Workflow Templates

This workflow facilitates seamless synchronization between Entra (Microsoft Azure AD) and Zammad. It automates the following processes: Fetch Entra Contacts: Create Universal User Object: Extracts key user information, such as email, phone, and name, and formats it for Zammad compatibility. Synchronize with Zammad: Identifies users in Zammad who need updates based on Entra data. Adds new users from Entra to Zammad. Deactivates users in Zammad if they are no longer in Entra. Key Features Dynamic Matching**: Compares contacts from Entra with existing Zammad users based on email and updates records accordingly. Efficient Management**: Automatically creates, updates, or deactivates Zammad users based on their status in Entra. Custom Fields**: Supports custom field mapping, ensuring enriched user profiles in Zammad. Setup Instructions Microsoft Entra Integration: Ensure proper API permissions for accessing Entra contacts. Configure Microsoft OAuth2 credentials in n8n. Zammad Integration: Set up Zammad API credentials with appropriate access rights. Customize the workflow to include additional fields or map existing fields as needed. Run Workflow: Trigger the workflow manually or set up an automation schedule (e.g., daily sync). Review created/updated/deactivated users in Zammad. Use Cases IT Administration**: Keep your support system in sync with the organization’s Entra data. Customer Management**: Ensure accurate and up-to-date user records in Zammad. Prerequisites Access to an Entra (Azure AD) environment with contacts data. A Zammad instance with API credentials for user management. A custom field in Zammad User Object (entra_key) of type String. A custom field in Zammad User Object (entra_object_type) of type `Single selection field with two key value pairs user = User contact = Contact` This workflow is fully customizable and can be adapted to your organization’s specific needs. Save time and reduce manual errors by automating your user sync process with this template! If you have found an error or have any suggestions, please report them here on Github.

Description This automation template is designed for Instagram marketers, influencers, and businesses looking to supercharge their Instagram engagement strategy. It automatically monitors Instagram post comments and sends personalized direct messages (DMs) to new commenters, while maintaining a smart tracking system to prevent duplicate messages. The workflow runs continuously, checking for new comments every 15 minutes and responding instantly to maintain high engagement rates. Note: This workflow uses the upload-post.com API for Instagram interactions and Google Sheets for contact tracking. The workflow is configured to monitor a specific Instagram post* Who Is This For? Instagram Marketers & Influencers:** Automatically engage with every commenter by sending personalized DMs with valuable content, links, or offers. E-commerce Businesses:** Convert Instagram comments into sales opportunities by instantly sending product links, discount codes, or catalog information via DM. Content Creators & Coaches:** Build deeper relationships with your audience by automatically reaching out to commenters with additional resources, course links, or exclusive content. Social Media Managers:** Scale client engagement without manual monitoring, ensuring no potential lead or follower interaction goes unnoticed. What Problem Does This Workflow Solve? Manually monitoring Instagram comments and sending follow-up DMs is time-consuming and often leads to missed opportunities. This workflow addresses these challenges by: Automated Comment Monitoring:** Continuously checks for new comments on your specified Instagram post every 15 minutes. Smart Duplicate Prevention:** Uses Google Sheets to track already contacted users, preventing spam and maintaining professional communication. Instant Response System:** Sends personalized DMs immediately when new comments are detected, maximizing engagement while the interaction is fresh. Scalable Engagement:** Handles multiple commenters simultaneously without manual intervention, perfect for viral posts or high-engagement content. Comprehensive Tracking:** Maintains detailed logs of all interactions including timestamps, usernames, and message content for analytics and follow-up. How It Works Post Configuration: Set your Instagram post URL, reply message, and profile username in the configuration node. Comment Monitoring: The workflow fetches all comments from your specified Instagram post using the upload-post.com API. Smart Filtering: Compares new comments against your Google Sheets database to identify users who haven't been contacted yet. Automated DM Sending: Sends personalized direct messages to new commenters with your configured message. Contact Tracking: Records each successful interaction in Google Sheets with comment ID, username, message sent, timestamp, and post URL. Continuous Monitoring: Automatically repeats the process every 15 minutes using the built-in scheduler. Setup Upload-Post API Credentials: Create an account at upload-post.com connect your Instagram account and add your API credentials to the HTTP request nodes. Google Sheets Setup: Create a Google Sheet with columns: comment_id, username, message_sent, timestamp, post_url Connect your Google account to the Google Sheets nodes Update the document ID in the "Read Contacted Users" and "Record Contacted User" nodes Instagram Post Configuration: In the "Configure Post & Message" node, update: postUrl: Your Instagram post URL to monitor replyMessage: The DM message to send to commenters profileUsername: Your Upload-post profile username Monitoring Schedule: The workflow is set to run every 15 minutes. You can adjust this in the "Schedule Trigger" node based on your needs. Requirements Accounts:** n8n, upload-post.com, Google (for Sheets access), Instagram business account. API Keys & Credentials:** Upload-post.com API token, Google Sheets OAuth2 credentials. Instagram Setup:** Business/Creator account with API access through upload-post.com. Features Duplicate Prevention:** Advanced comment ID tracking prevents sending multiple DMs to the same user Error Handling:** Robust error handling for API failures and edge cases Detailed Logging:** Comprehensive console logging for debugging and monitoring Flexible Configuration:** Easy to modify for different posts, messages, and monitoring intervals Success Tracking:** Monitors both successful and failed DM attempts for analytics Use this template to transform your Instagram engagement strategy, automatically converting every comment into a potential lead or deeper connection while maintaining professional communication standards.

AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: whether a category matches the expected one. The workflow takes support tickets and generates a category and priority, which is then compared with the correct answers in the dataset. We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular trigger so that the workflow can be started from either one. More info Once the category is generated by the agent, we check whether it matches the expected one in the dataset Finally we pass this information back to n8n as a metric

Who is this for? This workflow is designed for Customer Success Managers (CSM), sales, support, or marketing teams using HubSpot CRM who want to automate customer engagement tracking when new emails arrive. It’s ideal for businesses looking to streamline CRM updates without manual data entry. Problem Solved / Use Case Manually logging email interactions in HubSpot is time-consuming. This workflow automatically parses incoming emails, checks if the sender exists in HubSpot, and either: Creates a new contact + logs the email as an engagement (if the sender is new). Logs the email as an engagement for an existing contact. What This Workflow Does Triggers when a new email arrives in a connected IMAP inbox. Parses the email using AI (OpenAI) to extract structured data. Searches HubSpot for the sender’s email address. Updates HubSpot: Creates a contact (if missing) and logs the email as an engagement. Or logs the engagement for an existing contact. Setup Configure Email Account: Replace the default IMAP node with your email provider HubSpot Credentials: Add your HubSpot API key in the HubSpot nodes. OpenAI Integration: Ensure your OpenAI API key is set for email parsing. Customization Tips Improve AI Prompt**: Modify the OpenAI prompt to extract specific email data (e.g., customer intent). Add Filters**: Exclude auto-replies or spam by adding a filter node. Extend Functionality**: Use the parsed data to trigger follow-up tasks (e.g., Slack alerts, tickets). Need Help? Contact thomas@pollup.net for workflow modifications or help. Discover my other workflows here

This workflow combines customers' details with their payment data and passes the input to Pipedrive as a note to the organization. Prerequisites Stripe account and Stripe credentials Pipedrive account and Pipedrive credentials How it works Cron node triggers the workflow every day at 8 a.m. HTTP Request node searches for payments in Stripe. The Item Lists node creates separate items from a list of payment data. Merge node takes in the payment data as an input 1. Stripe node gets all the customers data. Set node renames customer-related data fields and keeps only needed fields. Merge node takes in the customer data as an input 2. Merge node combines the payment data with the customers one. Pipedrive node searches for the organization and creates a note with payment data.

Meeting Prep: Automated Meeting Attendee Enrichment Overview This workflow automates the process of gathering critical information about your meeting attendees right after they book a meeting. Whether they book through Calendly or Cal.com, this workflow extracts key details, uses Apollo.io to enrich their profiles with company and contact data, and logs everything into a Google Sheet for easy access. This ensures you're always prepared with relevant insights before every meeting. Use Case This workflow is perfect for: Sales Professionals**: Get instant insights into prospects' companies, roles, and social presence before calls. Customer Success Teams**: Understand your clients' business context to provide more tailored support. Recruiters**: Gather comprehensive candidate information ahead of interviews. Consultants**: Prepare for client meetings with a deeper understanding of their organization and industry. Anyone who takes meetings**: Save time on manual research and ensure you always have the data you need to make a great impression. How It Works Meeting Booking Trigger: The workflow springs into action the moment a new meeting is booked. It supports two popular scheduling platforms: Calendly: Triggers when an invitee.created event occurs. Cal.com: Triggers on a BOOKING_CREATED event. Extract Initial Data: From the booking event, the workflow extracts essential information like the attendee's name, email, company, and any notes provided during scheduling. Log Initial Entry: It immediately logs these initial details into your designated Google Sheet ("Meeting Prep" spreadsheet). This ensures a record exists, even if further enrichment isn't possible. Generate Apollo Query: Using the extracted name and company, the workflow dynamically builds a search URL for Apollo.io. This query is designed to find the most relevant person and company profiles on Apollo. Enrich with Apollo.io: The generated Apollo URL is then used to scrape Apollo.io via an Apify Scraper. This step attempts to pull extensive data, including job title, location, phone numbers, company size, industry, website URL, and social media profiles (LinkedIn, Twitter, Facebook, Github) for both the person and their company. A conditional check verifies if data was successfully retrieved from Apollo. Update Google Sheet: If data is available from Apollo: The Google Sheet entry is updated with all the rich, newly found information, changing the status to "Enriched". If data is not available: The Google Sheet entry's status is updated to "Info Not Available," clearly indicating that manual research might be needed. How to Set It Up To set up this powerful meeting prep workflow, follow these steps: Get Your API Keys: Calendly: Obtain your Calendly API key for the "Calendly Trigger" node. Cal.com: Get your Cal.com API key for the "Cal.com Trigger1" node. Apify: You'll need an Apify API token. Replace <YOURAPIKEY> in the "Scrape Apollo" node's URL with your actual Apify token. Google Sheet Setup: Copy the Template: Make a copy of the provided Google Sheet Template ("Meeting Prep") into your own Google Drive. This template has the necessary columns for enriched data. Connect Google Sheets: Ensure your Google Sheets OAuth2 API credentials are set up in n8n and linked to the "Google Sheets1" and "Google Sheets2" nodes. Update Sheet IDs: In both "Google Sheets1" and "Google Sheets2" nodes, update the documentId with the ID of your copied "Meeting Prep" Google Sheet. Import the Workflow: Import the provided workflow JSON into your n8n instance. Activate and Test: Once all credentials and sheet IDs are configured, activate the workflow. Test it by booking a new meeting through your connected Calendly or Cal.com account. Watch as your Google Sheet automatically populates with detailed attendee information! This workflow will dramatically cut down on your meeting preparation time, allowing you to focus on more strategic conversations.

This workflow automatically checks the status of your websites using UptimeRobot API. If any site is down or unstable, it will: Generate a natural-language alert message using GPT-4o Push the message to a LINE group (with funny IT-style encouragement) Log all DOWN status entries into your Supabase database Wait 30 minutes before repeating 🔧 How It Works Schedule Trigger – Runs on a fixed interval (every few minutes). UptimeRobot Node – Fetches website monitor data. Code Node (Filter) – Filters only websites with status 8 (may be down) or 9 (down). IF Node – If any site is down, proceed. LangChain LLM Node – Formats alert with a humorous message using GPT-4o. Line Notify (HTTP Request) – Sends the alert to your LINE group. Loop Over Items – Loops through all monitors. Filter Down (Status = 9) – Selects only “fully down” sites. Supabase Node – Logs these into synlora_uptime_down table. Wait Node – Delays next alert by 30 minutes to avoid spamming. ⚙️ Setup Steps Required: 🔗 UptimeRobot API Key 📲 LINE Channel Access Token and Group ID 🧠 OpenAI Key (GPT-4o Mini) 🗃️ Supabase Project & Table Step-by-step: Go to UptimeRobot → Get API key and ensure monitors are set up. Create a Supabase table with fields: website, status, uptime_id. Create a LINE Messaging API bot, join it to your group, and get: Access Token Group ID (userId or groupId) Add your OpenAI API Key for GPT-4o Mini (or switch to your preferred LLM). Import the workflow JSON into n8n. Set credentials in all necessary nodes. Activate the workflow.

Who is this for? This workflow is for professionals and teams who want to automate LinkedIn message replies with intelligent, human-like responses — without losing control over tone or accuracy. Ideal for founders, sales teams, DevRel, or community managers handling high-volume inbound messages. What problem is this workflow solving? Responding to every LinkedIn message manually is slow and inconsistent. Basic AI bots generate replies without context or nuance. This subworkflow solves both problems by using structured message routing from Notion and profile insights from UniPile to craft smart, context-aware responses. What this workflow does This workflow takes the sender’s message and profile (from LinkedIn Auto Message Router with Request Detection) and references your centralized Notion database of message types. It uses that to either match the message to a known response or generate a new one using OpenAI's GPT model — all while following professional tone guidelines. This is the third workflow in a 3-part automation system: Receives data from LinkedIn Auto Message Router with Request Detection Uses UniPile LinkedIn Profile Lookup Subworkflow to enrich responses based on follower count or org data Example Use Case If a message comes from someone with low reach (e.g., under 1,000 followers), the AI politely deflects a meeting request. If an influencer reaches out, the AI immediately offers a booking link. Your team controls this logic by updating the Notion database — no edits to the workflow required. Setup Connect this workflow as a subworkflow in your router or Slack approval flow Store your Notion API key and database ID in n8n Provide the following parent inputs: message – The LinkedIn message text sender – Name of the sender chatid – Session ID (optional for memory) linkedinprofile – Enriched array with LinkedIn context (follower count, connection info, etc.) Add your preferred AI model credentials (supports OpenAI, Gemini, or Ollama) Optional: Customize system prompt to better match your brand voice How to customize this workflow to your needs Update the Notion schema to include industry-specific categories or actions Change the AI tone (e.g., humorous, more corporate, etc.) Add conditional logic for auto-sending messages without Slack approval Extend to support multiple platforms (e.g., email, X/Twitter, Instagram DMs)

🧾 What this workflow does This workflow automatically generates avatar-style videos from the latest AI-related news using Dumpling AI and HeyGen. It runs every hour, scrapes trending articles, turns them into 30–60 second spoken scripts with GPT-4o, and produces short avatar videos with HeyGen. Finally, it logs the final video URL in a Google Sheet. 👤 Who is this for Newsletters and creators who want to automate AI trend updates Content marketers generating short-form video content Product teams experimenting with AI-generated summaries Automation enthusiasts combining LLMs + video + trending data ⚙️ How to set up 🔐 Requirements Dumpling AI API Key** stored securely as HTTP Header credential HeyGen API Key** added as an HTTP Header credential OpenAI API Key** for GPT-4o (can use GPT-4o-mini if preferred) Google Sheets account** with one column: Video link 🛠 Step-by-step setup Google Sheet Setup Create a Google Sheet with a single column named: Video link Update Credentials Use n8n’s credential manager to add tokens for: Dumpling AI HeyGen OpenAI Google Sheets Optional Customizations In the "Dumpling AI: Search AI News" node, you can change "query": "AI Agent" to other trending keywords (e.g., "Generative AI", "Autonomous Agents", etc.) Update the avatar_id and voice_id in the HeyGen request to match your preferred look/sound 🧠 How it works The Schedule Trigger runs hourly. Dumpling AI searches for fresh news related to "AI Agent." The top 4 news links are scraped for full content. Articles are merged and fed into GPT-4o via a LangChain Agent to produce a casual, conversational video script. HeyGen creates a video using the script, avatar, and voice. The workflow waits until the video rendering is complete. Once done, the final video link is logged into Google Sheets. 🧪 Customization Ideas Change the interval (e.g., every 6 hours, daily) Swap avatar/voice in HeyGen to fit your brand Expand to post the video directly to social media Add image background or B-roll overlays using Creatomate This is a fast, automated pipeline to create explainer-style AI news updates using real-time data and generative video tools.

Workflow Overview This cutting-edge n8n workflow is a powerful automation tool designed to revolutionize how content creators and marketers engage with YouTube channels. By leveraging AI and the YouTube Data API, this workflow automatically: Discovers New Content: Monitors a specific YouTube channel Retrieves the latest video in real-time Checks for new uploads at regular intervals Generates Intelligent Comments: Uses advanced AI (OpenAI's GPT models) to analyze video metadata Crafts contextually relevant, human-like comments Ensures each comment feels organic and engaging Seamless Deployment: Automatically posts the AI-generated comment directly on the video Eliminates manual interaction Increases potential channel visibility and engagement Key Benefits 🤖 Full Automation: No manual comment writing required 💡 Smart Contextual Comments: AI understands video content ⏱️ Time-Saving: Instant engagement without human intervention 📈 Potential Increased Visibility: Regular, intelligent interactions Setup Requirements YouTube Data API Credentials Obtain a Google Cloud API key Configure channel ID you want to target Set up OAuth2 authentication for comment posting OpenAI API Access Create an OpenAI account Generate an API key for comment generation Select preferred GPT model (GPT-4o, GPT-3.5, etc.) n8n Installation Install n8n (cloud or self-hosted) Import the workflow configuration Configure API credentials Set up scheduling preferences Potential Use Cases Content Creators monitoring competitor channels Marketing teams maintaining online presence Social media managers automating engagement Researchers tracking specific YouTube channels Future Enhancements Logging comment history Dynamic OAuth2 token management Multi-channel support Sentiment analysis for comment generation Connect With Me Got questions? Want to dive deeper? 📧 Email: Yaron@nofluff.online 🎥 YouTube: @YaronBeen 💼 LinkedIn: Yaron Been **Unlock the power of AI-driven YouTube engagement – automate, optimize, and amplify your online# Automate YouTube Engagement with GPT-4o Generated Comments Workflow Overview This n8n automation leverages AI to streamline YouTube channel engagement, providing a sophisticated solution for content interaction. By combining the YouTube Data API and OpenAI's GPT-4o, the workflow: Intelligent Content Discovery: Dynamically monitors specified YouTube channels Real-time detection of new video uploads Configurable monitoring intervals AI-Powered Comment Generation: Utilizes GPT-4o for contextual analysis Generates nuanced, platform-appropriate comments Ensures authentic, relevant interactions Automated Engagement: Seamlessly posts AI-crafted comments Enhances channel visibility Reduces manual social media management Key Benefits 🤖 Advanced Automation: AI-driven engagement 💡 Contextual Intelligence: GPT-4o powered insights ⏱️ Efficiency Optimization: Instant, scalable interactions 📈 Strategic Visibility: Consistent, meaningful channel presence Detailed Setup Instructions Prerequisites n8n instance (cloud or self-hosted) YouTube Data API access OpenAI API key Target YouTube channel(s) Configuration Steps YouTube Data API Setup Create a Google Cloud project Enable YouTube Data API v3 Generate OAuth2 credentials Store credentials securely in n8n OpenAI API Configuration Create OpenAI account Generate API key Select GPT-4o model Configure API key in n8n credentials Workflow Customization Replace placeholder channel IDs Adjust monitoring frequency Customize AI prompt for comment generation Configure OAuth2 authentication Workflow Customization Options Modify AI prompt to match specific content styles Add keyword filters for video selection Implement multi-channel support Create custom engagement rules Potential Use Cases Content creator audience engagement Brand social media management Community interaction automation Research and monitoring Ethical Considerations Maintain transparency about AI-generated comments Respect platform guidelines Avoid spam or misleading interactions Ensure comments add genuine value Future Enhancement Roadmap Advanced sentiment analysis Multi-language support Engagement performance tracking Adaptive comment generation Security Best Practices Never hardcode API keys Use n8n's credential management Implement secure OAuth2 authentication Regularly rotate API credentials Technical Requirements n8n v0.220.0 or higher YouTube Data API v3 OpenAI API access Stable internet connection Workflow Architecture [YouTube Channel Trigger] ⬇️ [Fetch Latest Video] ⬇️ [AI Comment Generation] ⬇️ [Post Comment] #YouTubeAutomation #AIEngagement #ContentMarketing #SocialMediaTech #GPT4Automation #WorkflowInnovation #AIComments #DigitalMarketing Connect With Me Exploring AI-Powered Social Media Automation? 📧 Email: Yaron@nofluff.online 🎥 YouTube: @YaronBeen 💼 LinkedIn: Yaron Been Transform your YouTube engagement with intelligent, responsible automation! Note: This workflow template is a starting point. Always customize and test thoroughly in your specific environment.

This workflow will archive your Spotify Discover Weekly playlist to an archive playlist named "Discover Weekly Archive" which you must create yourself. If you want to change the name of the archive playlist, you can edit value2 in the "Find Archive Playlist" node. It is configured to run at 8am on Mondays, a conservative value in case you forgot to set your GENERIC_TIMEZONE environment variable (see the docs here). Special thanks to erin2722 for creating the Spotify node and harshil1712 for help with the workflow logic. To use this workflow, you'll need to: Create then select your credentials in each Spotify node Create the archive playlist yourself Optionally, you may choose to: Edit the archive playlist name in the "Find Archive Playlist" node Adjust the Cron node with an earlier time if you know GENERIC_TIMEZONE is set Setup an error workflow like this one to be notified if anything goes wrong

This template quickly shows how to use RAG in n8n. Who is this for? This template is for everyone who wants to start giving knowledge to their Agents through RAG. Requirements Have a PDF with custom knowledge that you want to provide to your agent. Setup No setup required. Just hit Execute Workflow, upload your knowledge document and then start chatting. How to customize this to your needs Add custom instructions to your Agent by changing the prompts in it. Add a different way to load in knowledge to your vector store, e.g. by looking at some Google Drive files or loading knowledge from a table. Exchange the Simple Vector Store nodes with your own vector store tools ready for production. Add a more sophisticated way to rank files found in the vector store. For more information read our docs on RAG in n8n.