Using AI to Reduce Food Waste

Technology Overview

PROBLEM: The food inspection and quality assessment across food industry, for decades has been a manual, ad-hoc process with cumbersome paperwork. The Food Industry spends 2- 3 % of their total turnover on inspections which are manual and inconsistent. The inconsistency in quality assessment also leads to significant rejections, claim management and food waste. The growing labor shortage and increasing hourly wages is also hurting the industry.  The industry is desperately looking for technology to make the food inspection process more autonomous, objective, data driven and less labour-intensive requiring trained staff. Food inspection is ready for disruption and we are at the forefront of bringing this disruption and shaping the future of autonomous inspections. SOLUTION: Making food quality inspection more autonomous, consistent and objective at 10x operational efficiency compared to manual processes of today - using innovations in AI, Computer vision and IoT. TECHNOLOGY: We offer the food industry an autonomous grade analyzer, a turn-key IoT platform, integrated with advanced AI and computer vision technology stack.

Technology Features & Specifications

We offer the food industry’s first autonomous grade analyzer, a turn-key IoT platform, integrated with advanced AI and computer vision technology stack to make food quality inspections more consistent, objective, digitized and autonomous at 10X operational efficiency. Core differentiating technology components:

  • IoT: Patented IoT device for 360-degree analysis of commodity sample
  • AI: Patented AI based deep learning models to automate grade assessment of selected commodities
  • Computer Vision: Patented computer vision algorithms to augment defect analysis along with AI based deep-learning models
  • Proprietary Data sets: Our in-house developed annotation platform to collect, for the first time -  a clean, curated and labelled industry data set in close collaboration with a tier 1 industry player, which serves as an economic moat to maintain a competitive advantage
  • Patents: 3 provisional patents issued

Potential Applications

Our autonomous AI inspection is applicable across a broad specturm of food commodities. From business perspective, we are focused on 3 categories within food:

  1. Berries:  Strawberries, Raspberries, Blueberries and Blackberries
  2. Edible nuts: Cashews, Almonds, Peanuts, Hazelnuts, etc.
  3. Sea-food: Shrimp, fish fillets etc.

Across these 3 categories, the food industry spends 2- 3 % of total turnover on inspections. The proportion is higher when the volumes are smaller and vice versa.  Currently, our solution is used by Tier 1 players in the food supply chain in the following categories: Fresh Strawberries, Cashews and Almonds.

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