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EdTech
Amazon EC2, Open Source Whisper, Amazon Bedrock, Amazon S3, Amazon DynamoDB, AWS Lambda
Streamlined NLP and Data Management with AWS Solutions Leading to Improved Operational Efficiency
Scaler is an e-learning platform for working tech professionals. The platform garners over 90 million monthly search impressions and has over 100,000 daily users. It hosts over 4,500 articles created by industry experts, along with 25+ video courses from top Scaler Instructors who are industry veterans. Scaler offers 3,000+ interactive challenges for learning and competition. Scaler is devoted to creating an ecosystem that nurtures its learners and assists them in unlocking their talent.
Productivity Increase
Latency Reduction
Process Streamlining
Scaler Academy provides a comprehensive e-learning experience but faces challenges in analyzing live calls in near real-time for their sales team. This hinders their ability to provide timely recommendations and optimize their business processes, such as improving sales calls for better outcomes. Overcoming these challenges will be key to making their new system work smoothly and helping their business grow even more. To address these challenges, the customer approached CloudThat to leverage AWS services to elevate the overall e-learning experience for Scaler Academy’s users.
• The client’s data and audio files are stored in an Amazon S3 bucket, ensuring data security and integrity.
• Established a comprehensive pipeline for processing audio files, utilizing a model known as openai-Whisper. This pipeline efficiently converts audio content into text, enabling accurate transcription and subsequent translation to facilitate multilingual support.
• Leveraged Amazon SageMaker for managing a sophisticated Large Language Model (LLM) designed for natural language processing tasks. Integrated the Anthropic Claude v1.2 model into the system, leveraging Amazon Bedrock for enhanced performance and efficiency. This integration allows for contextual question answering, thereby augmenting the intelligence and capability of the overall system.
• Transformed embedded data into actionable insights with Cohere’s Amazon Bedrock powered model, enabling seamless training, deployment, auto-scaling, and endpoint monitoring to efficiently extract valuable Named Entity Recognition (NER) entities like Company Names, Job Roles, and Skills.
• Established an Amazon DynamoDB database to serve as a reliable and scalable storage solution for metadata associated with the implemented solutions. Configured the database schema to efficiently store and retrieve relevant metadata, enhancing the overall manageability and accessibility of critical information tied to the solutions.
• Implemented AWS CloudFormation template to automate the deployment and configuration of the entire solution. This template encapsulates the infrastructure as code, facilitating consistent and repeatable deployment across different environments
The solution enhanced the customer’s data management and scalability through AWS automation, optimizing processes such as data transfer from FTP to Amazon EC2, storage in Amazon S3, migration to Amazon Redshift, and seamless execution of transformation queries via Amazon EventBridge and AWS DMS.
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