AI: Using RAG-Based Enquiry Assistant using Vector Database

Developing a RAG-Based Enquiry Assistant with Amazon Bedrock, Vector Databases, and Full-Stack Integration

🧩 Enhanced Learning Objectives:

  • Apply RAG principles using Amazon Bedrock’s agent and knowledge base

  • Integrate real-time data sources (e.g., DynamoDB) with static knowledge (e.g., CSV in S3)

  • Build a RESTful backend using AWS Lambda and API Gateway

  • Create a responsive chatbot frontend using React and Chatbotify

  • Deploy and secure the application using S3 and CloudFront

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