2,132 n8n Slack workflow templates

The Slack node posts messages, opens threads, uploads files and adds reactions, while its trigger fires on messages, mentions and slash commands. That pairing makes Slack the usual place to put a workflow’s output, where the people who need it already are, and the usual place to accept a human approval step inside an otherwise unattended run. The templates here cover both roles.

• IT Ops AI SlackBot Workflow - Chat with your knowledge base

  by Angel Menendez · web · 27,843 clicks

  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.

  • 5 nodes
  • 27,843 views

  Workflow detailsImport from n8n.ioAutomation, AI

• Phishing Analysis - URLScan.io and VirusTotal

  by n8n Team · web · 26,877 clicks

  This n8n workflow automates the analysis of email messages received in a Microsoft Outlook inbox to identify indicators of compromise (IOCs), specifically suspicious URLs. It can be triggered manually or scheduled to run daily at midnight. The workflow begins by retrieving up to 100 read email messages from the Outlook inbox. However, there seems to be a configuration issue as it should retrieve unread messages, not read ones. It then marks these messages as read to avoid processing them again in the future. The messages are then split into individual items using the Split In Batches node for sequential processing. For each email, the workflow analyzes its content to find URLs, which are considered potential IOCs. If URLs are found, the workflow proceeds to check these URLs for potential threats using two services, URLScan.io and VirusTotal, in parallel. In the first path, URLScan.io scans each URL, and if there are no errors, the results from URLScan.io and VirusTotal are merged. If there are errors, the workflow waits 1 minute before attempting to retrieve the URLScan results again. The loop then continues for the next email. In the second path, VirusTotal is used to scan the URLs, and the results are retrieved. Finally, the workflow checks if the data field is not empty, filtering out items where no data was found. It then sends a summarized Slack message to report details about the analyzed email, including the subject, sender, date, URLScan report URL, and VirusTotal verdict for URLs that were reported as malicious. Potential issues during setup include configuring the Outlook node to retrieve unread messages, resolving a configuration issue in the VirusTotal node, and handling authentication and API keys for both URLScan.io and VirusTotal nodes. Additionally, proper error handling and testing with various email content types and URLs are essential to ensure the workflow accurately identifies IOCs and reports them to the Slack channel. An n8n automation workflow template by n8n Team.

  • 5 nodes
  • 26,877 views

  Workflow detailsImport from n8n.ioAutomation

• Advanced AI Demo (Presented at AI Developers #14 meetup)

  by Max Tkacz · web · 24,254 clicks

  This workflow was presented at the AI Developers meet up in San Fransico on 24 July, 2024. AI workflows Categorize incoming Gmail emails and assign custom Gmail labels. This example uses the Text Classifier node, simplifying this usecase. Ingest a PDF into a Pinecone vector store and chat with it (RAG example) AI Agent example showcasing the HTTP Request tool. We teach the agent how to check availability on a Google Calendar and book an appointment. An n8n automation workflow template by Max Tkacz.

  • 16 nodes
  • 24,254 views

  Workflow detailsImport from n8n.ioAutomation, AI

• Automate Customer Support Issue Resolution using AI Text Classifier

  by Jimleuk · web · 23,330 clicks

  This n8n template is designed to assist and improve customer support team member capacity by automating the resolution of long-lived and forgotten JIRA issues. How it works Schedule Trigger runs daily to check for long-lived unresolved issues and imports them into the workflow. Each Issue is handled as a separate subworkflow by using an execute workflow node. This allows parallel processing. A report is generated from the issue using its comment history allowing the issue to be classified by AI - determining the state and progress of the issue. If determined to be resolved, sentiment analysis is performed to track customer satisfaction. If negative, a slack message is sent to escalate, otherwise the issue is closed automatically. If no response has been initiated, an AI agent will attempt to search and resolve the issue itself using similar resolved issues or from the notion database. If a solution is found, it is posted to the issue and closed. If the issue is blocked and waiting for responses, then a reminder message is added. How to use This template searches for JIRA issues which are older than 7 days which are not in the "Done" status. Ensure there are some issues that meet this criteria otherwise adjust the search query to suit. Works best if you frequently have long-lived issues that need resolving. Ensure the notion tool is configured as to not read documents you didn't intend it to ie. private and/or internal documentation. Requirements JIRA for issues management OpenAI for LLM Slack for notifications Customising this workflow Why not try classifying issues as they are created? One use-case may be for quality control such as ensuring reporting criteria is adhered to, summarising and rephrasing issue for easier reading or adjusting priority. An n8n automation workflow template by Jimleuk.

  • 8 nodes
  • 23,330 views

  Workflow detailsImport from n8n.ioAutomation, AI

• Host your own Uptime Monitoring with Scheduled Triggers

  by Jimleuk · web · 21,003 clicks

  This n8n workflow demonstrates how to build a simple uptime monitoring service using scheduled triggers. Useful for webmasters with a handful of sites who want a cost-effective solution without the need for all the bells and whistles. How it works Scheduled trigger reads a list of website urls in a Google Sheet every 5 minutes Each website url is checked using the HTTP node which determines if the website is either in the UP or DOWN state. An email and Slack message are sent for websites which are in the DOWN state. The Google Sheet is updated with the website's state and a log created. Logs can be used to determine total % of UP and DOWN time over a period. Requirements Google Sheet for storing websites to monitor and their states Gmail for email alerts Slack for channel alerts Customising the workflow Don't use Google Sheets? This can easily be exchanged with Excel or Airtable. An n8n automation workflow template by Jimleuk.

  • 4 nodes
  • 21,003 views

  Workflow detailsImport from n8n.ioAutomation

• AI-Powered Information Monitoring with OpenAI, Google Sheets, Jina AI and Slack

  by Dataki · web · 18,013 clicks

  Check Legal Regulations: This workflow involves scraping, so ensure you comply with the legal regulations in your country before getting started. Better safe than sorry! 📌 Purpose This workflow enables automated and AI-driven topic monitoring, delivering concise article summaries directly to a Slack channel in a structured and easy-to-read format. It allows users to stay informed on specific topics of interest effortlessly, without manually checking multiple sources, ensuring a time-efficient and focused monitoring experience. To get started, copy the Google Sheets template required for this workflow from here. 🎯 Target Audience This workflow is designed for: Industry professionals** looking to track key developments in their field. Research teams** who need up-to-date insights on specific topics. Companies** aiming to keep their teams informed with relevant content. ⚙️ How It Works Trigger: A Scheduler initiates the workflow at regular intervals (default: every hour). Data Retrieval: RSS feeds are fetched using the RSS Read node. Previously monitored articles are checked in Google Sheets to avoid duplicates. Content Processing: The article relevance is assessed using OpenAI (GPT-4o-mini). Relevant articles are scraped using Jina AI to extract content. Summaries are generated and formatted for Slack. Output: Summaries are posted to the specified Slack channel. Article metadata is stored in Google Sheets for tracking. 🛠️ Key APIs and Nodes Used Scheduler Node:** Triggers the workflow periodically. RSS Read:** Fetches the latest articles from defined RSS feeds. Google Sheets:** Stores monitored articles and manages feed URLs. OpenAI API (GPT-4o-mini):** Classifies article relevance and generates summaries. Jina AI API:** Extracts the full content of relevant articles. Slack API:** Posts formatted messages to Slack channels. This workflow provides an efficient and intelligent way to stay informed about your topics of interest, directly within Slack. An n8n automation workflow template by Dataki.

  • 7 nodes
  • 18,013 views

  Workflow detailsImport from n8n.ioAutomation, AI

• AI Personal Assistant

  by Max Mitcham · web · 17,754 clicks

  Email Personal Assistant - Comprehensive Communication Manager This automation flow is designed to proactively monitor email, calendar, and Slack communications, analyze priorities across all channels, and generate a comprehensive daily briefing with actionable tasks for executive productivity management. ⚙️ How It Works (Step-by-Step): ⏰ Automated Daily Trigger Runs automatically on weekdays: Scheduled execution every weekday at 8:00 AM Manual trigger available for on-demand analysis Comprehensive daily communication audit 📧 Email Assistant Agent Analyzes inbox priorities and context: Scans unread emails across "To Respond" and "FYI" labels Checks email history to determine relationship context Identifies *company-related opportunities and partnerships Categorizes emails by urgency (High, Medium, Low) Cross-references with sent emails for follow-up context 📅 Follow-Up Assistant Agent Monitors meeting follow-up requirements: Reviews last 3 days of calendar meetings Fetches Fireflies transcripts for recorded sessions Identifies meetings without post-meeting communication Flags meetings requiring action items or follow-ups Checks sent emails and Slack for completed follow-ups 💬 Slack Assistant Agent Tracks Slack communication priorities: Monitors direct messages and @mentions Identifies unreplied Slack conversations Cross-references with email and calendar context Prioritizes responses based on sender importance Checks for threaded conversations requiring attention 🎯 Master Orchestrator Agent Synthesizes all communication data: Combines reports from all three assistant agents Cross-references with existing Google Sheets to-do list Prioritizes tasks by urgency and business impact Identifies correlations between different communication channels Creates comprehensive daily action plan 📊 Task Management Integration Automated tracking and delivery: Appends new tasks to Google Sheets to-do tracker Sends personalized daily briefing via Slack DM Maintains conversation memory for context continuity Tracks outstanding vs.

  • 5 nodes
  • 17,754 views

  Workflow detailsImport from n8n.ioAutomation, AI

• 🤖 Advanced Slackbot with n8n

  by Mutasem · web · 9,377 clicks

  Use case Slackbots are super powerful. At n8n, we have been using them to get a lot done.. But it can become hard to manage and maintain many different operations that a workflow can do. This is the base workflow we use for our most powerful internal Slackbots. They handle a lot from running e2e tests for Github branch to deleting a user. By splitting the workflow into many subworkflows, we are able to handle each command seperately, making it easier to debug as well as support new usecases. In this template, you can find eveything to setup your own Slackbot (and I made it simple, there's only one node to configure 😉). After that, you need to build your commands directly. This bot can create a new thread on an alerts channel and respond there. Or reply directly to the user. It responds for help request to return a help page. It automatically handles unknown commands. It also supports flags and environment variables. For example /cloudbot-test info mutasem --full-info -e env=prod would give you the following info, when calling subworkflow. How to setup Add Slack command and point it up to the webhook. For example. Add the following to the Set config node alerts_channel with alerts channel to start threads on instance_url with this instance url to make it easy to debug slack_token with slack bot token to validate request slack_secret_signature with slack secret signature to validate request help_docs_url with help url to help users understand the commands Build other workflows to call and add them to commands in Set Config. Each command must be mapped to a workflow id with an Execute Workflow Trigger node Activate workflow 🚀 How to adjust Add your own commands. Depending on your need, you might need to lock down who can call this. An n8n automation workflow template by Mutasem.

  • 4 nodes
  • 9,377 views

  Workflow detailsImport from n8n.ioAutomation

• Automate Your RFP Process with OpenAI Assistants

  by Jimleuk · web · 8,946 clicks

  This n8n workflow demonstrates how to automate oftern time-consuming form filling tasks in the early stages of the tendering process; the Request for Proposal document or "RFP". It does this by utilising a company's knowledgebase to generating question-and-answer pairs using Large Language Models. How it works A buyer's RFP is submitted to the workflow as a digital document that can be parsed. Our first AI agent scans and extracts all questions from the document into list form. The supplier sets up an OpenAI assistant prior loaded with company brand, marketing and technical documents. The workflow loops through each of the buyer's questions and poses these to the OpenAI assistant. The assistant's answers are captured until all questions are satisified and are then exported into a new document for review. A sales team member is then able to use this document to respond quickly to the RFP before their competitors. Example Webhook Request curl --location 'https://<n8n_webhook_url>' \ --form 'id="RFP001"' \ --form 'title="BlueChip Travel and StarBus Web Services"' \ --form 'reply_to="jim@example.com"' \ --form 'data=@"k9pnbALxX/RFP Questionnaire.pdf"' Requirements An OpenAI account to use AI services. Customising the workflow OpenAI assistants is only one approach to hosting a company knowledgebase for AI to use. Exploring different solutions such as building your own RAG-powered database can sometimes yield better results in terms of control of how the data is managed and cost. An n8n automation workflow template by Jimleuk.

  • 7 nodes
  • 8,946 views

  Workflow detailsImport from n8n.ioAutomation, AI

• Ask a human for help when the AI doesn't know the answer

  by Deborah · web · 8,850 clicks

  This is a workflow that tries to answer user queries using the standard GPT-4 model. If it can't answer, it sends a message to Slack to ask for human help. It prompts the user to supply an email address. This workflow is used in Advanced AI examples | Ask a human in the documentation. To use this workflow: Load it into your n8n instance. Add your credentials as prompted by the notes. Configure the Slack node to use your Slack details, or swap out Slack for a different service. An n8n automation workflow template by Deborah.

  • 6 nodes
  • 8,850 views

  Workflow detailsImport from n8n.ioAutomation, AI

• ETL pipeline for text processing

  by Lorena · web · 8,734 clicks

  This workflow allows you to collect tweets, store them in MongoDB, analyse their sentiment, insert them into a Postgres database, and post positive tweets in a Slack channel. Cron node: Schedule the workflow to run every day Twitter node: Collect tweets MongoDB node: Insert the collected tweets in MongoDB Google Cloud Natural Language node: Analyse the sentiment of the collected tweets Set node: Extract the sentiment score and magnitude Postgres node: Insert the tweets and their sentiment score and magnitude in a Posgres database IF node: Filter tweets with positive and negative sentiment scores Slack node: Post tweets with a positive sentiment score in a Slack channel NoOp node: Ignore tweets with a negative sentiment score. An n8n automation workflow template by Lorena.

  • 5 nodes
  • 8,734 views

  Workflow detailsImport from n8n.ioAutomation

• Creating a AI Slack Bot with Google Gemini

  by Zacharia Kimotho · web · 8,663 clicks

  This is an example of how we can build a slack bot in a few easy steps Before you can start, you need to o a few things Create a copy of this workflow Create a slack bot Create a slash command on slack and paste the webhook url to the slack command Note Make sure to configure this webhook using a https:// wrapper and don't use the default http://localhost:5678 as that will not be recognized by your slack webhook. Once the data has been sent to your webhook, the next step will be passing it via an AI Agent to process data based on the queries we pass to our agent. To have some sort of a memory, be sure to set the slack token to the memory node. This way you can refer to other chats from the history. The final message is relayed back to slack as a new message. Since we can not wait longer than 3000 ms for slack response, we will create a new message with reference to the input we passed. We can advance this using the tools or data sources for it to be more custom tailored for your company. Usage To use the slackbot, go to slack and click on your set slash command eg /Bob and send your desired message. This will send the message to your endpoint and get return the processed results as the message. If you would like help setting this up, feel free to reach out to zacharia@effibotics.com. An n8n automation workflow template by Zacharia Kimotho.

  • 4 nodes
  • 8,663 views

  Workflow detailsImport from n8n.ioAutomation, AI

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