Workflow Templates

This workflow automatically adds closed deals from Pipedrive as new customers into Stripe. Prerequisites Pipedrive account and Pipedrive credentials Stripe account and Stripe credentials How it works Pipedrive trigger node starts the workflow when a deal gets updated in Pipedrive. IF node checks that the current won time is not equal to the previuos one in the deal and continues the workflow if it's true. Pipedrive node extracts the organization's details to pass it further. HTTP Request node searches for the same organization's details within Stripe. If a customer doesn't exist within Stripe, Merge node passes a new customer details to Stripe. Stripe node creates a new customer.

Markdown to Notion Blocks Converter Transform markdown-formatted text into properly structured Notion page content with this comprehensive workflow. Overview This workflow automatically converts markdown text into Notion's block format and inserts it directly into a Notion page. Perfect for content creators, documentation teams, and anyone who needs to migrate markdown content to Notion. Features Complete Markdown Support**: Handles headers (H1-H4), paragraphs, lists, quotes, code blocks, and horizontal rules Rich Text Formatting**: Preserves bold, italic, and link formatting Smart Text Processing**: Generates plain text excerpts and maintains original content structure Direct Notion Integration**: Automatically inserts converted blocks into your specified Notion page Batch Processing**: Efficiently handles large content blocks What It Does Takes markdown-formatted text as input Parses and converts it to Notion's block structure Handles complex formatting including: Headers and subheaders Bulleted and numbered lists Code blocks with syntax highlighting Blockquotes Bold and italic text Links Horizontal dividers Uploads the converted content directly to your Notion page Use Cases Content Migration**: Move existing markdown documentation to Notion Automated Publishing**: Convert blog posts or articles from markdown to Notion Documentation Workflows**: Streamline technical documentation processes Content Syndication**: Publish the same content across multiple platforms Requirements Notion API credentials Target Notion page ID Markdown-formatted source content Setup Configure your Notion API credentials Replace the page ID in the HTTP request node with your target Notion page Connect your markdown data source (replace the mock data node) Execute the workflow

AI Voice Calling Bot - OpenAI GPT-4o + ElevenLabs + Twilio Integration for Multilingual Appointment Booking & Service Orders Overview Transform your business with an intelligent voice calling bot that handles customer calls automatically in 25+ languages. This N8n workflow integrates OpenAI GPT-4o, ElevenLabs text-to-speech, and Twilio for seamless appointment scheduling, pizza orders, and service bookings. Key Features Multilingual Support**: Conversations in English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Arabic, and 20+ more languages Natural AI Conversations**: GPT-4o powered responses with ElevenLabs realistic voice synthesis Multi-Service Handling**: Appointments, orders, and service requests with automatic logging Real-time Processing**: Instant speech-to-text and audio response generation Prerequisites N8n instance (self-hosted or cloud) Twilio account with phone number OpenAI API key (GPT-4o access) ElevenLabs API credentials Google Sheets access Cloud storage for audio files Setup Instructions Step 1: Configure Credentials Add API keys for OpenAI, ElevenLabs, Twilio, and Google Sheets in N8n credentials manager. Step 2: Prepare Data Storage Create Google Sheets for call logs and appointments with columns: timestamp, caller_id, speech_input, ai_response, language, call_sid. Step 3: Configure Twilio Set webhook URL to your N8n endpoint: https://your-n8n-instance.com/webhook/voice-webhook Step 4: Update Sheet IDs Replace placeholder Google Sheet IDs in workflow nodes with your actual sheet IDs. Customization Options Voice Settings**: Adjust ElevenLabs multilingual voice models and parameters AI Behavior**: Modify system prompts for specific business needs and languages Service Types**: Add custom service handling logic Business Hours**: Implement language-specific operating hours Monitoring Track call analytics, language preferences, conversion rates, and customer satisfaction across all supported languages through automated Google Sheets logging. Ready for production use with comprehensive error handling and scalability for global businesses.

This workflow automatically adds a note of the PR from GitHub to the Pipedrive contact if their GitHub email matches a Person in Pipedrive. Prerequisites Pipedrive account and Pipedrive credentials GitHub account and GitHub credentials How it works GitHub Trigger node activates the workflow when a GitHub user adds a PR. HTTP Request node gets the user's data and sends it further. Pipedrive node searches the same email that GitHub user has in Pipedrive. IF node checks whether a person with the same email exists in Pipedrive. In case there's such a person in Pipedrive, the Pipedrive node creates a note within the person's profile.

An intelligent WhatsApp-based chatbot designed for restaurants to automate customer interactions related to table bookings, menu inquiries, opening hours, services, and offers. Built using the n8n automation platform and powered by an AI language model, this solution streamlines communication, boosts efficiency, and improves customer satisfaction. Objectives Automate replies to common customer queries on WhatsApp Handle table booking requests with confirmation Provide menu item details, pricing, and dietary information Share restaurant timing, location, and service availability Promote offers and handle promotional queries Operate 24/7 without manual intervention Store bookings and conversations for reporting and analytics Workflow Summary Step 1: Message Reception Node: WhatsApp Trigger (Webhook or API-based) Function: Listens for incoming customer messages. Step 2: Intent Recognition Node: AI Query Processor (e.g., OpenAI API) Function: Detects customer intent (e.g., booking, menu, timing). Step 3: Conditional Routing Node: Switch or IF Node Function: Routes flow based on detected intent: General information (menu, timing, services) Table booking Step 4A: Respond to General Info Queries Node: AI Response or Static Reply Node Function: Returns relevant information (menu, timing, address, etc.). Step 4B: Process Booking Requests Nodes: Collect Booking Details** (via chatbot interactions) Store Booking Info** (to DB or Google Sheets) Send Booking Confirmation** (to customer) Step 5: Context Management Node: Set/Update Customer Data Function: Maintains conversation state and tracks follow-up messages. Database or Google Sheet Columns for Table Booking | Column Name | Description | | ----------------- | ----------------------------------------------- | | reservation\_id | Unique reservation identifier | | guest\_name | Full name of the guest | | contact\_number | Customer’s WhatsApp or mobile number | | email | (Optional) Email address | | booking\_date | Reservation date (YYYY-MM-DD format) | | booking\_time | Reservation time (HH\:MM format) | | party\_size | Number of guests | | table\_id | (Optional) Table number or identifier | | special\_requests | Allergies, seating preferences, etc. | | status | Booking status: Confirmed / Cancelled / Pending | | created\_at | Timestamp when booking was made | | updated\_at | Timestamp when booking was last modified | Prerequisites Verified WhatsApp Business Account with API access n8n instance (Cloud or self-hosted) Access to an AI service (e.g., OpenAI, Claude) Google Sheets, Airtable, MySQL, or other DB integration Setup Instructions Connect WhatsApp API using webhook or third-party WhatsApp provider (e.g., 360Dialog, Twilio). Integrate AI using HTTP Request or OpenAI node for response generation. Create Data Store (Google Sheet, Airtable, or MySQL) with defined booking columns. Design Workflow in n8n with intent detection, conditional logic, and response nodes. Test End-to-End by sending different WhatsApp queries and checking logs and stored data. Example Conversation Customer: “Can I book a table for 2 people tomorrow at 8 PM?” Bot: “Sure. Please provide your name and contact number to confirm the reservation for 2 people at 8:00 PM tomorrow.” \[Booking details are saved, and a confirmation is sent.] Benefits Fully automated customer interaction Supports real-time table reservations Accurate and quick responses Scales without increasing staff effort Operates 24/7 Centralized booking data for analytics Analytics and Reporting Track key performance metrics such as: Number of bookings per day/week Average response time Customer satisfaction scores (via feedback node) Popular menu items or query types Booking conversion rates Security and Compliance End-to-end encrypted WhatsApp messages Role-based access to sensitive data Compliance with data protection regulations (e.g., GDPR) Secure API integrations and storage solutions Conclusion This WhatsApp chatbot serves as a reliable, AI-powered digital front desk for restaurants. Built using n8n and scalable components, it automates customer support, manages bookings, and enhances operational efficiency while offering a seamless customer experience.

Build an AI Agent which accesses two MCP Servers: a RAG MCP Server and a Search Engine API MCP Server. This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Tutorial Click here to watch the full tutorial on YouTube! How it works We build an AI Agent which has access to two MCP servers: An MCP Server with a RAG database (click here for the RAG MCP Server An MCP Server which can access a Search Engine, so the AI Agent also has access to data about more current events Installation In order to use the MCP Client, you also have to use MCP Server Template. Open the MCP Client "MCP Client: RAG" node and update the SSE Endpoint to the MCP Server workflow Install the "n8n-nodes-mcp" community node via settings > community nodes ONLY FOR SELF-HOSTING: In Docker, click on your n8n container. Navigate to "Exec" and execute the below command to allow community nodes: N8N_COMMUNITY_PACKAGES_ALLOW_TOOL_USAGE=true Navigate to Bright Data and create a new "Web Unlocker API" with the name "mcp_unlocker". Open the "MCP Client" and add the following credentials: How to use it Run the Chat node and start asking questions More detailed instructions Missed a step? Find more detailed instructions here: Personal Newsfeed With Bright Data and n8n What is Retrievel Augmented Generation (RAG)? Large Language Models (LLM's) are trained on data until a specific cutoff date. Imagine a model is trained in December 2023 based data until September 2023. This means the model doesn't have any knowledge about events which happened in 2024. So if you ask the LLM who was the Formula 1 World Champion of 2024, it doesn't know the answer. The solution? Retrieval Augmented Generation. When using Retrieval Augmented Generation, a user's question is being sent to a semantic database. The LLM will use the information retrieved from the semantic database to answer the user's question. What is Model Context Protocol (MCP)? MCP is a communication protocol which is used by AI agents to call tools hosted on external servers. When an MCP client communicates with an MCP server, the server will provide an overview of all its tools, prompts and resources. The MCP server can then choose which tools to execute (based on the user's request) and execute the tools. An MCP client can communicate with multiple MCP servers, which can all host multiple tools.

Streamline your accounting by automatically creating QuickBooks Online customers and sales receipts whenever a successful Stripe payment is processed. Ideal for businesses looking to reduce manual data entry and improve accounting efficiency. How it works Trigger: The workflow is triggered when a new successful payment intent event is received from Stripe. Retrieve Customer Data: Fetches customer details from Stripe associated with the payment. Check QuickBooks Customer: Searches QuickBooks Online to see if the customer already exists using their email address. Create or Use Existing Customer: If the customer doesn't exist in QuickBooks, they are created; otherwise, the existing customer is used. Generate Sales Receipt: A sales receipt is created in QuickBooks Online with payment details, including item descriptions, amounts, and currency. Set up steps Connect Accounts: Authenticate both your QuickBooks Online and Stripe accounts in n8n. Webhook Setup: Configure the Stripe webhook to send payment_intent.succeeded events to this workflow. Test the Workflow: Trigger a test payment in Stripe to validate the integration. Customize Details: Adjust item descriptions or other fields in the QuickBooks sales receipt JSON body as needed. This workflow requires basic familiarity with n8n, but setup can be completed in under 15 minutes for most users.

Who is this for? This workflow is for digital marketers, small business owners, lead generation agencies, and VAs who need a scalable way to find and store local business leads using AI. It’s especially useful for teams that want to enrich leads with real-time news insights and save the structured data to Airtable. What problem is this workflow solving? Manually researching local businesses and staying up to date with relevant news is time-consuming and inefficient. This automation eliminates that burden by using Dumpling AI chat agents to generate leads and context, GPT-4o to summarize, and Airtable to store everything in one place. What this workflow does This AI workflow listens for a manual trigger in n8n and executes the following steps: Extracts local business leads using a Local Business Agent from Dumpling AI. Pulls current news related to the business type or location using a News Agent from Dumpling AI. Uses GPT-4o to combine both responses into a human-readable summary. Extracts structured lead data like name, category, and city. Saves the summary and lead data into Airtable for easy follow-up. Setup 1. Create AI Agents in Dumpling AI Sign in at Dumpling AI Create two separate agents: Local Business Agent: Designed to respond with structured lists of businesses by location and category. News Agent: Designed to fetch relevant recent news and summaries about a specific industry or region. After setting up each agent, copy the Agent Key from Dumpling AI. These keys will be required in the headers of your HTTP Request nodes in n8n. 2. Manual Trigger This workflow begins with a manual trigger inside n8n, Which is the When chat message is recieved. This makes it easy to test and reuse, especially during setup. 3. Get Local Business Data from Dumpling AI The first HTTP Request node sends a prompt like List 5 top real estate companies in Atlanta with full address and services. Include your Local Business Agent Key in the x-agent-key header. The response will return a structured list of business leads. 4. Get News Context from Dumpling AI The second HTTP Request node sends a prompt such as Give me the latest news related to the real estate market in Atlanta. Use your News Agent Key in the header. This fetches a brief set of recent news summaries relevant to the businesses being researched. 5. Use GPT-4o to Merge and Summarize The GPT node combines the list of businesses and news into one coherent summary. You can modify the prompt to output in paragraph format, bullet points, or structured notes. 6. Save Lead to Airtable The Airtable node sends all structured fields into your selected base and table. Be sure to connect your Airtable account and confirm the columns match exactly. How to customize this workflow Replace the prompt inside the HTTP node to focus on different types of businesses or cities. Expand the GPT output to include additional lead info like websites, phone numbers, or emails if the agent includes them. Add a webhook trigger to allow this flow to be run via a chatbot, external app, or button. Link to HubSpot or another CRM to sync the leads automatically. Duplicate the process to run for multiple industries in parallel. Final Notes You must create and configure your Dumpling AI agents first before running this workflow. The Agent Keys from Dumpling AI are required in both HTTP Request nodes. This flow is modular and flexible, ready for deeper CRM integrations. The manual trigger is great for testing, but you can add a Webhook node to automate it. This workflow helps you launch an intelligent lead gen process that combines location-targeted business discovery, AI-generated insights, and structured CRM-friendly output, all powered by Dumpling AI and OpenAI.

Who is this for? This workflow is perfect for customer support teams, sales departments, or solopreneurs who receive frequent email enquiries and want to automate the initial response process using AI. If you spend too much time answering similar questions, this system helps respond faster and more intelligently—without writing a single line of code. What problem is this workflow solving? Manually responding to repeated customer enquiries slows productivity and increases delay. This workflow classifies if an incoming email is a real enquiry, analyzes the content with a LangChain-powered agent, fetches helpful context using Dumpling AI, and sends a personalized reply using Gmail—all within minutes. What this workflow does Listens for new incoming Gmail messages using the Gmail Trigger node. Classifies whether the email is an enquiry using a GPT-4o classification prompt. Uses a Filter node to continue only if the email was classified as an enquiry. Passes the email content to a LangChain Agent, enhanced with memory, AI tools, and Dumpling AI to search for relevant information. The agent constructs a smart, relevant response, then sends it to the original sender via Gmail. Setup Connect Gmail Use the Gmail Trigger node to connect to the Gmail account that receives enquiries. Make sure Gmail OAuth2 credentials are authenticated. Configure Dumpling AI Agent Sign up at Dumpling AI. Create an agent trained to search your help docs, site content, or FAQs. Copy your Dumpling agent ID and API key. Paste it in the Dumpling AI Agent – Search for Relevant Info HTTP Request node. Set Up LangChain Agent No extra setup needed beyond connecting OpenAI credentials. GPT-4o is used for classification and reply generation. Enable Gmail Reply Node The final Send Email Response via Gmail node will send the AI-generated reply back to the same thread. How to customize this workflow to your needs Change the classification prompt to include other email types like “support”, “complaint”, or “sales”. Add additional logic if you want to CC someone or forward certain types of enquiries. Add a Notion or Google Sheets node to log the conversation for analytics. Replace Gmail with Outlook or another email provider by switching the nodes. Improve context by adding more AI tools like database queries or preloaded FAQs.

This workflow creates an Asana task when a new ticket is created in Zendesk. Subsequent comments on the ticket in Zendesk are added as comments to the task in Asana. Prerequisites Zendesk account and Zendesk credentials. Asana account and Asana credentials. Asana workspace to create tasks in. How it works The workflow listens for new tickets in Zendesk. When a new ticket is created, the workflow creates a new task in Asana. The Asana GID is then saved in one of the ticket's fields (in setup we call this "Asana GID"). The next time a comment is added to the ticket, the workflow retrieves the Asana GID from the ticket's field and adds the comment to the task in Asana. Setup This workflow requires that you set up a webhook in Zendesk. To do so, follow the steps below: In the workflow, open the On new Zendesk ticket node and copy the webhook URL. In Zendesk, navigate to Admin Center > Apps and integrations > Webhooks > Actions > Create Webhook. Add all the required details which can be retrieved from the On new Zendesk ticket node. The webhook URL gets added to the “Endpoint URL” field, and the “Request method” should match what is shown in n8n. Save the webhook. In Zendesk, navigate to Admin Center > Objects and rules > Business rules > Triggers > Add trigger. Give trigger a name such as “New tickets”. Under “Conditions” in “Meet ALL of the following conditions”, add “Status is New”. Under “Actions”, select “Notify active webhook” and select the webhook you created previously. In the JSON body, add the following: { "id": "{{ticket.id}}", "comment": "{{ticket.latest_comment_html}}" } Save the Zendesk trigger. You will also need to set up a field in Zendesk to store the Asana GID. To do so, follow the steps below: In Zendesk, navigate to Admin Center > Objects and rules > Tickets > Fields > Add field. Use the number field option and give the field a name such as “Asana GID”. Save the field. In n8n, open the Update ticket node and select the field you created in Zendesk.

Who is this for? This workflow is built for newsletter writers, marketers, content creators, or anyone who curates and summarizes web articles. It’s especially helpful for virtual assistants and founders who need to quickly turn web content into digestible, branded newsletters using AI. What problem is this workflow solving? Manually reading, summarizing, and formatting multiple articles into a newsletter takes time and focus. This workflow automates the process using Dumpling AI for crawling, GPT-4o for summarization, and Gmail for delivery—so you can go from raw URLs to a polished email in minutes. What this workflow does Starts manually (can also be scheduled) Reads a list of article URLs from Google Sheets Sends URLs to Dumpling AI to crawl and extract content Splits each article into a single item for processing Uses a Code node to clean and structure article data Uses an Edit Fields node to merge articles into one JSON block GPT-4o summarizes and generates HTML content for the newsletter Sends the formatted newsletter via Gmail Setup Google Sheets Create a sheet with a column (A) for article URLs Update the Read URLs from Google Sheet node to use your Sheet ID and tab name Connect your Google account in the credentials Dumpling AI Sign up at https://app.dumplingai.com Create an agent for web crawling under /crawl Add your Dumpling API key in the HTTP headers of the Crawl Content with Dumpling AI node Split Node Breaks apart the array of articles from Dumpling AI so each article is processed individually Code Node Structures each article as JSON with title, url, and cleaned text content Edit Fields Node Gathers all structured articles back into a single JSON array to prepare for AI summarization OpenAI (GPT-4o) Processes the article list and returns a formatted subject line and HTML newsletter content Gmail Connect your Gmail account to send the AI-generated newsletter to your inbox or team Update the recipient field in the Send HTML Email via Gmail node How to customize this workflow to your needs Replace the manual trigger with a Schedule node to send newsletters weekly Modify the GPT-4o prompt to change tone (e.g., more professional, funny, casual) Add filtering logic to skip low-value articles Connect Slack, Airtable, or Notion for internal team usage Change Gmail to SendGrid or Outlook if preferred Final Notes This workflow uses: Dumpling AI** /crawl endpoint to extract article content Split, **Code, and Edit Fields nodes to format multi-article input GPT-4o** for summarization and HTML formatting Gmail** for delivery This setup eliminates manual steps and delivers fast, consistent newsletters powered by AI.

🎤 Audio-to-Insights: Auto Meeting Summarizer Transform your meeting recordings into actionable insights automatically. This powerful n8n workflow monitors your Google Drive for new audio files, transcribes them using OpenAI's Whisper, generates intelligent summaries with ChatGPT, and logs everything in Google Sheets - all without lifting a finger. 🔄 How It Works This workflow operates as a seamless 6-step automation pipeline: Step 1: Smart Detection The workflow continuously monitors a designated Google Drive folder (polls every minute) for newly uploaded audio files. Step 2: Secure Download When a new audio file is detected, the system automatically downloads it from Google Drive for processing. Step 3: AI Transcription OpenAI's Whisper technology converts your audio recording into accurate text transcription, supporting multiple audio formats. Step 4: Intelligent Summarization ChatGPT processes the transcript using a specialized prompt that extracts: Key discussion points and decisions Action items with assigned persons and deadlines Priority levels and follow-up tasks Clean, professional formatting Step 5: Timestamp Generation The system automatically adds the current date and formats it consistently for tracking purposes. Step 6: Automated Logging The final summary is appended to your Google Sheets document with the date, creating a searchable archive of all meeting insights. ⚙️ Setup Steps Prerequisites Before setting up the workflow, ensure you have: Active Google Drive account OpenAI API key with credits Google Sheets access n8n instance (cloud or self-hosted) Configuration Steps 1. Credential Setup Google Drive OAuth2**: Required for folder monitoring and file downloads OpenAI API Key**: Needed for both transcription (Whisper) and summarization (ChatGPT) Google Sheets OAuth2**: Essential for writing summaries to your spreadsheet 2. Google Drive Configuration Create a dedicated folder in Google Drive for meeting recordings Copy the folder ID from the URL (the long string after /folders/) Update the folderToWatch parameter in the workflow 3. Google Sheets Preparation Create a new Google Sheet or use an existing one Ensure it has columns: Date and Meeting Summary Copy the spreadsheet ID from the URL Update the documentId parameter in the workflow 4. Audio Requirements Supported Formats**: MP3, WAV, M4A, MP4 Recommended Size**: Under 100MB for optimal processing Language**: Optimized for English (customizable for other languages) Quality**: Clear audio produces better transcriptions 5. Workflow Activation Import the workflow JSON into your n8n instance Configure all credential connections Test with a sample audio file Activate the workflow trigger 🚀 Use Cases Project Management Team Standup Summaries**: Convert daily standups into actionable task lists Sprint Retrospectives**: Extract improvement points and action items Stakeholder Updates**: Generate concise reports for leadership Sales & Customer Success Discovery Call Notes**: Capture prospect pain points and requirements Demo Follow-ups**: Track questions, objections, and next steps Customer Check-ins**: Monitor satisfaction and expansion opportunities Consulting & Professional Services Client Strategy Sessions**: Document recommendations and implementation plans Requirements Gathering**: Organize complex project specifications Progress Reviews**: Track deliverables and milestone achievements HR & Training Interview Debriefs**: Standardize candidate evaluation notes Training Sessions**: Create searchable knowledge bases Performance Reviews**: Document development plans and goals Research & Development Brainstorming Sessions**: Capture innovative ideas and concepts Technical Reviews**: Log decisions and architectural choices User Research**: Organize feedback and insights systematically 💡 Advanced Customization Options Enhanced Summarization Modify the ChatGPT prompt to focus on specific elements: Add speaker identification for multi-person meetings Include sentiment analysis for customer calls Generate department-specific summaries (technical, sales, legal) Extract financial figures and metrics automatically Integration Expansions Slack Integration**: Auto-post summaries to relevant channels Email Notifications**: Send summaries to meeting participants CRM Updates**: Push action items directly to Salesforce/HubSpot Calendar Integration**: Schedule follow-up meetings based on action items Quality Improvements Audio Preprocessing**: Add noise reduction before transcription Multi-language Support**: Configure for international teams Custom Templates**: Create industry-specific summary formats Approval Workflows**: Add human review before final storage 🛠️ Troubleshooting & Best Practices Common Issues Large File Processing**: Split recordings over 100MB into smaller segments Poor Audio Quality**: Use noise reduction tools before uploading API Rate Limits**: Implement delay nodes for high-volume usage Formatting Issues**: Adjust ChatGPT prompts for consistent output Optimization Tips Upload files in supported formats only Ensure stable internet connection for cloud processing Monitor OpenAI API usage and costs Regularly backup your Google Sheets data Test workflow changes with sample files first 📊 Expected Outputs Sample Summary Format: Meeting Summary - March 15, 2024 Key Discussion Points: Q1 budget review and allocation decisions New product launch timeline and milestones Team restructuring and role assignments Action Items: John: Finalize budget proposal by March 20th (High Priority) Sarah: Schedule product demo sessions for March 25th Team: Submit org chart feedback by March 18th Decisions Made: Approved additional marketing budget of $50K Delayed product launch to April 15th for quality assurance Promoted Lisa to Senior Developer role 📞 Questions & Support For any questions, customizations, or technical support regarding this workflow: 📧 Email Support Primary Contact**: Yaron@nofluff.online Response Time**: Within 24 hours on business days Best For**: Setup questions, customization requests, troubleshooting 🎥 Learning Resources YouTube Channel**: https://www.youtube.com/@YaronBeen/videos Step-by-step setup tutorials Advanced customization guides Workflow optimization tips 🔗 Professional Network LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Connect for ongoing support Share your workflow success stories Get updates on new automation ideas 💡 What to Include in Your Support Request Describe your specific use case Share any error messages or logs Mention your n8n version and setup type Include sample audio file characteristics (if relevant) Ready to transform your meeting chaos into organized insights? Download the workflow and start automating your meeting summaries today!