Design a no-code retrieval-augmented generation pipeline that ingests internal documents, chunks and embeds them, keeps the index fresh, and answers questions with grounded, cited responses.
## CONTEXT Every organization sits on a sprawl of knowledge: wikis, PDFs, support macros, contracts, Slack threads, and product docs, and employees waste hours hunting for answers that exist somewhere. Retrieval-augmented generation (RAG) turns that sprawl into an answer engine, and by 2026 no-code platforms like n8n…
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