Enhancing Photo Analytics Using AWS
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Company Size
11-200
Region
- Asia
Country
- Taiwan
Product
- Amazon Rekognition
- Amazon EC2
- Amazon CloudFront
- Amazon RDS
Tech Stack
- AWS
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Computer Vision Software
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- Consumer Goods
Applicable Functions
- Sales & Marketing
Use Cases
- Visual Quality Detection
Services
- Cloud Planning, Design & Implementation Services
About The Customer
Amplframe is a photography community platform based in Taiwan. Founded in 2016, the platform serves as a hub for avid photographers to list and explore various lenses. The website features photos uploaded by users, which are categorized by different types of lenses. The platform has seen a significant increase in traffic, with 18,000 visits over a period of seven months.
The Challenge
Amplframe, a photography community platform in Taiwan, was facing challenges in managing the increase in website traffic, with 18,000 visits over a period of seven months. The company needed a solution that could efficiently handle the sudden spikes in website traffic during events or holidays. Additionally, they were looking for ways to enhance the user experience by reducing webpage loading time and increasing the website engagement rate.
The Solution
Amplframe adopted a range of AWS products and services to address their challenges. They used Amazon Rekognition for image recognition and analysis, which helped in increasing the average website engagement rate. Amazon CloudFront was used for the delivery of content, which significantly cut the webpage loading time, providing a better user experience. To accommodate peaks in website activity, Amplframe ran a combination of Amazon EC2 instances and Amazon RDS. This solution not only supported the increase in website traffic but also decreased the monthly IT production cost and reduced server development time.
Operational Impact
Quantitative Benefit
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