Extend the full-stack Notion AI agent (Skill 3) with a custom RAG pipeline (Skill 4): train domain-specific embedding models on PAI, build a vector knowledge base in OpenSearch/OSS, and wire the Bailian-hosted agent to retrieve from both Notion (content management via OAuth/MCP) and the custom RAG store (domain knowledge) — all fronted by a single Vercel chatbot UI authenticated via IDaaS.
Extend the full-stack Notion AI agent (Skill 3) with a custom RAG pipeline (Skill 4): train domain-specific embedding models on PAI, build a vector knowledge base in OpenSearch/OSS, and wire the Bailian-hosted agent to retrieve from both Notion (content management via OAuth/MCP) and the custom RAG store (domain knowledge) — all fronted by a single Vercel chatbot UI authenticated via IDaaS.
See _combos/static-site-with-ai-backend-990f4c.
See _combos/notion-ai-cms-on-vercel-d897b6.
See _combos/full-stack-notion-ai-agent-with-deployed-fronten-33dde2.
See _combos/custom-rag-pipeline-with-deployed-frontend-ba57d2.
Q: How do I build an end-to-end full-stack Notion AI agent with a custom RAG knowledge base? A: You can extend a full-stack Notion AI agent with a custom RAG pipeline by training domain-specific embedding models on PAI and building a vector knowledge base in OpenSearch or OSS. The Bailian-hosted agent retrieves data from both your Notion workspace via OAuth/MCP and the custom RAG store, all delivered through a single Vercel chatbot UI authenticated via IDaaS.