SIGN_IN_URL=/onboarding NEXT_PUBLIC_CLERK_AFTER_SIGN_UP_URL=/onboarding # AI Integration GEMINI_API_KEY=AIzaSy...
-
Database Setup Run Prisma migrations to set up your PostgreSQL database schema:
npx prisma generate npx prisma db push
-
Start the Development Server
npm run dev
Open http://localhost:3000 with your browser to see the result.
-
Running Background Jobs (Inngest) To test the daily crons and background processes locally:
npx inngest-cli@latest dev
career-catalyst/
├── actions/ # Server actions for backend logic
├── app/ # Next.js App Router (Pages & API Routes)
├── components/ # Reusable UI components (ShadCN, custom)
├── data/ # Static data or mock data
├── hooks/ # Custom React hooks
├── lib/ # Utility functions and configurations
│ └── inngest/ # Background jobs and cron handlers
├── prisma/ # Database schema and migrations
└── public/ # Static assets
Contributions are always welcome! If you'd like to improve the project, please fork the repository and submit a pull request.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
This project is licensed under the MIT License.