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Slack AI Chatbot with RAG for company staff

21 nodes · agent, memoryBufferWindow, embeddingsOpenAi, vectorStoreQdrant, toolCalculator, slack

Engine
n8n
Nodes
21
Trigger
scheduled/triggered
Source file
1643_Slack_Manual_Automate_Webhook.json

Workflow flow

IntegrationsAgentMemoryBufferWindowEmbeddingsOpenAiVectorStoreQdrantToolCalculatorSlackManualHTTPGoogle DriveDocumentDefaultDataLoaderTextSplitterTokenSplitterLmChatAnthropic+8 more
100%

Simple Memory

@n8n/n8n-nodes-langchain.memoryBufferWindow

Embeddings OpenAI1

@n8n/n8n-nodes-langchain.embeddingsOpenAi

RAG

@n8n/n8n-nodes-langchain.vectorStoreQdrant

Calculator

@n8n/n8n-nodes-langchain.toolCalculator

TRIGGER

Get message

Slack

TRIGGER

When clicking ‘Test workflow’

Manual

Default Data Loader

@n8n/n8n-nodes-langchain.documentDefaultDataLoader

Token Splitter

@n8n/n8n-nodes-langchain.textSplitterTokenSplitter

Embeddings OpenAI2

@n8n/n8n-nodes-langchain.embeddingsOpenAi

Anthropic Chat Model

@n8n/n8n-nodes-langchain.lmChatAnthropic

AI Agent

@n8n/n8n-nodes-langchain.agent

Create collection

HTTP

Refresh collection

HTTP

Send message

Slack

Get folder

Google Drive

Download Files

Google Drive

Qdrant Vector Store1

@n8n/n8n-nodes-langchain.vectorStoreQdrant

17 steps · flows top to bottom, branches left to right

Browse by integration

agentmemoryBufferWindowembeddingsOpenAivectorStoreQdranttoolCalculatorslackmanualhttpRequestgoogleDrivedocumentDefaultDataLoadertextSplitterTokenSplitterlmChatAnthropic
Browse all integrations →
Download n8n JSONDownload sanitized JSONDownload flow graph

Import into n8n

  1. Download the n8n JSON file (full or sanitized).
  2. In n8n: Workflows → Import from file.
  3. Open each node and reconnect credentials to your accounts.
  4. Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

Free n8n workflow: Slack AI Chatbot with RAG for company staff. 21 nodes across agent, memoryBufferWindow, embeddingsOpenAi, vectorStoreQdrant, toolCalculator, slack, manual, httpRequest, with a downloadable JSON and a visual flow diagram on OpenRuna.

What this workflow does

Built in n8n, "Slack AI Chatbot with RAG for company staff" chains 21 nodes to move data between agent, memoryBufferWindow, embeddingsOpenAi, vectorStoreQdrant, toolCalculator, slack, manual, httpRequest. 21 nodes · agent, memoryBufferWindow, embeddingsOpenAi, vectorStoreQdrant, toolCalculator, slack It starts from a scheduled/triggered trigger and routes data through every node in order. OpenRuna renders the node graph and offers the JSON export so you can import and adapt it in minutes. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Fork it to add error handling, retries, or a notification step without designing the 21-node flow from scratch.
  • Benchmark it against your current agent integration to spot missing steps or redundant nodes.
  • Study how data moves from agent to memoryBufferWindow before building your own variant.
  • Share it with your team as a documented reference for scheduled/triggered automations in the agent stack.

Example output

Imported into n8n, "Slack AI Chatbot with RAG for company staff" exposes 21 configured nodes. Trigger type: scheduled/triggered. Integrations: agent, memoryBufferWindow, embeddingsOpenAi, vectorStoreQdrant, toolCalculator, slack, manual, httpRequest. Reconnect the agent credential first, then walk the remaining nodes top to bottom. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Ask Claude to turn the "Slack AI Chatbot with RAG for company staff" JSON into a plain-English runbook, node by node. It can flag where agent rate limits or missing retries might bite before you go live.

ChatGPT

Drop the workflow JSON or this OpenRuna page URL into ChatGPT and ask for a step-by-step runbook: triggers, branches, and which fields to customise for agent, memoryBufferWindow, embeddingsOpenAi, vectorStoreQdrant, toolCalculator, slack, manual, httpRequest. Handy for onboarding teammates new to n8n.

Cursor

In Cursor, ask Agent mode to parameterise "Slack AI Chatbot with RAG for company staff" — extract agent IDs and secrets into environment variables without changing the 21-node structure.

Frequently asked questions

How do I import "Slack AI Chatbot with RAG for company staff" into n8n?
Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "Slack AI Chatbot with RAG for company staff" use?
It uses: agent, memoryBufferWindow, embeddingsOpenAi, vectorStoreQdrant, toolCalculator, slack, manual, httpRequest. The flow diagram above shows how each service connects across the 21 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?
Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own agent and memoryBufferWindow credentials in n8n after import.
What trigger type does "Slack AI Chatbot with RAG for company staff" use?
Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "Slack AI Chatbot with RAG for company staff" free to use?
OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for agent, memoryBufferWindow, embeddingsOpenAi, vectorStoreQdrant, toolCalculator, slack, manual, httpRequest.

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