About This Architecture

Enterprise-grade GenAI plant MIS reporting platform deployed on AWS Mumbai Region combines Amazon Bedrock foundation models with agentic orchestration via Step Functions. User requests flow through CloudFront and WAF to an EKS-hosted React SPA, routing to specialized microservices for reports, tasks, and conversational AI via API Gateway and Lambda functions. The architecture implements RAG patterns using RDS pgvector for knowledge retrieval, DynamoDB for conversation state, and S3 for report artifacts, with EventBridge enabling near-realtime synchronization across data stores. Comprehensive observability through CloudWatch, X-Ray, and CloudTrail ensures production-grade monitoring, while Cognito, KMS, and GuardDuty provide defense-in-depth security. Fork this diagram on Diagrams.so to customize the GenAI tier, adjust the agentic workflow, or adapt the data persistence layer for your manufacturing intelligence platform.

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How do I architect a GenAI-powered enterprise reporting platform on AWS with agentic orchestration and RAG patterns?

Deploy Amazon Bedrock foundation models with Step Functions orchestrating supervisor, task, and RAG agents. Use EKS for microservices, RDS pgvector for knowledge retrieval, DynamoDB for conversation state, and EventBridge for realtime sync. This AWS Mumbai diagram shows the complete architecture with security, observability, and data persistence layers.