AgShift utilizes AI-driven computer vision and machine learning to provide autonomous food quality assessment across the supply chain, significantly enhancing inspection accuracy and efficiency. By processing millions of images, their system achieves a fourfold reduction in operational costs and increases sample sizes, thereby improving brand quality and minimizing product recalls.
Funding
$6.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Current methods of food quality assessment rely on manual inspection, which is subjective, inconsistent, and costly. Limited sample sizes and infrequent inspections can lead to undetected quality defects, resulting in product recalls and brand damage.
Solution
AgShift offers an AI-powered food quality assessment platform called Hydra that automates the inspection process across the food supply chain. The system uses computer vision and machine learning to analyze images of commodities, providing objective and consistent quality assessments. By processing millions of images, the platform increases sample sizes, improves inspection accuracy, and reduces operational costs. The technology enables food organizations to proactively identify and address quality issues, minimizing the risk of recalls and enhancing brand reputation.
Target Audience
AgShift's primary customers are food producers, processors, distributors, and retailers seeking to improve quality control, reduce operational costs, and minimize the risk of product recalls.
Features
- AI-driven computer vision for autonomous food quality assessment
- Trained on millions of images and data points for specific commodities
- Objective and consistent quality assessment at scale
- Real-time data and audit trails for improved traceability
- Integration with existing supply chain management systems
- Customizable quality parameters and reporting dashboards