About This Architecture

Agentic generative AI system deployed in AWS Mumbai (ap-south-1) combines Amazon Bedrock for LLM orchestration, pgvector-enabled RDS PostgreSQL for semantic search, and Step Functions for task workflow automation. CloudFront delivers a Cognito-secured SPA while API Gateway routes requests to specialized Lambda functions handling MIS reporting, chatbot interactions, and task management. Architecture demonstrates enterprise-grade AI integration with external ERP systems, Power BI analytics, and comprehensive security via WAF, KMS, and CloudTrail. Fork this diagram on Diagrams.so to customize the Lambda function logic, swap Bedrock models, or adapt the workflow orchestration for your regional deployment. Multi-subnet design isolates compute, AI/data, and orchestration layers following AWS Well-Architected best practices for production generative AI workloads.

People also ask

How do I architect an agentic generative AI system on AWS with Bedrock, pgvector for semantic search, and Step Functions for task orchestration?

Deploy Amazon Bedrock AgentCore with pgvector-enabled RDS PostgreSQL for semantic search, Lambda functions for MIS/chatbot/task logic, and Step Functions for workflow orchestration. Secure with CloudFront, WAF, Cognito, and isolate compute/AI/orchestration in separate subnets. This AWS Mumbai diagram shows production-ready integration with external ERPs and Power BI.