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