This project addresses the problem of effectively managing real-time data in collaborative environments where multiple users need to access, modify, and synchronize data seamlessly. Many existing tools fail to provide the necessary functionality for real-time data manipulation combined with an intuitive user interface. To resolve these issues, this study focuses on building a robust database manipulation tool using Firestore, Firebase’s NoSQL database service, which enables smooth and efficient CRUD (Create, Read, Update, Delete) operations with instantaneous data synchronization across all users and devices. A key feature of this project is the implementation of a local cache mechanism enhanced by AI/ML algorithms. This mechanism enables users to continue accessing and updating data even when offline while intelligently predicting which data will be needed most frequently based on user behaviour patterns. This functionality is vital for improving user experience, particularly in scenarios where internet connectivity may be intermittent. Once the connection is restored, any changes made while offline are automatically synchronized with the Firestore database, ensuring users can work without interruptions.