Case Study

Scaler Achieves Near Real-Time Audio Transcription, Driving Productivity with CloudThat

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Amazon SageMaker, Amazon Bedrock, Amazon S3, Amazon OpenSearch, Amazon Translate, Amazon Comprehend, AWS Lambda, Amazon API Gateway, AWS IAM, AWS CloudTrail, Amazon CloudWatch


Near real-time audio transcription, end-to-end GenAI solution implementation, reduced manual transcription efforts, NoSQL DynamoDB storage optimization, and automated deployment with AWS CloudFormation.

About the Client

Scaler is an E-Learning platform that empowers tech professionals worldwide. It has 90M monthly search impressions, 100K daily users, 4,500+ expert articles, 25+ video courses, and 3,00+ interactive challenges. 


End-to-end Gen AI Solutions

Streamlining the Deployment

Near Real-Time Transcription

Amazon SageMaker


Increased Productivity

The Challenge

Scaler Academy aims to improve its e-learning experience but faces challenges analyzing live calls promptly, which hinders sales team optimization. To overcome this, they approached CloudThat to leverage AWS services and enhance user experience. 


  • Client’s data and audio files are stored securely in an Amazon S3 bucket. 
  • Established pipeline with openai-Whisper for accurate audio transcription and translation. 
  • Integrated Anthropic Claude v1.2 model via Amazon SageMaker for advanced natural language processing. 
  • Utilized Cohere’s Amazon Bedrock-powered model for actionable insights extraction. 
  • Implemented Amazon DynamoDB for scalable metadata storage. 
  • Automated deployment and configuration using AWS CloudFormation template. 

The Results

Enhanced operational efficiency and productivity through near real-time transcription, end-to-end GenAI solution, reduced manual efforts, efficient metadata storage, and streamlined AWS deployment. 

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