About This Architecture

Production-grade conversational AI architecture combining serverless request handling with dedicated ML inference infrastructure on AWS. Internet Users connect through CloudFront CDN to an Application Load Balancer, routing to API Gateway and Lambda Functions for request processing, which orchestrate EC2 Instances and SageMaker for model inference. ElastiCache Redis maintains session state while DynamoDB persists conversation history, with Kinesis streaming events to CloudWatch for observability. Ideal for architects building scalable chatbot or LLM-powered applications requiring low-latency responses and durable context. Fork this diagram on Diagrams.so to adapt the inference layer for your model serving requirements.

People also ask

How do you architect a ChatGPT-style conversational AI system on AWS?

Route users through CloudFront and ALB to API Gateway, use Lambda for request orchestration, SageMaker or EC2 for inference, ElastiCache for sessions, and DynamoDB for history. This diagram shows the complete pattern.