DaaS / Products / Full Custom RAG with Deployed Frontend

Full Custom RAG with Deployed Frontend

Fine-tune a domain-specific LLM and train custom embedding models on PAI, build a vector search pipeline with OpenSearch/Elasticsearch and OSS, deploy the inference backend via Bailian, and deliver a polished chatbot UI on Vercel with infrastructure managed by Terraform.

Products involved

Scenario

Fine-tune a domain-specific LLM and train custom embedding models on PAI, build a vector search pipeline with OpenSearch/Elasticsearch and OSS, deploy the inference backend via Bailian, and deliver a polished chatbot UI on Vercel with infrastructure managed by Terraform.

How the products combine

  1. bailian+bailian+es+es+opensearch+oss+oss+pai+es+opensearch+oss+oss+pai · custom-rag-train-embeddings-to-production-app-9bbc6d — Custom RAG: Train Embeddings to Production App
  2. See _combos/custom-rag-train-embeddings-to-production-app-9bbc6d.

  3. bailian+es+es+opensearch+oss+oss+pai · custom-rag-pipeline-train-embeddings-to-deploy-a-956ae5 — Custom RAG Pipeline: Train Embeddings to Deploy Application
  4. See _combos/custom-rag-pipeline-train-embeddings-to-deploy-a-956ae5.

  5. 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 · custom-rag-pipeline-with-deployed-frontend-ba57d2 — Custom RAG Pipeline with Deployed Frontend
  6. See _combos/custom-rag-pipeline-with-deployed-frontend-ba57d2.

  7. alinux+pai+bailian+bailian+es+es+opensearch+oss+oss+pai+es+opensearch+oss+oss+pai+bailian+es+es+opensearch+oss+oss+pai+bailian+pai · full-custom-rag-custom-llm-custom-embeddings-75fbf5 — Full Custom RAG: Custom LLM + Custom Embeddings
  8. See _combos/full-custom-rag-custom-llm-custom-embeddings-75fbf5.

Typical questions

FAQ

Q: How do I build a fully custom RAG system with a deployed web frontend? A: You can implement this architecture by fine-tuning a domain-specific LLM and training custom embedding models on PAI, then delivering a polished chatbot UI on Vercel with infrastructure managed by Terraform. The setup connects these components using a vector search pipeline built with OpenSearch or Elasticsearch and OSS, while the inference backend is deployed via Bailian.