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Smart Food Grader

To collaborate and be a valued partner in frontier technology
for organizations in their digital evolutionary journey



Identified 90% success in food grading.

Paris

Goal

To cut down the food produce waste, cost and supply customer with quality products.

Insights and Action

Improves the food quality by grading with certain parameters which gets rid off by grading based on the food standards and compliances. Food waste will be avoided based on the analytics and deep learning.

The process defined at every point in the supply chain from farm to wholesaler, to distributor, to packer or processor, to retailer, fresh produce is inspected for freshness, damage, size, and color to fit within the specifications.

Deep learning is the key for training the images and then the quality assessment will be autonomous. Capturing the photos will result the values and the report.

Based on gathered data, predictive analytics can be run through Artificial Intelligence.

Results

15-20%

Of horticulturists have already deployed such technologies to aid in their orchards.

90%

success rate in grading the produce using certain grading parameters.







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