Workflow Templates

Who is this for? This workflow is ideal for businesses, accountants, and finance teams who receive bank slip images via LINE and want to automate the extraction of transaction details. It eliminates manual data entry and speeds up financial tracking. What problem does this workflow solve? Many businesses receive bank transfer slips via LINE from customers, but manually recording transaction details into spreadsheets is time-consuming and error-prone. This workflow automates the entire process, extracting structured data from the bank slips and storing it in Google Sheets for seamless record-keeping. What this workflow does: Receives bank slip images from LINE BOT Extracts transaction details (sender, receiver, amount, transaction ID) using SpaceOCR Automatically logs extracted data into Google Sheets Works with Standard Bank Slips & PromptPay transactions Eliminates manual data entry and reduces errors Setup Instructions: 1. Prerequisites A LINE BOT with Messaging API enabled A SpaceOCR API Key (Get from https://spaceocr.com/) A Google Sheets account to store extracted data An n8n instance running (Cloud or Self-hosted) 2. Setup Google Sheets Create a Google Sheet with the following structure: A (Date) B (Time) C (Sender) D (Receiver) E (Bank Name) F (Amount) G (Transaction ID) Ensure your Google Sheets API is enabled and connected to n8n. For an example of the required format, check this Google Sheets template: Google Sheets Template 3. Configure n8n Workflow 1. Webhook Node (Receives bank slip from LINE BOT) Set method:* Set Path:* 2. HTTP Request (Download Image from LINE Message) Retrieves image URL from the LINE message payload 3. SpaceOCR Node (Extract Text from Bank Slip) Input:* API Key:* #### 4. Google Sheets Node (Save Transaction Data) Select your Google Sheet Map extracted data (sender, receiver, amount, etc.) to the respective columns 4. Deploy & Test Activate the workflow in n8n Set Webhook URL in LINE Developer Console Send a test bank slip image to the LINE BOT Check Google Sheets for extracted transaction data

Generate and Publish AI Content to LinkedIn and X (Twitter) with n8n Overview This n8n workflow automates the generation and publishing of AI-powered social media content across LinkedIn and X (formerly Twitter). By leveraging AI, this workflow helps social media managers, marketers, and content creators streamline their posting process. Who is this for? Social media managers Content creators Digital marketers Businesses looking to automate content generation Features AI-powered content creation** tailored for LinkedIn and X (Twitter) Automated publishing** to both platforms Structured output parsing** to ensure consistency OAuth2 authentication** for secure posting Merge and confirmation steps** to track successful postings Setup Instructions Prerequisites Before using this workflow, ensure you have: An n8n instance set up API credentials for: Google Gemini AI (for content generation) X Developer Account with OAuth2 authentication LinkedIn Developer Account with OAuth2 authentication A form submission service integrated with n8n Workflow Breakdown 1. Trigger: Form Submission A user submits a form containing the post title. The form is secured with Basic Authentication. The submitted title is passed to the AI Agent. 2. AI Content Generation The Google Gemini Chat Model processes the title and generates: LinkedIn post content Twitter (X) post content Hashtags Call-to-action (LinkedIn) Character limit check (Twitter) 3. Parsing AI Output A structured output parser converts the AI-generated content into a JSON format. Ensures correct formatting for LinkedIn and Twitter (X). 4. Publishing to Social Media X (Twitter) Posting Extracts the Twitter post from the AI output. Publishes it via an OAuth2-authenticated X (Twitter) account. LinkedIn Posting Extracts the LinkedIn post from the AI output. Publishes it via an OAuth2-authenticated LinkedIn account. 5. Merging Post Results Merges the response data from both LinkedIn and Twitter after publishing. 6. Confirmation Step Displays a final confirmation form once the posts are successfully published. Benefits Save time** by automating content creation and publishing. Ensure consistency** across platforms with structured AI-generated posts. Secure authentication** using OAuth2 for LinkedIn and Twitter. Increase engagement** with AI-optimized hashtags and CTAs. This workflow enables seamless social media automation, helping professionals post engaging AI-powered content effortlessly. 🚀

Built this for a dedicated Slack outage-notifications channel — works well on both desktop and mobile. This is for: IT Administrators & small MSPs looking to streamline M365 alerts from one or multiple mailboxes into a single or specific Slack channels IT Admins who prefer ChatOps over management-by-email What does it do Scans for M365 outage alerts emails (every 1 min) Checks if it impacts a specific user region (if the alert calls it out, countries have to be manually set) Summarizes the incident using OpenAI o4-mini (cheap model - or you can swap for local Ollama) Sends a Slack Block to your outage channel with incident link (can be extended) Deletes the original alert email after successful delivery Credentials Outlook: Create an Outlook credential (OAuth2.0) to point to the mailbox (regular or shared) where M365 service alerts will be received Slack: Create a Slack bot credential with access to the slack channel you want updates posted to OpenAI: Create a OpenAI credential that has access to the GPT-4O-MINI model. Recommend you use projects in OpenAI so that you may set a per-project-budget and not impact other projects. Review this OpenAI documentation for more info on managing Projects in the API portal. Expect this to consume no more than 1-2 cents per month on average. Setup Download & import the workflow Modify the first Outlook block (Check for 365 Service Alert) to use the Outlook credential Modify the OpenAI block's system prompt to call out the countries your users reside in ie. "- Assume the organization has users primarily in the U.S. and Australia. If those regions are affected, state: "Your users may have been affected." Otherwise, add: "No impact expected for your user base."" ← swap U.S. & Australia for desired countries Modify the Slack block (Post outage to Slack) to specify the channel updates will be posted to Sample Slack Output Workflow Diagram

Who is this template for? Anyone who is drowning in emails Busy parents who has alot of school emails Busy executives with too many emails Case Study I get too many emails from my kid's school about soccer practice, lunch orders and parent events. I use this workflow to read all the emails and tell me what is important and what requires actioning. Read more -> How I used A.I. to read all my emails What this workflow does It uses IMAP to read the emails from your email account (i.e. Gmail). It then passes the email to Openrouter.ai and uses a free A.I. model to read and summarize the email. It then sends the summary as a message to your messenger (i.e. Line). Setup You need to find your email server IMAP credentials. Input your openrouter.ai API credentials or replace the HTTP request node with an A.I. node such as OpenAI. Input your messenger credentials. I use Line but you can change the node to another messenger line Telegram. You need to change the message ID to your ID inside the http request. You can find your user ID inside the https://developers.line.biz/console/. Change the "to": {insert your user ID}. How to adjust it to your needs You can change the A.I. prompt to fit your needs by telling it to mark emails from a certain address as important. You can change the A.I. model from the current meta-llama/llama-3.1-70b-instruct:free to a paid model or other free models. You can change the messenger node to telegram or any other messenger app you like.

Use case This automation is for teams working in Notion. When you have a lot of back and forth in the comment section, it’s easy to lose track of what is going on in the conversation. This automation relies on AI to generate a summary of the comment section. How it works Every hour (the trigger can be adapted to your need and usecase), the automation checks if new comments have been added to the pages of your Notion database. If there are new comments, the comments are sent to an AI model to write a summary. The summary is then added to a predefined page property. The automation also updates a “Last execution” property. This prevents to re-generate the AI summary when no new comments have been received. Setup Define your Notion variables: Notion database, property that will hold the AI summary, property that will hold the last execution date of the automation. Set up your Notion credentials. Set up your AI model credentials (API key). How to adjust it to your needs Use the LLM model of your choice. In this template, I used Gemini but you can easily replace it by ChatGPT, Claude, etc. Adapt the prompt to your use case to get better summaries: specify the maximum number of characters, give an example, etc. Adapt the trigger to your needs. You could use Notion webhooks as trigger in order to run the automation only when a new comment is added (this setup is advised if you’re on n8n cloud version).

Define Your ICP from Customer LinkedIn Profiles Use Case This automation helps marketing and sales teams define their Ideal Customer Profile (ICP) using real LinkedIn profiles of current high-fit customers. By enriching and analyzing profile data, it generates a clear ICP definition and scoring methodology for future targeting. What This Automation Does This automation analyzes LinkedIn profiles of your existing customers and produces: A structured ICP definition A scoring model to evaluate future prospects A Google Boolean search string to find similar prospects Input: LinkedIn profile URLs of existing high-fit customers (e.g., https://www.linkedin.com/in/amirashkenazi/) Output: A Google Doc containing the ICP analysis and scoring methodology How It Works Trigger: Waits for a chat message containing one or more LinkedIn profile URLs. AI Agent: Parses and processes the URLs. Airtop Data Enrichment: Uses Airtop to extract structured information from each LinkedIn profile (e.g., job title, company, experience, skills). Memory: Maintains state between inputs for consistent analysis. LLM Analysis: Uses Claude 3.7 Sonnet to synthesize enriched data into a meaningful ICP. Google Docs: Automatically creates a new doc with a timestamped title and appends the ICP definition. Setup Requirements Airtop Profile connected to LinkedIn, Insert the profile name in the Airtop Tool Airtop API credentials. Get it free here If you choose to activate saving the profiles in Google Docs you will need OAuth2 credentials (or just copy the ICP definition from the chat) Next Steps Use the ICP for Scoring**: Feed new LinkedIn profiles through the same Airtop enrichment and use the scoring function to evaluate fit. Automate Target Discovery**: Plug the Boolean search output into LinkedIn, Google, or People Data Labs for ICP-matching lead generation. Refine Continuously**: Repeat the workflow as your customer base grows or segments evolve. Read more about how to Define ICP from Customer Examples

Who is this template for? This workflow template is designed for people seeking alerts when certain specific changes are made to any web page. Leveraging agentic AI, it analyzes the page every day and autonomously decides whether to send you an e-mail notification. Example use cases Track price changes on [competitor's website]. Notify me when the price drops below €50. Monitor new blog posts on [industry leader's website] and summarize key insights. Check [competitor's job page] for new job postings related to software development. Watch for new product launches on [e-commerce site] and send me a summary. Detect any changes in the terms and conditions of [specific website]. Track customer reviews for [specific product] on [review site] and extract key themes. How it works When clicking 'test workflow' in the editor, a new browser tab will open where you can fill in the details of your espionage assignment Make sure you be as concise as possible when instructing AI. Instruct specific and to the point (see examples at the bottom). After submission, the flow will start off by extracting both the relevant website url and an optimized prompt. OpenAI's structured outputs is utilized, followed by a code node to parse the results for further use. From here on, the endless loop of daily checks will begin: Initial scrape 1 day delay Second scrape AI agent decides whether or not to notify you Back to step 1 You can cancel an espionage assignment at any time in the executions tab Set up steps Insert your OpenAI API key in the structured outputs node (second one) Create a Firecrawl account and connect your Firecrawl API key in both 'Scrape page'-nodes Connect your OpenAI account in the AI agents' model node Connect your Gmail account in the AI agents' Gmail tool node

✉️ Telegram Email Agent with GPT + Gmail Category: Messaging / AI Agent Level: Beginner-Friendly Tags: Telegram, Email Automation, AI Agent, Gmail, GPT Model Watch Step-by-step video guide here: https://www.youtube.com/watch?v=nyI40s9QOuw&t=420s&pp=0gcJCb4JAYcqIYzv 🤖 What This Workflow Does This workflow turns your Telegram bot into a personal email assistant powered by AI. With just a message on Telegram, users can: Send an email via Gmail Automatically generate the email content using OpenAI Models. Get confirmation or responses directly in Telegram It's like ChatGPT meets Gmail, inside your Telegram chat. 🔧 How It Works Telegram Trigger – Listens for incoming messages from your bot. AI Agent – Processes the input using OpenAI Model and converts it into structured email content (To, Subject, Body). Memory Node – Stores short-term context per user (via chat ID), so the agent can hold simple conversations. Gmail Node – Sends the generated email using your Gmail account. Telegram Node – Replies to the user confirming the output or status. 🧠 Why This is Useful Ever wanted to send an email while on the go, without typing the whole thing out in Gmail? This is a fast, intuitive, and AI-powered way to: Dictate or draft emails from anywhere Create an AI-powered virtual assistant via Telegram Integrate n8n's Langchain Agent with real-world productivity use cases 🪜 Setup Instructions Connect your Telegram bot via BotFather and add the credentials in n8n. Set up your OpenAI API key (GPT-4o-mini recommended). Add your Gmail OAuth credentials. Activate the workflow and start messaging your bot!

Who is this for? This template is for any website owner, digital agency, or compliance officer operating within the European Union. It's designed for users who need to comply with the upcoming European Accessibility Act (EAA) but may not have deep technical or legal expertise. Disclaimer This workflow uses an npm package called "cheerio" to work with the specified URLs HTML code. Installing packages is only possible in self hosting. What problem is this workflow solving? / Use Case Starting June 28, 2025, the European Accessibility Act (EAA) mandates that most websites offering products or services in the EU must be accessible and publish a formal Accessibility Statement. Manually creating this legal document is complex, requiring both a technical site analysis and knowledge of specific legal requirements. This workflow automates the generation of a compliant first draft, saving significant time and effort. What this workflow does After you input your details (like website URL and API key) in a central configuration node, this workflow automatically: Scans your live website for accessibility issues using the powerful WAVE API. Processes the scan results to identify the main problem areas. Instructs a Google Gemini AI agent with a specialized legal prompt based on the European Accessibility Act. Generates a formal Accessibility Statement in your desired language. Saves the statement as an .html file and sends it to you as an email attachment. Setup This workflow is designed for a quick setup: Configure All Variables: Click the 'CHANGE THESE: dependencies' node. This is your central control panel. Fill in all the values, including your WAVE API Key, the URL to analyze, company details, and desired output language. Set Up Credentials: You will need to connect your Google accounts for the workflow to run. Gemini: Click the 'gemini 2.5 pro' node, click the gear icon (⚙️) next to the "Credential" field, and connect your Google Gemini API credentials. Gmail: Click the 'Send report by email' node and connect your Gmail account to allow sending the final report. Activate & Execute: Make sure the workflow is active in the top-right corner, then click 'Execute Workflow' to run your first analysis. How to customize this workflow to your needs This template is a great starting point for any EU country. Here's how to adapt it: Localize for Your Country (Important!):* The generated statement contains a placeholder for the "Enforcement Procedure". You *must* edit the prompt in the *'Accessibility Statement Generator'** node to replace this placeholder with the name and link to your specific country's official enforcement body. Change the AI:** Swap the Google Gemini node for any other AI model, like OpenAI or Anthropic Claude, by replacing the node and connecting it to the agent. Change the Trigger:* Replace the *'When clicking ‘Execute workflow’'** node with a Form Trigger or Webhook Trigger to run this workflow based on external inputs, for example, to offer this analysis as a service to your clients.

🧾 Generate Project Summary from meeting transcript Who’s it for 🤝 Project managers looking to automate client meeting summaries Client success teams needing structured deliverables from transcripts Agencies and consultants who want consistent, repeatable documentation How it works / What it does ⚙️ Trigger: Manual or webhook trigger kicks off the workflow. Get meeting transcript: Reads the raw transcript from a specified Google Docs file. Generate summary: Sends transcript + instructions to OpenAI (gpt-4.1-mini) to produce a structured project summary. Convert to HTML: Transforms the LLM-generated Markdown into styled HTML. Prepare request: Wraps HTML and metadata into a multipart request body. Create Google Doc: Uploads the new “Project Summary” document into your Drive folder. How to set up 🛠️ Credentials Google Docs & Drive OAuth2 credentials OpenAI API key (gpt-4.1-mini) Nodes configuration Manual Trigger / webhook node Google Docs “Get meeting transcript” node: set documentURL AI Chat Model node: select gpt-4.1-mini Markdown node: enable tables & emoji Google Drive “CreateGoogleDoc” node: set target folder ID Paste in your IDs Update documentURL to your transcript doc Update google_drive_folder_id in the Set node Execute Click “Execute Workflow” or call via webhook Requirements 📋 n8n Google OAuth2 scopes for Docs & Drive OpenAI account with GPT-4.1-mini access A Google Drive folder to store summaries How to customize ✨ Output format**: Edit the Markdown prompt in the ChainLlm node to adjust headings or tone Timeline section**: Extend LLM prompt template with your own phase table Styling**: Tweak inline CSS in the Code node (Prepare_Request) for fonts or margins Trigger**: Swap Manual Trigger for HTTP/Webhook trigger to integrate with other tools Language model**: Upgrade to a different model by changing model.value in the AI node

How it Works This workflow fetches top news headlines every 10 minutes from NewsAPI, summarizes them using OpenAI's GPT-4o model, and sends a concise email digest to a list of recipients defined in a Google Spreadsheet. It's ideal for anyone who wants to stay updated with the latest news in a short, digestible format. 🎯 Use Case Professionals who want summarized daily news Newsletters or internal communication updates Teams that require contextual summaries of the latest events Setup Instructions 1. Upload the Spreadsheet File name: Emails Column: Email with recipient addresses 2. Configure Google Sheets Nodes Connect your Google account to: Email List Send Email 3. Add API Credentials NewsAPI Key** → for fetching top headlines OpenAI API Key** → for summarizing headlines Gmail Account** → for sending the email digest 4. Activate the Workflow Once active, the workflow runs every 10 minutes via a cron trigger Summarized news is sent to the list of emails in the spreadsheet 🔁 Workflow Logic Trigger: Every 10 minutes via Cron Fetch News: HTTP request to NewsAPI for top headlines Summarize: Headlines are passed to OpenAI's GPT-4o for 5-bullet summary Read Recipients: Google Sheet is used to collect email recipients Send Email: Summary is formatted and sent via Gmail 🧩 Node Descriptions | Node Name | Description | |-----------|-------------| | Cron | Triggers the workflow every 10 minutes. | | HTTP Request - NewsAPI | Fetches top news headlines using NewsAPI. | | Set | Formats or structures raw news data before processing. | | AI Agent | Summarizes the news content using OpenAI into 5 bullet points. | | Email List | Reads recipient email addresses from the 'Emails' Google Spreadsheet. | | Send Email | Sends the email digest to all recipients using Gmail. | 🛠️ Customization Tips Modify the AI prompt for tone, length, or content type Send summaries to Slack, Telegram, or Notion instead of Gmail Adjust cron interval for more/less frequent updates Change email formatting (HTML vs plain text) 📎 Required Files | File Name | Purpose | |-----------|---------| | Emails spreadsheet | Google Sheet containing the list of email recipients | | daily_news.json | Main n8n workflow file to automate daily news digest | 🧪 Testing Tips Add 1–2 test email addresses in your spreadsheet Temporarily change the Cron node to run every minute for testing Check email inbox for delivery and formatting Inspect the execution logs for API errors or formatting issues 🏷 Suggested Tags & Categories #News #OpenAI #Automation #Email #Digest #Marketing

Daily Email Pulse Summary: This agent summarizes a user's daily emails into a clean, actionable summary. It uses OpenAI to analyze content and sends a formatted "Daily Pulse" email at the end of each day. Main use cases: Keep track of open loops and next steps across all email conversations Identify high-potential leads and flag conversations going nowhere Eliminate the need to manually review your inbox at day’s end Build a smart summary layer using AI without hallucination or noise How it works This workflow can be divided into eight core nodes, each serving a distinct purpose in helping a user stay on top of their day. The result is a curated, AI-generated summary delivered to your inbox — crafted from real message content, not guesswork. Schedule Trigger (Trigger Node – Runs Daily at Set Time) Kicks off the workflow at a specific time each day (e.g. 6:00 PM). Ensures you receive your Daily Pulse consistently, without needing to run it manually. Date Transformer (Function Node – Define Today & Tomorrow Range) Uses JavaScript to calculate the current day’s date range: today: Start of day (00:00:00) tomorrow: Start of next day (used as a cutoff) This ensures only emails from today are analyzed, keeping the summary focused and current. Get All Messages (Gmail Node – Fetch Filtered Emails) Pulls in all Gmail messages with internalDate between today and tomorrow. Outputs structured data: from, subject, and body text of each email. This forms the raw data for the daily business pulse. Aggregator (Function or Item Lists Node – Combine Message Fields) Aggregates each message into a readable format: From: John@example.com Subject: Demo Follow-up Body: Let’s schedule a time this week... All messages are stitched together into a single combinedText string for analysis. This gives the AI model full context for the day in one unified document. Email Cleanup (Function Node – Remove Noise & Normalize Text) Cleans the combinedText blob to remove: HTML tags Marketing footers (e.g., unsubscribe links) Redundant whitespace or formatting artifacts Ensures GPT gets clean, relevant message content with no distractions. Agent (OpenAI Node – Generate Structured Summary) Uses a System Prompt to define its role as an AI Chief of Staff. Uses a User Prompt that instructs it to categorize messages into sections: 📝 Open Loops / Pending Follow-Up 🚀 Next Steps You’ve Committed To 🧲 Leads Worth Following Up On 🛑 Conversations That Aren’t Leading Anywhere 🧠 Strategy Notes ✅ Top 3 Tasks for Tomorrow Built-in guardrails ensure the model only uses real content (no hallucination). Sections with no relevant data are omitted to keep it concise. HTML Formatter (Function Node – Wrap Markdown in Email-Ready HTML) Wraps the GPT-generated markdown summary in a simple <html><body> structure. Applies white-space: pre-wrap to preserve formatting and spacing. The result is a clean, readable email that renders well across all inboxes (especially Gmail). Email Send (Email Node – Deliver the Final Pulse) Sends the formatted summary to your email inbox. Subject: Your Daily Business Pulse – {{today}} HTML body: Uses the formatted output from the previous step. Final output: a well-organized, scannable summary of the day’s communication — focused on what matters. Why It Works Automates the end-of-day review ritual without effort Prioritizes follow-ups, action items, and time-sensitive leads Filters out noise and low-value conversations Leverages GPT without risk of hallucination or irrelevant output Delivers clarity, helping you focus on tomorrow’s most important tasks