Workflow Templates

Acts as a virtual receptionist for the restaurant, handling incoming calls via VAPI without human intervention. It collects user details (name, booking time, number of people) for table bookings, checks availability in a PostgreSQL database using n8n, books the table if available, and sends confirmation. It also provides restaurant details to users, mimicking a human receptionist. Key Insights VAPI must be configured to accurately capture user input for bookings and inquiries. PostgreSQL database requires a table to manage restaurant bookings and availability. Workflow Process Initiate the workflow with a VAPI call to collect user details (name, time, number of people). Use n8n to query the PostgreSQL database for table availability. If a table is available, book it using n8n and update the PostgreSQL database. Send a booking confirmation and hotel service details back to VAPI via n8n. Store and update restaurant table data in the PostgreSQL database using n8n. Usage Guide Import the workflow into n8n and configure VAPI and PostgreSQL credentials. Test with a sample VAPI call to ensure proper data collection and booking confirmation. Prerequisites VAPI API credentials for call handling PostgreSQL database with booking and availability tables Customization Options Modify the VAPI input fields to capture additional user details or adjust the PostgreSQL query for specific availability criteria.

What if your quote requests managed themselves? Every quote request is a potential deal — but only if it's handled quickly, properly, and without things falling through the cracks. What if instead of copy-pasting emails and pinging teammates manually, your entire process just... ran itself? This automation makes it happen: it captures form submissions, notifies your sales team on Slack, stores leads in Airtable, and sends an email confirmation to the client — all in one seamless n8n flow. ⚙️ Tools used Tally** – to collect client quote requests n8n** – to automate everything, no code needed Airtable** – to store leads and track status Slack** – to instantly notify your sales team Gmail** – to confirm the request with the client 🧩 Flow structure overview Trigger from a Tally form using a webhook Extract and format the data Create a new record in Airtable Send a message to Slack Wait 5 minutes Send an email confirmation via Gmail 📥 Step 1 – Webhook (Tally) This node listens for incoming quote requests from the Tally form. HTTP Method:** POST Path:** /Request a Quote Authentication:** None Respond:** Immediately The data arrives as an array inside body.data.fields. Each field has a label and a value that we’ll need to map manually. 🧹 Step 2 – Edit Fields (Set) This step extracts usable values from the raw form data. Example mapping: Name = {{ $json.body.data.fields[0].label }} Email Address = {{ $json.body.data.fields[1].value }} Type of Service Needed = {{ $json.body.data.fields[2].value }} Estimated Budget = {{ $json.body.data.fields[3].value }} Preferred Timeline = {{ $json.body.data.fields[4].value }} Additional Details or Questions = {{ $json.body.data.fields[5].value }} 📊 Step 3 – Create record in Airtable We send the cleaned fields into a database (CRM) in Airtable. Operation:** Create Base & Table:** Request a Quote - Airtable Base Mapping:** Manual field-to-column matching Each quote submission becomes a new record with all project details. 📣 Step 4 – Send a message to Slack This node notifies your sales team immediately in a Slack channel. Message format: :new: New quote request received! 👤 Name: {{ $json.fields.Name }} 📧 Email: {{ $json.fields.Email }} 💼 Service: {{ $json.fields["Type of Service"] }} 💰 Budget: {{ $json.fields["Estimated Budget (€)"] }} ⏱️ Timeline: {{ $json.fields["Preferred Timeline"] }} 📝 Notes: {{ $json.fields["Additional Details"] }} ⏳ Step 5 – Wait 5 minutes This node simply delays the email by 5 minutes. Why? To give a human salesperson time to reach out manually before the automated confirmation goes out. It adds a personal buffer. 📧 Step 6 – Send confirmation via Gmail To:** {{ \$('Edit Fields').item.json\["Email Address"] }} Subject:** Thanks for your quote request 🙌 Email Type:** HTML Message body: Hi {{ $('Edit Fields').item.json.Name }}, Thanks a lot for your quote request — we’ve received your information! Our team will get back to you within the next 24 hours to discuss your project. Talk soon, — The WebExperts Team ✅ Final result With this automation in place: The client feels acknowledged and taken seriously Your team gets notified in real time You store everything in a clean, structured database All this without writing a single line of backend code. It’s fast, scalable, and business-ready.

📌 Workflow Description This workflow allows users to generate AI images directly from Telegram while automatically logging each request to Google Sheets for tracking. When a user sends a prompt to your Telegram bot, the workflow receives the prompt, generates an image using OpenAI, saves the prompt and generated image link to Google Sheets, and then sends the image back to the user in Telegram. ⚙️ How to Set It Up Connect your Telegram credentials by adding your bot token in both the Telegram Trigger and Telegram Send Message nodes. Ensure your bot is added to the intended chat. Connect your OpenAI credentials by inserting your API key in the OpenAI node and configuring it for image generation. Connect your Google Sheets account by authorising the Google Sheets node and selecting the target spreadsheet and worksheet where you want to save prompts and image links. Finally, activate the workflow and test by sending a prompt to your Telegram bot to confirm that the image is generated, saved to Google Sheets, and sent back to Telegram seamlessly. That’s it – your AI Image Generator with Google Sheets logging is ready to use. ⸻ ✅ That’s it – your AI Image Generator with Google Sheets logging is ready for use.

Who this template is for This template is for developers, content creators, or application builders who want to integrate an AI-powered text-to-image generation service into their applications or systems via an API endpoint. Use case Creating a secure API endpoint that converts text prompts into AI-generated images, with built-in content moderation to prevent inappropriate content generation. This can be used for creative applications, content creation tools, prototyping interfaces, or any system that needs on-demand image generation. How this workflow works Receives text prompt through a webhook endpoint Filters the prompt for inappropriate content using AI moderation Submits valid prompts to the Fal.ai Flux image generation service Polls for completion status and retrieves the generated image when ready Returns the image results in a structured JSON format to the client Set up steps Create a Fal.ai account and obtain API credentials Configure the HTTP Header Auth credentials with your Fal.ai API key Set up an OpenAI API key for the content moderation component Deploy the workflow and note the webhook URL for your API endpoint Test the endpoint by sending a POST request with a JSON body containing a "prompt" field

This workflow compares 2 datasets from a single database. Two SQL nodes create a slightly different summary report based on the payments table. Both reports have the same structure, but different time periods. In addition to that, output from the "Orders from 2004 and 2005" node has an extra manipulation on the ordercount variable. This makes Compare Datasets node to produce four outputs: data in A Only Branch, in B Only Branch, Same Branch records and Different Branch records. Please refere to the MySQL Tutorial website and download the example database: https://www.mysqltutorial.org/mysql-sample-database.aspx

🧾 Summary This workflow monitors Kubernetes pod CPU usage using Prometheus, and sends real-time Slack alerts when CPU consumption crosses a threshold (e.g., 0.8 cores). It groups pods by application name to reduce noise and improve clarity, making it ideal for observability across multi-pod deployments like Argo CD, Loki, Promtail, applications etc. 👥 Who’s it for Designed for DevOps and SRE teams and platform teams, this workflow is 100% no-code, plug-and-play, and can be easily extended to support memory, disk, or network spikes. It eliminates the need for Alertmanager by routing critical alerts directly into Slack using native n8n nodes. ⚙️ What it does This n8n workflow polls Prometheus every 5 minutes ⏱️, checks if any pod's CPU usage crosses a defined threshold (e.g., 0.8 cores) 🚨, groups them by app 🧩, and sends structured alerts to a Slack channel 💬. 🛠️ How to set up 🔗 Set your Prometheus URL with required metrics (container_cpu_usage_seconds_total, kube_pod_container_resource_limits) 🔐 Add your Slack bot token with chat:write scope 🧩 Import the workflow, customize: Threshold (e.g., 0.8 cores) Slack channel Cron schedule 📋 Requirements A working Prometheus stack with kube-state-metrics Slack bot credentials n8n instance (self-hosted or cloud) 🧑‍💻 How to customize 🧠 Adjust threshold values or query interval 📈 Add memory/disk/network usage metrics 💡 This is a plug-and-play Kubernetes alerting template for real-time observability. 🏷️ Tags: Prometheus, Slack, Kubernetes, Alert, n8n, DevOps, Observability, CPU Spike, Monitoring Prometheus Spike Alert to Slack

This N8N template makes it easy to extract key YouTube video data - including title, view count, like count, comment count, and many more - and save it directly into a connected Google Sheet. Use cases are many: Whether you're YouTubers, content strategists, growth marketers, and automation engineers, this tool gives you fast, structured access to video-level insights in seconds. How It Works The workflow begins when you click Execute Workflow or Test Workflow manually in N8N. It reads the list of video URLs in the connected Google Sheet. Only the URLs marked with the Ready status will be processed. The tool loops through each video and prepares the necessary data for the YouTube API call later. For each available URL, the tool extracts the video ID and sends a request to the YouTube API to fetch key metrics. The response is checked: If successful: the video’s statistics are written back to the corresponding row in the Google Sheet and the row's status is marked as Finished. If unsuccessful: the row's status is updated to Error for later review. How To Use Download the workflow package. Import the workflow package into your N8N interface. Duplicate the YouTube - Get Video Statistics Google Sheet template into your Google Sheets account. Set up Google Cloud Console credentials in the following nodes in N8N, ensuring enabled access and suitable rights to Google Sheets and YouTube services: For Google Sheets access, ensure each node is properly connected to the correct tab in your connected Google Sheet template: Node Google Sheets - Get Video URLs → connected to Tab Video URLs; Node Google Sheets - Update Data → connected to Tab Video URLs; Node Google Sheets - Update Data - Error → connected to Tab Video URLs. For YouTube access, set up a GET method to connect to YouTube API in the following node: Node HTTP - Find Video Data. In your connected Google Sheet, enter the video URLs that you want to crawl and set the rows' status to Ready. Run the workflow by clicking Execute Workflow or Test Workflow in N8N. View the results in your connected Google Sheet: Successful fetches will update the rows' status in Column A in the Video URLs tab to Finished and the video metrics will populate. If the call fails, the rows' status in Column A in the tab will be marked as Error. Requirements Basic setup in Google Cloud Console (OAuth or API Key method enabled) with enabled access to YouTube and Google Sheets. How To Customize By default, the workflow is manually triggered in N8N. However, you can automate the process by adding a Google Sheets trigger that monitors new entries automatically. If you want to fetch additional video fields or analytics (like tags, category ID, etc.), you can expand the HTTP - Find Video Data node to include those. Need Help? Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle

Automatically Send Square Summary Report for Yesterday's Sales via Microsoft Outlook What It Does This workflow automatically connects to the Square API and generates a daily sales summary report for all your Square locations. The report matches the figures displayed in Square Dashboard > Reports > Sales Summary. It's designed to run daily and pull the previous day's sales into a CSV file, which is then sent to a manager/finance team for analysis. This workflow builds on my previous template, which allows users to automatically pull data from the Square API into n8n for processing. (See here: https://n8n.io/workflows/6358) Prerequisites To use this workflow, you'll need: A Square API credential (configured as a Header Auth credential) A Microsoft Outlook credential How to Set Up Square Credentials: Go to Credentials > Create New Choose Header Auth Set the Name to Authorization Set the Value to your Square Access Token (e.g., Bearer <your-api-key>) How It Works Trigger: The workflow runs every day at 4:00 AM Fetch Locations: An HTTP request retrieves all Square locations linked to your account Fetch Orders: For each location, an HTTP request pulls completed orders for the specified report_date Filter Empty Locations: Locations with no sales are ignored Aggregate Sales Data: A Code node processes the order data and produces a summary identical to Square’s built-in Sales Summary report Create CSV File: A CSV file is created containing the relevant data Send Email: An email is sent to the chosen third party Example Use Cases Automatically send Square sales data to management to improve the quality of planning and scheduling decisions Automatically send data to an external third party, such as a landlord or agent, who is paid via commission Automatically send data to a bookkeeper for entry into QuickBooks How to Use Configure both HTTP Request nodes to use your Square API credential Set the workflow to Active so it runs automatically Enter the email address of the person you want to send the report to and update the message body If you want to remove the n8n attribution, you can do so in the last node Customization Options Add pagination to handle locations with more than 1,000 orders per day Instead of a daily summary, you can modify this workflow to produce a weekly summary once a week Why It's Useful This workflow saves time, reduces manual report pulling from Square, and enables smarter automation around sales data — whether for operations, finance, or performance monitoring.

What does the workflow do? This workflow is primarily designed to generate animated illustrations for content creators and social media professionals with Midjourney (unoffcial) and Kling (unofficial) API served by PiAPI. PiAPI is an API platform which provides professional API service. With service provided by PiAPI, users could generate a fantastic animated artwork simply using workflow on n8n without complex settings among various AI models. What is animated illustration? An animated illustration is a digitally enhanced artwork that combines traditional illustration styles with subtle, purposeful motion to enrich storytelling while preserving its original artistic essence. Who is this workflow for? Social Media Content Creators: Produces animated illustrations for social media posts. Digital Marketers: Generates marketing materials with motion graphics. Independent Content Producers: Creates animated content without specialized animation skills. Step-by-step Setting Instructions To simplify workflow settings, usually users just need to change basic prompt of the image and the motion of the final video following the instrution below: Sign in your PiAPI account and get your X-API-Key. Fill in your X-API-Key of PiAPI account in Midjourney and Kling nodes. Enter your desired image prompt in the Prompt node. Enter the motion prompt in Kling Video Generator node. For more complex or customization settings, users could also add more nodes to get more output images and generate more videos. Also, they could change the target image to gain a better result. As for recommendation, users could change the video models for which we would recommend live-wallpaper LoRA of Wanx. Users could check API doc to see more use cases of video models and image models for best practice. Use Case Input Prompt A gentle girl and a fluffy rabbit explore a sunlit forest together, playing by a sparkling stream. Butterflies flutter around them as golden sunlight filters through green leaves. Warm and peaceful atmosphere, 4K nature documentary style. --s 500 --sref 4028286908 --niji 6 Output Video When there is troubleshooting Check if the X-API-Key has been filled in nodes needed. Check your task status in Task History in PiAPI to get more details about task status. More Generation Case for Reference

F Description This workflow automatically searches Airbnb for the best deals in your target locations and saves them for later reference. It helps travelers find affordable accommodations by continuously monitoring listings and identifying properties that match your budget and preferences. Overview This workflow automatically searches Airbnb for the best deals in your target locations and saves them for later reference. It uses Bright Data to scrape Airbnb listings and can filter results based on your preferences for price, amenities, and ratings. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping Airbnb listings without being blocked. Spreadsheets/Databases:** For storing and comparing property deals. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Data Storage: Configure where you want to store the Airbnb deals. Customize: Specify locations, date ranges, and your budget constraints. Use Cases Travelers:** Find the best accommodation deals for your trips. Digital Nomads:** Track affordable long-term stays in different locations. Property Managers:** Monitor competitor pricing in your area. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #airbnb #travel #brightdata #dealhunting #vacationrentals #traveldeals #accommodationdeals #airbnbdeals #n8nworkflow #workflow #nocode #travelhacks #budgettravel #propertydeals #travelplanning #airbnbscraper #vacationplanning #bestairbnbs #travelautomation #affordableaccommodation #staydeals #traveltech #digitalnomad #accommodationfinder

What It Does This workflow automatically runs when a new email is received in the user's Gmail account. It sends the email content to OpenAI (GPT-4.1-mini), which intelligently determines whether the message requires action. If the email is identified as actionable, the workflow sends a structured alert message to the user in Microsoft Teams. This keeps the user informed of high-priority emails in real time without the need to manually check every message. The workflow does not log any execution data, ensuring that email content remains secure and unreadable by others. How It Works Trigger on New Email**: The workflow is triggered automatically when a new email is received in the user's Gmail account.  Email Evaluation with OpenAI**: The email content is sent to GPT-4.1-MINI, which evaluates whether the message requires user action.  Filter Actionable Emails**: Only emails identified as actionable by the AI are allowed to proceed through the rest of the workflow.  Send Notification to Teams**: For actionable emails, the workflow sends a structured alert message to the user in Microsoft Teams chat via a Power Automate webhook. Prerequisites Gmail IMAP Credentials  OpenAI API Key  Microsoft Teams Webhook URL  Power Automate Flow to send message to Teams chat  How to Set It Up 1. Set Up Power Automate Workflow 1.1 Open Workflow Power Automate in Microsoft Teams Open the Workflow app from Microsoft Teams.  If it's not already added, go to Apps → search "Workflow" → click Add → open it. 1.2 Create a New Flow Click New Flow → select Create from blank. 1.3 Add a Trigger: When a Teams webhook request is received In the trigger setup, set Who can trigger the flow? to Anyone.  After saving the flow, a webhook URL will be generated — this URL will be used in n8n workflow. 1.4 Add Action: Parse JSON Set Content to: Body  Use the following schema: { "type": "object", "properties": {    "from": {      "type": "string"    },    "receivedAt": {      "type": "string"    },    "subject": {      "type": "string"    },    "message": {      "type": "string"    } } } 1.5 Add Action: Get an @mention token for a user Set the User field to the Microsoft Teams email address of the person to notify (e.g. yourname@domain.com). 1.6 Add Action: Post message in a chat or channel In this action, configure the following: Post as: Flow bot  Post in: Chat with Flow bot  Recipient: Your Microsoft Teams email address (e.g., yourname@domain.com) Paste the following code into the Message (in code view): Hello @{outputs('Get_an_@mention_token_for_a_user')?['body/atMention']}, You have received a new email at your email address @{body('Parse_JSON')?['recipientEmail']} that requires your attention: From: @{body('Parse_JSON')?['sender']} Received On: @{body('Parse_JSON')?['date']} Subject:  @{body('Parse_JSON')?['subject']} Please review the message at your earliest convenience. Click here to search this mail in your mailbox 1.7 Save and Enable the Flow Click Save. Turn the flow On. The webhook URL is now active and available in the first trigger step, copy it to use in n8n. Need help with the setup? Feel free to contact us 2. Configure IMAP Email Trigger First, enable 2‑Step Verification in your Google Account and generate an App Password for n8n. Then, in the IMAP node → Create Credential to connect using the following details:  • User: your Gmail address  • Password: the App Password  • Host: imap.gmail.com  • Port: 993  • SSL/TLS: Enabled Follow the n8n documentation to complete the setup. 3. Configure OpenAI Integration Add your OpenAI API key as a credential in n8n. Follow the n8n documentation to complete the setup. 4. Set Up HTTP Request to Trigger Power Automate Workflow Paste generated Webhook URL from the Power Automate workflow into the URL field of the HTTP Request node. 5. Disable Execution Logging for Privacy To ensure that email content is not stored in logs and remains fully secure, you can disable execution logging in n8n: In the n8n Workflow Editor, click on the three dots (•••) in the top right corner and select Settings. In the settings panel: Set Save manual executions to: Do not save Set Save successful production executions to: Do not save Set Save failed production executions to: Do not save if you also want to avoid logging errors Save the changes. Refer to the official n8n documentation for more details: 6. Activate the Workflow Set the workflow status to Active in n8n so it runs automatically when a new mail is received in Gmail. Need Help? Contact us for support and custom workflow development.

Water Reminder Workflow This workflow demonstrates how to use n8n and Slack to build an intelligent water drinking reminder system, combined with Google Sheets for data recording and OpenAI for generating personalized reminder messages. Google Sheet Template The iOS shortcut template: The result in iOS health: The template demo in Youtube Key Features Scheduled Reminders: Automatically sends water reminders at random times every hour. Intelligent Scheduling: Delays the next reminder if you've recently had water. AI-Generated Messages: Uses OpenAI to generate friendly and non-repetitive reminder messages. Data Tracking: Records daily water intake and calculates percentage of goal achievement. Quick Response: Easily record water intake through Slack buttons. iOS Integration: Provides iOS shortcut links to sync data with the Health app. Pre-Configuration Requirements To use this workflow, you need to set up the following: Google Sheets: Create a Google spreadsheet with log and setting sheets The log sheet should include date, time, and value columns The setting sheet is used to store daily water intake goals Slack: Create a Slack app and obtain an API token Configure permissions for interactive buttons OpenAI: Obtain an OpenAI API key iOS Shortcut (optional): Create an iOS shortcut named darrell_water for recording health data Node Configurations 1. Scheduled Triggers and Data Collection 1.1. Schedule Trigger Purpose**: Triggers water reminders on schedule Configuration**: Cron Expression: 0 {{ Math.floor(Math.random() * 11) }} 8-23 * * * Triggers at a random minute every hour, only between 8 AM and 11 PM 1.2. Google Sheets - Get Target Purpose**: Retrieves daily water intake goal Configuration**: Document ID: Your Google spreadsheet ID Sheet Name: setting 1.3. Google Sheets - Get Log Purpose**: Retrieves today's water intake records Configuration**: Document ID: Your Google spreadsheet ID Sheet Name: log Filter Condition: date equals today's date {{ $now.format('yyyy-MM-dd') }} 1.4. Summarize Purpose**: Calculates total water intake for today Configuration**: Fields to Summarize: value (sum) 1.5. Limit Purpose**: Gets the most recent water intake record Configuration**: Keep: Last items 2. Intelligent Reminder Logic 2.1. Combine Data Purpose**: Merges target and actual water intake data Configuration**: Combine By: Combine by position Number of Inputs: 3 2.2. If Purpose**: Checks if water was consumed recently Configuration**: Condition: {{ DateTime.fromISO($json.date+"T"+$json.time).format('yyyy-MM-dd HH:mm:ss') }} is after {{ $now.minus(30, "minutes") }} 2.3. Wait Purpose**: Randomly delays the reminder if water was consumed recently Configuration**: Wait Time: {{ Math.floor(Math.random() * 1) + 1 }} minutes 3. AI Message Generation and Sending 3.1. OpenAI Purpose**: Generates personalized water reminder messages Configuration**: Model: gpt-4o-mini Messages: System prompt: Requests responses in Traditional Chinese and in JSON format User prompt: Includes information about last water time, current time, goal, and progress Temperature: 1 3.2. Slack Send Drink Notification Purpose**: Sends water reminders to Slack channel Configuration**: Channel: Your Slack channel ID Message Type: Block Block UI: Contains AI-generated reminder message and water amount buttons (100ml, 150ml, 200ml, 250ml, 300ml) 4. User Interaction and Data Recording 4.1. Slack Drink Webhook Purpose**: Receives user interactions when water buttons are clicked Configuration**: HTTP Method: POST Path: slack-water-webhook 4.2. Slack Action Payload Purpose**: Parses Slack interaction data Configuration**: Mode: Raw JSON Output: {{ $json.body.payload }} 4.3. Slack Action Drink Data Purpose**: Extracts water amount and message information Configuration**: Assignments: value: {{ $json.actions[0].value }} message_text: {{ $json.message.text }} shortcut_url: shortcuts://run-shortcut?name=darrell_water&input= shortcut_url_data: JSON containing water amount and time message_ts: {{ $json.container.message_ts }} 4.4. Google Sheets Purpose**: Records water intake data to spreadsheet Configuration**: Operation: Append Document ID: Your Google spreadsheet ID Sheet Name: log Column Mapping: date: {{ $now.format('yyyy-MM-dd') }} time: {{ $now.format('HH:mm:ss') }} value: {{ $json.value }} 4.5. Send to Slack with Confirm Purpose**: Sends confirmation message and provides iOS shortcut link Configuration**: Channel: Your Slack channel ID Message Type: Block Block UI: Contains confirmation message and iOS Health app button Reply Settings: Reply to the thread of the original message Author Information This workflow was created by darrell_tw_, an engineer focused on AI and Automation. Contact: X Threads Instagram Website