Integrated AI Intelligence Systems: A Review of Retrieval, Language Processing, and Multimodal Technologies

Abstract

The rapid advancement of Artificial Intelligence (AI) has led to the development of intelligent systems capable of processing information from multiple sources, including text, speech, images, and documents. Recent technologies such as Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), Speech-to-Text (STT), and Text-to-Speech (TTS) have significantly improved the performance of modern AI applications. This review paper examines the key technologies, research developments, and applications of integrated AI intelligence systems. Various studies related to information retrieval, language understanding, speech processing, and document intelligence are analyzed to identify their strengths, limitations, and practical significance. The paper also discusses current challenges and future research opportunities in the field. The review highlights the growing importance of integrating multiple AI technologies within a unified framework to improve accessibility, efficiency, and user experience across academic, research, and professional environments.