Leading Indian P&C Insurer
Cattle Recognition and Identification system
Product
The client sought a cost-effective, non-invasive solution for cattle identification during the claims process, seeking an alternative to RFID tags that would minimize errors.
Solution
A mobile-centric solution was developed, utilizing computer vision, machine learning, and other AI models to identify unique biometric markers for accurate cattle recognition and classification.
Outcome
The system significantly reduced manual labor and dependencies while ensuring more efficient and humane cattle identification, streamlining the claims process and enhancing accuracy.


Implementing an AI-Powered Solution for Efficient and Non-Invasive Cattle Identification
The client required a cost-effective, non-invasive solution for cattle identification during policy registration and claims. The existing method of using RFID tags was expensive, prone to malfunctions, and invasive. A mobile-centric solution was developed, leveraging computer vision, machine learning, and AI to identify unique biometric markers such as color, breed, age, facial landmarks, and muzzle patterns. This approach created a tamper-proof database, enabling accurate cattle recognition. The solution was integrated with the client's existing web-based application, providing easy access to claim-related data and organizing documents for efficient storage.



The new system drastically reduced manual labor and eliminated the need for costly and invasive identification methods. By simplifying the cattle identification process, the insurer enhanced accuracy, reduced errors, and streamlined the entire claims process. This solution not only improved operational efficiency but also fostered a more humane and reliable approach to cattle recognition.
Streamlined, Humane, Error-Free
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