The project involves developing a robust AI manager agent designed to operate entirely on edge computing devices, specifically targeting small to medium-sized enterprises (SMEs) in sectors like hospitality. The AI manager will collect and analyze real-time data from various applications used by SMEs—such as order management, inventory control, customer feedback, and more—to provide actionable insights, forecasts, and recommendations to improve business operations. A core component of the project is creating an interactive, conversational AI interface that allows business owners to ask questions in natural language (text or voice). The AI manager will respond by summarizing current business performance, identifying key metrics, and providing step-by-step guidance for using business applications. An essential feature of this system will be its ability to self-learn from data trends and user feedback, making it an adaptive and evolving tool tailored to each business. Students will address several challenges, including developing lightweight, efficient AI models optimized for edge processing, creating a user-friendly dashboard with visual guidance, and ensuring the AI's modular design to support integration with third-party applications. Additionally, the project will require maintaining strict data privacy and security due to the sensitive nature of business data.

System Architecture Document: Detailed design documentation outlining the AI manager’s data pipeline, core AI functionalities, and architecture for integration with third-party applications. Edge-Based AI Model Suite: Set of optimized models for NLP (question-answering, FAQ search), forecasting, and anomaly detection, capable of running efficiently on edge devices. User Interface Dashboard: A cross-platform, mobile-friendly dashboard with an interactive, visual help system using overlays and voice-guided assistance. Data Security and Privacy Module: Implementation of data encryption, access controls, and role-based permissions aligned with SME data privacy needs. API Gateway and Plugin System: A framework allowing third-party applications to integrate and share data seamlessly with the AI manager. Testing and Performance Report: Final report with test cases, user feedback, and a performance assessment showing real-time functionality and resource optimization on edge hardware.