AI-Driven Predictive Demand Forecasting for Organic Food Products

Our SME in the Organic & Natural Foods industry seeks to implement an AI-driven solution for predictive demand forecasting. As the market for organic products continues to grow, efficient inventory management is critical. The proposed solution will utilize advanced technologies such as LLMs, computer vision, and predictive analytics to forecast demand based on historical sales data, market trends, and external factors like seasonal variations. By leveraging tools like TensorFlow, PyTorch, and OpenAI API, the system will deliver actionable insights that can optimize stock levels, reduce waste, and ultimately increase operational efficiency. The project involves data collection and preprocessing, model development and training using AutoML techniques, and integrating these predictions into existing inventory systems through APIs. The expected outcome is a robust and scalable forecasting tool that aligns with the company's sustainability goals.