Build an AI Agent that will index new documents in n8n

An n8n workflow that fires when someone asks a question in Slack, then an AI agent chunks and embeds the document into your vector store — giving you your knowledge base kept up to date automatically. No code: import the JSON, connect your apps, and it runs 24/7.

difficulty Advancedsetup 1 hourresult Your knowledge base kept up to date automatically
  1. 1

    Trigger when someone asks a question in Slack

    A Slack Trigger starts the workflow the moment someone asks a question in Slack.

  2. 2

    Retrieve the right context

    A Vector Store node (Pinecone) fetches the most relevant passages from your indexed content so the answer is grounded in your own material.

  3. 3

    Hand it to the AI agent

    An AI Agent node running Claude chunks and embeds the document into your vector store. The prompt is pre-written and scoped to this one job so results stay consistent.

  4. 4

    Deliver the indexing

    The result is sent to Telegram — ready for a human to approve.

  5. 5

    Add a safety net (optional)

    Insert an IF/human-approval step before anything is published or emailed, so you stay in control until you trust the output.

Frequently asked questions

Does this need n8n Cloud or can I self-host?

Either works. The workflow is a standard n8n export, so you can run it on n8n Cloud or on your own self-hosted instance — you only connect your own app credentials.

How do I import the workflow into n8n?

Download the JSON, then in n8n open a new workflow, choose ⋯ → Import from file, and select it. Every trigger, node and connection appears on the canvas; you just add your credentials and activate it.

How much does the AI part cost to run?

Pennies. Each run sends a small amount of text to the model, so most teams spend a few dollars a month even at hundreds of runs. You set the model and can cap volume in n8n, so costs never surprise you.

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