The project aims to develop a prototype for an AI-driven national database that provides critical information and connections to improve the safety and well-being of abused and neglected children in America. The current challenge is the lack of a centralized system that efficiently aggregates and analyzes data to support decision-making and intervention strategies. By leveraging AI technology, the project seeks to create a system that can identify patterns, predict risks, and suggest solutions to stakeholders involved in child welfare. The database will serve as a tool for social workers, policymakers, and child advocacy groups to access real-time information and collaborate effectively. The project will focus on designing a user-friendly interface and ensuring data privacy and security. The ultimate goal is to lay the groundwork for a comprehensive system that can be scaled and implemented nationwide.

The deliverables for this project include a functional prototype of the AI-driven database, complete with a user interface and basic data analysis capabilities. The team will also provide documentation detailing the system architecture, data sources, and AI algorithms used. Additionally, a presentation will be prepared to demonstrate the prototype's features and potential impact on child welfare. The project will conclude with a report outlining recommendations for further development and implementation.