Purina US, a subsidiary of Nestle, used artificial intelligence (AI) and machine learning (ML) to automate animal breed detection on the Petfinder platform. By leveraging Amazon Rekognition Custom Labels, AWS Step Functions, and other AWS services, Purina created an ML model that detects the pet breed from uploaded images and auto-populates pet attributes. This solution improves the accuracy and efficiency of pet adoption on Petfinder.
Purina Uses AI to Optimize Pet Profiles for Petfinder Application
Background
Purina US, a subsidiary of Nestle, has a long history of helping people adopt pets through Petfinder, a digital marketplace for animal shelters and rescue groups. However, accurately reflecting the specific breed of animals available for adoption was a challenge, as many shelter animals are mixed breed.
The Solution
To address this challenge, Purina used artificial intelligence (AI) and machine learning (ML) to automate animal breed detection at scale. They employed Amazon Rekognition Custom Labels, AWS Step Functions, and other AWS services to create an ML model that detects the pet breed from an uploaded image and auto-populates the pet attributes.
How It Works
The solution uses Rekognition Custom Labels, which allows businesses to identify objects and scenes in images specific to their needs. Instead of thousands of images, Purina only needed a small set of training images per category. The architecture involves Amazon API Gateway, AWS CDK, AWS CodeBuild, Amazon DynamoDB, AWS Lambda, Amazon Rekognition, AWS Step Functions, and AWS Systems Manager.
Benefits
With this AI solution, Purina’s Petfinder team can accelerate the creation of pet profiles for shelters, reducing administrative burden. The solution automates the training and deployment process, making it easier to maintain and improve the models over time. By leveraging AI, Purina achieved significant time savings, reducing the average time for creating a pet profile from 7 minutes to 4 minutes.
Security
The solution ensures data encryption in transit and at rest, following AWS Well-Architected best practices.
Conclusion
Purina’s use of AI and ML, specifically with Amazon Rekognition Custom Labels and AWS Step Functions, has revolutionized how pet profiles are created on the Petfinder application. By adopting this AI solution, companies can optimize their processes, improve customer interactions, and achieve measurable business outcomes.
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If you want to evolve your company with AI and stay competitive, consider the following steps:
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List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions
- AWS Machine Learning Blog
- Twitter – @itinaicom
