End-to-End Trained RAG Platform with Event-Driven Serving

Scenario

Use Terraform to deploy the full ML pipeline (EventBridge + DataWorks ingestion → PAI training of custom embeddings/rerankers → production RAG on Elasticsearch/Bailian) from Combo 3, then wire Combo 1's EventBridge-driven knowledge base update mechanism on top so that when new documents land in storage, the serving layer automatically re-indexes using the custom-trained models — creating a closed-loop system from raw data through model training to live event-driven RAG serving.

How the products combine

1. eb · event-driven-rag-knowledge-base-pipeline-6fa59f — Event-Driven RAG Knowledge Base Pipeline

See _combos/event-driven-rag-knowledge-base-pipeline-6fa59f.

2. dataworks · multi-modal-content-platform-with-search-and-str-b003fb — Multi-Modal Content Platform with Search and Streaming

See _combos/multi-modal-content-platform-with-search-and-str-b003fb.

3. airec · event-pipeline-to-production-rag-platform-d21287 — Event Pipeline to Production RAG Platform

See _combos/event-pipeline-to-production-rag-platform-d21287.

4. airec · full-stack-live-commerce-intelligence-platform-87a422 — Full-Stack Live Commerce Intelligence Platform

See _combos/full-stack-live-commerce-intelligence-platform-87a422.

Typical questions

• train custom embeddings and deploy event-driven RAG
• end-to-end RAG from data pipeline to live serving
• EventBridge ingestion to PAI training to auto-updating knowledge base
• Terraform deploy full RAG with auto-reindex on new docs
• production RAG platform with custom models and event-driven updates
• 从数据管道到模型训练到自动更新RAG服务
• Terraform部署完整RAG平台含自动索引更新
• DataWorks加工数据训练模型后自动服务RAG

Q: How do I deploy an end-to-end RAG platform with custom models and event-driven serving? A: The platform is deployed as a cross-product combination spanning numerous integrated cloud services. It provides an end-to-end architecture for trained RAG with event-driven serving. Infrastructure provisioning is handled via Terraform.