• Clients:

  • Category:

    Machine Learning

  • Services:

    Artificial Intelligence and Data analytics

  • Web:

Deployed machine learning and data analytics, incorporating data augmentation techniques and deep learning algorithms, and implementing a comprehensive approach, including a tailored dashboard, advanced sales forecasting, menu engineering, promotional day suggestions, real-time cooking time estimation, personalized recommendations, and AI-driven staffing and inventory management, addressing the restaurant’s diverse challenges effectively.

The story

Our client, a rapidly growing startup in the food technology sector based in Sweden. Owning a renowned chain of restaurants aimed to stay ahead of the culinary game. They required a comprehensive dashboard that would provide an in-depth understanding of their ongoing services, from sales insights to inventory management. To cater to this demand, we designed an advanced AI-driven system that integrates various aspects of kitchen management into one streamlined platform.

The challenge

The challenge at hand had several critical aspects within the restaurant industry, demanding innovative solutions. It required the precision of accurate sales predictions, a daunting task given the industry’s ever-changing dynamics. Additionally, crafting a menu that could adapt to the diverse and evolving preferences of customers was essential. Real-time cooking estimates had to be generated, considering factors like kitchen traffic and order complexity to ensure efficient operations. Personalizing recommendations for a broad and varied clientele was another hurdle to overcome. Lastly, managing inventory effectively while preserving ingredient freshness posed a significant challenge.

The solution

The solution to the challenges involved harnessing the capabilities of machine learning and data analytics. To enhance accuracy, data augmentation techniques were employed, reinforcing the XGBoost model’s ability to adapt to unpredictable shifts in sales trends. Deep learning algorithms played a crucial role in fine-tuning menu recommendations and suggesting promotional days, catering to the restaurant’s diverse clientele. The approach encompassed a comprehensive strategy, including the development of a dashboard tailored for kitchen owners, offering valuable insights into offerings and sales trends. Additionally, an advanced XGBoost-powered sales forecasting model empowered chefs and managers to plan ahead, while menu engineering went beyond standard options by analyzing menu popularity and proposing data-driven culinary creations. Promotional day suggestions, real-time cooking time estimations, personalized meal recommendations, and AI-driven smart staffing and inventory management rounded out the holistic solution, ensuring punctuality, customer satisfaction, and optimal operations.

The outcome

With AI, the restaurant chain witnessed a transformative leap. Sales forecasts boasted an accuracy rate of 93%, leading to improved inventory management. The kitchen staff could optimize operations, from ingredient procurement to staffing needs, ensuring timely service and delighted customers.


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