A leading American airline faced a hurdle with customer satisfaction regarding their in-flight menu options. The airline struggled to anticipate demand for certain meals, resulting in a surplus of some items and a shortage of others. However, Valorem Reply, a Microsoft Designated Azure Data & AI Solutions Partner, had previous experience working with the airline and had valuable insight into the issue, along with recommendations to address the allocation problem. Within a span of just six weeks, we deployed a Demand Forecasting Accelerator solution that enables the airline to predict catering demand for each flight. Our machine learning model predicts catering demand by item and by flight, providing catering vendors with required menu items, food quantities, etc. in advance. This innovative solution is based on a model produced in Azure ML, which is connected to a new table in Azure SQL DB and runs on the airline's Azure tenant. This provides the airline with access to both the model and the API. With our innovative solution, the airline can now accurately predict customer demand for meals and adjust their stock if there are delays or unexpected changes to flights, facilitating a better customer and employee experience. Consequently, the airline has seen a notable increase in revenue of approximately $2M - $5M per year and a reduction in food waste of $50K - $80K a month.