Case Study

EdTech Firm Automates Video Workflows to Reduces Bit Rate By 20–50% using AWS Elemental MediaConvert

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AWS Elemental MediaConvert, AWS Step Functions, AWS Lambda, Amazon CloudFront, AWS CloudFormation, Amazon S3, AWS CloudWatch, Amazon SNS, Amazon DynamoDB


Business decisions with real-time analytics, structured user hierarchy, and Amazon Quick Sight dashboards processing 250 GB daily, offering key metrics for comprehensive business evaluation in just 15 minutes.

About the Client

FreshLearn was founded in 2020 by CEO Rahul Mehta. FreshLMS draws on his extensive experience in building tech products and teams worldwide. It lets creators quickly monetize knowledge with courses, workshops, and downloads, launching profitable online businesses in under an hour. Over 13,000 creators globally have earned $20M+ by selling their content. FreshLearn offers 24/7 support via live chat, email, and scheduling. 


20–50% bit reduction

(QVBR (Quality-defined variable bitrate))

Controlled logs

(AWS CloudWatch)

Maintained and Compressed Folder Hierarchies

(AWS CloudFront)

The Challenge

The company faced a challenge with user-uploaded videos, as high-definition (HD) quality wasn’t universally supported on devices. Initially, videos went directly to Amazon S3 and were delivered globally via AWS CloudFront without compression, causing poor user experience and increased bandwidth usage. 


  • Delivering video content requires a secure infrastructure, and this architecture is built to provide maximum security. This security incorporates components like access control and authentication to safeguard the content. 
  • AWS media VOD workflow supports QVBR (Quality-defined variable bit rate), which helps reduce the bit rate by 20–50%. 
  • The procedure is streamlined by automation, which increases its dependability and efficiency. 

The Results

Integrated ABR videos across multiple devices with professional-grade quality, time reduction, and 20–50% bit reduction using QVBR while automating the video processing workflow. 

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