DaaS / Products / Full-Stack Custom RAG: Train to Production

Full-Stack Custom RAG: Train to Production

A team trains domain-specific embedding models and fine-tunes LLMs on PAI using curated datasets, builds a hybrid retrieval pipeline combining custom-trained vector embeddings with BM25 keyword search across OpenSearch and Elasticsearch backed by OSS document storage, then applies neural reranking, synonym expansion, and relevance tuning before deploying the complete RAG application to production end users.

Products involved

Scenario

A team trains domain-specific embedding models and fine-tunes LLMs on PAI using curated datasets, builds a hybrid retrieval pipeline combining custom-trained vector embeddings with BM25 keyword search across OpenSearch and Elasticsearch backed by OSS document storage, then applies neural reranking, synonym expansion, and relevance tuning before deploying the complete RAG application to production end users.

How the products combine

  1. es+oss+pai · ml-powered-semantic-search-pipeline-b3728a — ML-Powered Semantic Search Pipeline

    2. See _combos/ml-powered-semantic-search-pipeline-b3728a.

  2. 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 · custom-rag-with-optimized-search-relevance-707e4a — Custom RAG with Optimized Search Relevance

    3. See _combos/custom-rag-with-optimized-search-relevance-707e4a.

  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.

  4. es+opensearch+oss · vector-search-rag-pipeline-on-alibaba-cloud-96d675 — Vector Search RAG Pipeline on Alibaba Cloud

    5. See _combos/vector-search-rag-pipeline-on-alibaba-cloud-96d675.

Typical questions

FAQ

Q: How do I build and deploy a complete custom RAG pipeline from model training to production? A: You can build and deploy a complete custom RAG pipeline by training domain-specific embedding models and fine-tuning LLMs on PAI, then constructing a hybrid retrieval system with custom vector embeddings and BM25 keyword search across OpenSearch and Elasticsearch backed by OSS document storage. After applying neural reranking and relevance tuning, the entire application is deployed directly to production end users.