Cloud Concierge

Cloud Concierge aims to be an AI-powered web platform aimed at revolutionizing
operational efficiency in the hospitality industry. Cloud Concierge synthesizes
internal metrics (sales, inventory, labor) and external data (weather, traffic, event,
and demographic trends) to provide predictive insights, enabling restaurateurs to
proactively optimize staffing and inventory and mitigate waste. Initially, the focus
will be on restaurants in Ottawa, serving as a prototype for the first phase. Working
with the Computer Engineering student team, we would like to create a framework
for the data collection and report component of the Cloud Concierge product. This
prototype aims to validate the framework and its impact within the local market.
For internal metrics, we would like to collect sales and labour data from Point of
Sale (POS) systems. For external data, we would like to collect weather, traffic, and
events data. Finally, the product would be able to generate a report that draws
patterns in the combination of the two sets of data.




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