Food Analyzer

Transforming Quality Control for the Hospitality Industry with AI

Business Challenges

The client was a KSA-based leader in culinary and hospitality services who faced significant challenges in maintaining and assessing the food quality for customers, some of whom were providing in-flight meals. Traditional food inspection methods were time-consuming and error-prone, thus lacking the precision needed to elevate the operational efficiency needed for large-scale catering and simultaneously ensure customer satisfaction. These challenges led to high wastage, compliance issues, and inconsistency in food quality. To deliver a superior culinary experience, the client needed to move away from the old-fashioned method of manual evaluation.

Our Approach

Our solution uses both AI and computer vision to analyze the images of food before and after eating. It delivers insights into meal consumption patterns to help predict overall food quality. By analysing thousands of images daily, our scalable solution can provide precise data on how much food was consumed, left, or partially eaten. This automated analysis can be directly integrated with client workflows, thus reducing food waste and driving culinary excellence in the long run.
  • AI-Powered Analysis: Using an advanced AI model with computer vision trained to recognize food categories and consumption levels.
  • Scalable Architecture: Capable of processing thousands of images daily to keep pace with high-demand operations.
  • Seamless Integration: Easily added into existing processes to enhance decision-making.

Key Takeaways

  • 40% Decrease in Manual Quality Inspections
  • 60% Accuracy in Predicting Meal Quality
  • 35% Increase in Real-Time Decision-Making Capabilities

Use Case

An AI solution that can analyze meal consumption by accurately assessing how much food is eaten, left untouched, or partially consumed, optimizing food quality control and reducing waste across operations.

Results

  • Operational Efficiency: Enhanced efficiency in evaluating meal quality and consumption trends, leading to better service delivery.
  • Enhanced Customer Satisfaction: Improved food quality and operational efficiency directly contribute to customer satisfaction.
  • Waste Reduction: Improved data insights help reduce food wastage and streamline menu optimization.