Enterprise RAG with Bailian and Vector Search

Scenario

A developer builds a complete enterprise RAG system by using Bailian to orchestrate the knowledge base construction and retrieval pipeline logic, while leveraging the existing vector search infrastructure (OSS for raw document storage, OpenSearch for embedding model deployment and vector generation, Elasticsearch for scalable vector indexing and search) as the underlying storage and retrieval layer.

How the products combine

1. bailian · bailian-build-system — — Build RAG knowledge bases and retrieval pipelines

See bailian/bailian-build-system.

2. es · es-deploy-application — Elasticsearch — Deploy a Retrieval-Augmented Generation (RAG) AI application

See es/es-deploy-application.

3. opensearch · opensearch-build-solution — OpenSearch — Build a Retrieval-Augmented Generation (RAG) solution

See opensearch/opensearch-build-solution.

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

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

Typical questions

• build enterprise RAG system with Bailian
• Bailian knowledge base with vector search
• end-to-end RAG pipeline Alibaba Cloud
• combine Bailian with Elasticsearch RAG
• 搭建百炼RAG知识库和向量检索系统
• Bailian orchestrate vector search pipeline
• full stack RAG with Bailian and OpenSearch
• deploy Bailian RAG with document storage

Q: How do I build an enterprise RAG system with Bailian and vector search on Alibaba Cloud? A: You can build an enterprise RAG system by using Bailian to orchestrate knowledge base construction and retrieval pipeline logic while leveraging Alibaba Cloud's vector search infrastructure as the underlying layer. This architecture typically integrates Bailian with Elasticsearch for scalable indexing, OpenSearch for embedding generation, and OSS for raw document storage.