Every year around one-third of food produced for human consumption is lost or wasted globally (source: WFP). One of the reasons is that donors such as restaurants, diners and take-aways does donate their remaining food to food banks but with out of idea whether at that particular time, the food bank is ready to accept and cater the donation. On the other hand, food banks can't connect with the donors that are right fit for them on a particular day with regards to their capacity to accept, maintain and distribute the food. Our solution is aiming to determine the feasibility of the Donor/NGO according to their need and match the right fit using an AI model.

The project is the minimal viable product (MVP) that is developed using Python for creating synthetic data, Tensorflow for creating AI model and finally, Streamlit for creating the final web application. The solution is deployed on Streamlit Cloud.

The final solution (version 1) is a web application that can be accessed at  https://food-bank-ai.streamlit.app/ . 

It provides a nice UI with easy to follow instructions at each step of the customer journey. It is a responsive website that can be accessed via any digital device but it is recommended to access it using desktop PC for the best user experience.