Build an AI-powered course recommender using Amazon Bedrock and AWS End User Messaging

This article demonstrates building an AI-powered course recommendation system for EdTech using Amazon Bedrock and AWS End User Messaging via WhatsApp.

• Users discover courses through WhatsApp conversations with personalized AI recommendations
• AWS End User Messaging captures WhatsApp messages and publishes to Amazon SNS
• Amazon Bedrock with Claude 3 Haiku powers natural language understanding and agent actions
• Amazon Titan Embeddings enable semantic search for course matching beyond keyword matching
• Amazon OpenSearch Serverless handles vector similarity matching with traditional filters
• Messages stored in S3, catalogued via AWS Glue, analyzed with Athena and QuickSight dashboards
• Exponential backoff and retry logic ensure resilience and error handling
• Serverless architecture scales automatically without manual infrastructure management
• Future enhancements include voice integration, predictive analytics, and digital admissions

This solution combines conversational AI with educational services to improve student retention, engagement, and learning outcomes while providing operational efficiency through automation and analytics.