Give Your AI Agents a Real Memory with RAG

Turn scattered files into structured knowledge your agents can instantly retrieve for smarter, context-aware answers 🧠

AI Data Storage — no vector DBs, no complex setup. Just upload & go.

RAG is Essential for AI Agents

Without RAG, your AI agents are flying blind - limited to their prompts and whatever data they can pull in real time. They can’t “remember” past interactions or access your unique knowledge base 💡

RAG changes that. By storing and indexing your documents, images, and structured data, your agents can:

  • Answer with precision — retrieving only the most relevant facts.
  • Stay consistent — using the same source of truth for every reply.
  • Scale effortlessly — no need to retrain models or rewrite prompts for new data.

This means fewer hallucinations, faster responses, and higher trust from your users - all while keeping control of your proprietary information.

How RAG Works in Latenode

Upload & Index

Drag-and-drop PDFs, text, images (with OCR), or other files. We automatically chunk and embed them for high-accuracy retrieval.

Search Instantly

Add a RAG Search node to any workflow, pick your storage, ask in plain language, and get the most relevant chunks in milliseconds.

Power Smarter Agents

Connect the search results directly to an AI Agent node so your bots can answer with context from your docs - whether for chat, support, or multi-agent automations.

Build document-aware workflows without writing a single retrieval query.

Why Build with Latenode’s RAG

Faster Deployment

Go from upload to live agent in minutes.

No API Hassles

Access all top LLMs via one subscription.

Smarter Agents

Answer with context, not just guesswork.

Ready to Build Your First RAG‑Enabled Agent?

Just Upload & Go 🤖