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Cheatector

A standalone SaaS project I built that aids in detecting AI-generated content within PDFs. Users buy credits via Stripe, where one credit equals one PDF analysis.

Cheatector - Detect AI Generated Content in Your PDFs

Cheatector Application

Introducing Cheatector, a unique SaaS I developed single-handedly. It serves a crucial function - helping you identify portions of your PDFs that could potentially be recognized as AI-generated content. It operates on a simple credit system, where users can purchase credits using Stripe, and each credit allows for one PDF analysis.

This project was brought to life during my spare time, over a week of evenings after work and throughout the weekend. Despite the time constraints, it has resulted in a fully functional SaaS platform that uses the following technologies:

  • Next.js for the front-end development
  • Tailwind CSS for styling
  • Supabase for the database and auth (Google and GitHub)
  • Stripe for handling payments
  • OpenAI's reverse-engineered detect API for AI content detection
  • LangChain for managing PDF trimming

This project is a testament to what can be achieved in a short amount of time with the right dedication and use of technology. Although it's currently not free to use, it stands as a significant milestone in my journey as a developer. It not only helped me sharpen my skills but also highlighted the potential of AI in our everyday tasks.