AI-Based Plagiarism Detection System Using Deep Learning and LLMs

Abstract: Generative AI is shaking up how we think about academic honesty and professional integrity—and not always in a good way. Most old plagiarism checkers aren’t up to the task anymore. They catch copy-paste or obvious paraphrasing, but miss the tricky stuff: clever rewording, translations, or anything cooked up by modern AI tools. Add in all the weird formats—images, messy PDFs—and things get even more complicated. PlagiGuard AI bridges this gap. Instead of relying on a collection of different tools, it uses deep learning and large language models to spot when the meaning’s been stolen, not just the wording. It can even flag when AI wrote the text. You just upload your files—PDFs, Word docs, images—and PlagiGuard pulls out the content, compares it locally and online, and gives you a straight-up risk report. You’ll see which sentences are copied, paraphrased, or machine-generated. The architecture’s built for speed, security, and scale, handling more than twenty languages with no sweat.

Keywords: Artificial Intelligence, Plagiarism Detection, AI Content Detection, Natural Language Processing (NLP), Optical Character Recognition (OCR), FastAPI, React.js, Python, Supabase, Machine Learning, Document Analysis, Text-to-Speech, PDF Report Generation, Academic Integrity.