AgShift has declared the launch of Hydra F100 BQ, the leading global AI-based tool to analyze the quality of food. Hydra F100 BQ is a fruitful outcome of AgShift and stands to be the world’s first food quality analyzer. As an essential solution to general monitoring and management challenges faced by the officials and inspectors in the department of food, this AI-based food quality analyzing software ensures consistency, optimizes the efficiency of food inspection processes and eliminates the unwanted human efforts. With Hydra F100 BQ, quality checks, pricing, sourcing, and complete assessment of food commodities can be achieved in a much simplified manner.
Announcing the grand release of the product, the founder of the startup, Miku Jha said “This was a much-needed innovation in food quality assessment. The current food quality assessment processes are paper-based and manual, many times leading to inconsistent and subjective outcomes that result in losses in the range of $15 to $16 billion annually, not accounting for millions of dollars lost in recovery costs, claim management and diluted brand equity for the organizations involved.”
AgShift holds the action line of delivering groundbreaking solutions to the risks and problems faced by the food ecosystem worldwide. Highlighting the broader vision and strong mission of the company, she added, “We are committed to closing the gap between food and technology. The food industry is prime for innovation, specifically in the field of automation. Our solutions are bringing much needed operational efficiencies and objective accuracies enabling a different kind of quality transparency across the entire food supply chain.”
Using Artificial Intelligence (AI) as its prime root of development and scaling, Silicon Valley-based startup has been working towards independent, significant and effective food quality inspection system. AgShift has walked along its way, creating milestones of inspiration- conducting ongoing commercial trials with reputed food companies like strawberry inspection with Driscoll’s, cashew inspections with Olam and the list continues. The robust analyzer integrates conceptual and analytical intensified learning models with a thought to prevent wastage of food globally.