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CASE STUDIES
How we helped a biotech company secure food supply chains in the USA
CASE STUDIES
How we helped a biotech company secure food supply chains in the USA
We built an analytics and computer vision platform for early microbial risk detection and real-time insights, aggregating data from 15+ diverse sources including US government agencies, leading to substantial savings and precise farm management.
We built an analytics and computer vision platform for early microbial risk detection and real-time insights, aggregating data from 15+ diverse sources including US government agencies, leading to substantial savings and precise farm management.
The Client & Category
The client is a US biotechnology company that specializes in detecting and predicting microbial threats within food supply chains.
The client aimed to address food producers’ challenges related to disease and contamination that create risks for human health, company reputation, and financial performance. They wanted to cut monitoring costs, improve feed conversion ratios, and reduce animal mortality rates through early detection solutions.
The Outcome
Our platform has transformed the detection of microbial threats at US food production facilities. Organic samples are now analyzed on-site and within minutes versus days. Several dozen samples can be analyzed in parallel using our client’s proprietary hardware technology backed by our software platform.
This platform has empowered veterinarians and facility managers to promptly implement precise control measures in response to emerging threats. This has helped reduce monetary losses, increase food output, and minimize the risk to human health, leading to healthier and safer communities across the United States.
The Solution
We worked closely with the client to architect, design, and develop a web and mobile platform for real-time data aggregation and analytics.
One of the key inputs to this platform is computer vision algorithms that we developed using deep learning and conventional techniques. These algorithms automate the detection and classification of pathogens from microscopic images with > 95% accuracy.
We built over 500 data pipelines to collect data from farms across the United States and Europe as well as US government agencies such as FDA, USDA, OSHA and others. The data existed on multiple technology platforms, websites, and file formats including PDF, CSV, XLS, and JSON. We also designed a custom data model to cater to the unique characteristics and requirements of the use case, considering factors such as food production, processing, distribution, and consumption. This platform is a powerful foundation to weave together insights and knowledge that are delivered to end-users through interactive dashboards, e-mails, and alerts.
The solution is cloud-native with automated mechanisms for scaling, code deployment and maintenance, and data security. Additionally, our QA team has written over 1,000 automated tests to ensure code quality and stable feature releases.
We built over 500 data pipelines to collect data from farms across the United States and Europe as well as US government agencies such as FDA, USDA, OSHA and others. The data existed on multiple technology platforms, websites, and file formats including PDF, CSV, XLS, and JSON. We also designed a custom data model to cater to the unique characteristics and requirements of the use case, considering factors such as food production, processing, distribution, and consumption. This platform is a powerful foundation to weave together insights and knowledge that are delivered to end-users through interactive dashboards, e-mails, and alerts.
The solution is cloud-native with automated mechanisms for scaling, code deployment and maintenance, and data security. Additionally, our QA team has written over 1,000 automated tests to ensure code quality and stable feature releases.