How to Build a Real-Time AI Recommendation Agent Using AWS Bedrock and Kinesis

A software developer has published a technical guide detailing how to build an AI-powered recommendation system that responds to user behavior in real time, replacing traditional batch-processing approaches. The architecture uses Amazon Kinesis to ingest and route user interaction events, AWS Lambda to process and enrich those events, and Amazon Bedrock as the AI reasoning and recommendation layer. DynamoDB stores user profiles and caches fresh recommendations, while S3 archives raw events for future model retraining. A key design choice keeps the AI inference pipeline fully asynchronous, so users are served cached recommendations instantly while updated ones are computed in the background. The result is a system where a user's recommendation set can refresh within seconds of their behavior changing, rather than waiting for an overnight batch job.