Paper IQ – AI-Powered Research Insight Analyzer is an intelligent system designed to automate the process of reading, understanding, and summarizing academic research papers using artificial intelligence. With the exponential growth of scientific publications, researchers often face challenges in efficiently extracting relevant insights, identifying key findings, and staying up to date with the latest advancements in their fields. PaperIQ addresses this problem by leveraging natural language processing (NLP), machine learning, and text mining techniques to analyze research papers, extract important sections, generate concise summaries, and provide datadriven insights. The system processes documents in multiple formats such as PDF, DOCX, and TXT, performing preprocessing tasks like text extraction, cleaning, and keyword identification. It then applies advanced transformer-based language models to perform semantic understanding, topic classification, and insight generation. PaperIQ also identifies research gaps, emerging trends, and frequently cited concepts, enabling users to gain a deeper understanding of literature without manually reviewing each paper. Additionally, the system supports comparative analysis across multiple papers, helping users identify similarities, contradictions, and research evolution over time. The modular architecture allows customization based on domain-specific research requirements and analytical depth. By providing structured outputs and visual insights, PaperIQ enhances knowledge accessibility and interpretability.