Train custom domain-specific embedding models and fine-tune LLMs on PAI, build a hybrid retrieval pipeline combining vector search with BM25 keyword search across OpenSearch and Elasticsearch, then deploy the complete inference stack behind Cloudflare edge gateway for low-latency global production serving.
Scenario
Train custom domain-specific embedding models and fine-tune LLMs on PAI, build a hybrid retrieval pipeline combining vector search with BM25 keyword search across OpenSearch and Elasticsearch, then deploy the complete inference stack behind Cloudflare edge gateway for low-latency global production serving.
How the products combine
- airec+alinux+airec+opensearch+alinux+alinux+cloudflare+opensearch+pai+alinux+cloudflare+bailian+es+es+opensearch+oss+oss+pai+opensearch+alinux+es · airec-with-custom-models-and-semantic-search-fe8869 — AIRec with Custom Models and Semantic Search
See _combos/airec-with-custom-models-and-semantic-search-fe8869.
- alinux+bailian+alinux+bailian+alinux+pai+bailian+bailian+es+es+opensearch+oss+oss+pai+es+opensearch+oss+oss+pai+bailian+es+es+opensearch+oss+oss+pai+bailian+pai+bailian+pai+es+alinux+bailian+bailian+pai+es+opensearch+es+opensearch+alinux+oss+rds+alinux+oss+rds+ecs+oss+terraform+ecs+rds+terraform+alinux+rds+ecs+oss+terraform+alinux+rds+es+opensearch+oss+es+rds+es+supabase+bailian+es+es+opensearch+oss+oss+pai+es+rds+terraform+es+vercel+alinux+pai+bailian+es+es+opensearch+oss+oss+pai+bailian+pai+bailian+pai+bailian+es+es+opensearch+oss+oss+pai+es+opensearch+oss+es+oss+pai · full-stack-custom-rag-train-to-production-e68446 — Full-Stack Custom RAG: Train to Production
See _combos/full-stack-custom-rag-train-to-production-e68446.
- airec+opensearch · semantic-search-powered-recommendation-system-5bbd35 — Semantic Search-Powered Recommendation System
See _combos/semantic-search-powered-recommendation-system-5bbd35.
- alinux+alinux+cloudflare+opensearch+pai+alinux+cloudflare+bailian+es+es+opensearch+oss+oss+pai+opensearch · production-rag-with-edge-served-inference-a4f07c — Production RAG with Edge-Served Inference
See _combos/production-rag-with-edge-served-inference-a4f07c.
Typical questions
- train custom RAG and deploy globally with edge inference
- full stack RAG with CDN and custom embeddings
- PAI model training to production edge deployment
- end-to-end RAG pipeline with Cloudflare gateway
- train embeddings and deploy with global edge serving
- 从模型训练到全球边缘部署的完整RAG系统
- PAI训练加OpenSearch检索加Cloudflare边缘推理
- production RAG with edge-accelerated inference
Q: How do I build and deploy an end-to-end RAG pipeline with custom models and global edge inference? A: You can achieve this by training custom domain-specific embedding models and fine-tuning LLMs on PAI, building a hybrid retrieval pipeline across OpenSearch and Elasticsearch, and deploying the stack behind a Cloudflare edge gateway. This configuration delivers low-latency global production serving by combining vector and BM25 keyword search. The workflow integrates multiple cloud services specifically designed for full-stack custom RAG development.