International Journal of Science, Engineering and TechnologyAuthors: Satyam Kumar Tripathi, Raj Singh, Jyoti Maddheshiya, Ritika Singh, Mr. Sanjeev Pathak
Abstract: People today face an overwhelming volume of daily information, which often causes cognitive overload and makes it hard to manage memories effectively. Standard tools like basic note-taking apps or digital reminders usually fall short because they lack contextual awareness and have limited search capabilities. To address this, we introduce RecallX, an AI-driven memory assistant built to capture, organize, and retrieve various types of data—including text, audio, images, and video. By combining Natural Language Processing (NLP), computer vision, and speech recognition, RecallX moves past basic file storage. Instead, it structures memories with contextual awareness and creates associative links, similar to how human memory works. The system pulls out key details, tags them with metadata like timeframes and related entities, and allows users to search their memories naturally using everyday language. By relying on semantic search rather than strict keyword matching, RecallX delivers much more accurate and relevant results. Ultimately, this scalable architecture is built to lighten the user’s mental workload and boost daily productivity.
DOI: https://doi.org/10.5281/zenodo.19969977
