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IT ops AI SlackBot workflow - chat with your knowledge base

Angel MenendezAngel Menendez
39013 views
2/3/2026
Official Page

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Video Demo:

Click here to see a video of this workflow in action.

Summary Description:

The "IT Department Q&A Workflow" is designed to streamline and automate the process of handling IT-related inquiries from employees through Slack. When an employee sends a direct message (DM) to the IT department's Slack channel, the workflow is triggered. The initial step involves the "Receive DMs" node, which listens for new messages. Upon receiving a message, the workflow verifies the webhook by responding to Slack's challenge request, ensuring that the communication channel is active and secure.

Once the webhook is verified, the workflow checks if the message sender is a bot using the "Check if Bot" node. If the sender is identified as a bot, the workflow terminates the process to avoid unnecessary actions. If the sender is a human, the workflow sends an acknowledgment message back to the user, confirming that their query is being processed. This is achieved through the "Send Initial Message" node, which posts a simple message like "On it!" to the user's Slack channel.

The core functionality of the workflow is powered by the "AI Agent" node, which utilizes the OpenAI GPT-4 model to interpret and respond to the user's query. This AI-driven node processes the text of the received message, generating an appropriate response based on the context and information available. To maintain conversation context, the "Window Buffer Memory" node stores the last five messages from each user, ensuring that the AI agent can provide coherent and contextually relevant answers.

Additionally, the workflow includes a custom Knowledge Base (KB) tool (see that tool template here) that integrates with the AI agent, allowing it to search the company's internal KB for relevant information. After generating the response, the workflow cleans up the initial acknowledgment message using the "Delete Initial Message" node to keep the conversation thread clean. Finally, the generated response is sent back to the user via the "Send Message" node, providing them with the information or assistance they requested. This workflow effectively automates the IT support process, reducing response times and improving efficiency.

To quickly deploy the Knowledge Ninja app in Slack, use the app manifest below and don't forget to replace the two sample urls:

{
    "display_information": {
        "name": "Knowledge Ninja",
        "description": "IT Department Q&A Workflow",
        "background_color": "#005e5e"
    },
    "features": {
        "bot_user": {
            "display_name": "IT Ops AI SlackBot Workflow",
            "always_online": true
        }
    },
    "oauth_config": {
        "redirect_urls": [
            "Replace everything inside the double quotes with your slack redirect oauth url, for example: https://n8n.domain.com/rest/oauth2-credential/callback"
        ],
        "scopes": {
            "user": [
                "search:read"
            ],
            "bot": [
                "chat:write",
                "chat:write.customize",
                "groups:history",
                "groups:read",
                "groups:write",
                "groups:write.invites",
                "groups:write.topic",
                "im:history",
                "im:read",
                "im:write",
                "mpim:history",
                "mpim:read",
                "mpim:write",
                "mpim:write.topic",
                "usergroups:read",
                "usergroups:write",
                "users:write",
                "channels:history"
            ]
        }
    },
    "settings": {
        "event_subscriptions": {
            "request_url": "Replace everything inside the double quotes with your workflow webhook url, for example: https://n8n.domain.com/webhook/99db3e73-57d8-4107-ab02-5b7e713894ad",
            "bot_events": [
                "message.im"
            ]
        },
        "org_deploy_enabled": false,
        "socket_mode_enabled": false,
        "token_rotation_enabled": false
    }
}

n8n IT Ops AI Slackbot Workflow - Chat with Your Knowledge Base

This n8n workflow automates an AI-powered Slackbot that can answer questions by querying a knowledge base (represented by another n8n workflow). It listens for incoming Slack messages, processes them with an AI agent, and responds in Slack.

What it does

This workflow streamlines IT operations by providing an AI assistant that can interact with users in Slack and leverage a knowledge base to answer queries.

  1. Receives Slack Messages: It listens for incoming messages via a webhook, likely triggered by a Slack integration (e.g., a Slash Command or an Event Subscription).
  2. Filters Messages: An "If" node checks for a specific condition (e.g., if the message contains a certain keyword or is a direct mention), allowing the bot to selectively respond.
  3. Processes with AI Agent: If the condition is met, an AI Agent (powered by LangChain) takes the user's query.
    • It uses an OpenAI Chat Model for natural language understanding and generation.
    • It maintains Simple Memory to remember previous interactions within a conversation.
    • It utilizes a "Call n8n Workflow Tool" to interact with an external knowledge base (another n8n workflow) to retrieve relevant information.
  4. Responds to Slack: After processing, the AI Agent's response is sent back to the Slack channel where the original message originated.
  5. Handles Non-Matches: If the initial filter condition is not met, the workflow performs a "No Operation," effectively ignoring the message.
  6. Responds to Webhook: It sends a response back to the initial webhook trigger, acknowledging receipt of the message.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Slack Account: A Slack workspace and an app configured to send and receive messages (e.g., via a webhook or event subscription).
  • OpenAI API Key: An OpenAI API key for the Chat Model.
  • Another n8n Workflow: A separate n8n workflow that acts as your "knowledge base" and can be called by the "Call n8n Workflow Tool" to retrieve information.

Setup/Usage

  1. Import the workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your Slack credential for the "Slack" node.
    • Set up your OpenAI credential for the "OpenAI Chat Model" node.
  3. Configure Webhook:
    • Copy the URL from the "Webhook" trigger node.
    • Configure your Slack app to send events (e.g., message.channels, app_mention) or slash commands to this Webhook URL.
  4. Configure the "If" Node: Adjust the conditions in the "If" node (ID 20) to match how you want your bot to be triggered (e.g., {{ $json.event.text.includes('bot') }} or {{ $json.event.type === 'app_mention' }}).
  5. Configure the "Call n8n Workflow Tool":
    • Specify the URL and any necessary authentication for your knowledge base n8n workflow.
    • Ensure your knowledge base workflow is set up to receive input and return relevant information.
  6. Activate the workflow: Once configured, activate the workflow in n8n.

Your AI Slackbot will now be ready to interact with users and leverage your knowledge base!

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