Workflow Templates

Transform your meetings into actionable insights automatically! This workflow captures meeting audio, transcribes conversations, generates AI summaries, and emails the results to participants—all without manual intervention. What's the Goal? Auto-record meetings** when they start and stop when they end Transcribe audio** to text using Vexa Bot integration Generate intelligent summaries** with AI-powered analysis Email summaries** to meeting participants automatically Eliminate manual note-taking** and post-meeting admin work Never miss important discussions** or action items again Why Does It Matter? Save 90% of Post-Meeting Time**: No more manual transcription or summary writing Never Lose Key Information**: Automatic capture ensures nothing falls through cracks Improve Team Productivity**: Focus on discussions, not note-taking Perfect Meeting Records**: Searchable transcripts and summaries for future reference Instant Distribution**: Summaries reach all participants immediately after meetings How It Works Step 1: Meeting Detection & Recording Start Meeting Trigger**: Detects when meeting begins via Google Meet webhook Launch Vexa Bot**: Automatically joins meeting and starts recording End Meeting Trigger**: Detects meeting end and stops recording Step 2: Audio Processing & Transcription Stop Vexa Bot**: Ends recording and retrieves audio file Fetch Meeting Audio**: Downloads recorded audio from Vexa Bot Transcribe Audio**: Converts speech to text using AI transcription Step 3: AI Summary Generation Prepare Transcript**: Formats transcribed text for AI processing Generate Summary**: AI model creates concise meeting summary with: Key discussion points Decisions made Action items assigned Next steps identified Step 4: Distribution Send Email**: Automatically emails summary to all meeting participants Setup Requirements Google Meet Integration: Configure Google Meet webhook and API credentials Set up meeting detection triggers Test with sample meeting Vexa Bot Configuration: Add Vexa Bot API credentials for recording Configure audio file retrieval settings Set recording quality and format preferences AI Model Setup: Configure AI transcription service (e.g., OpenAI Whisper, Google Speech-to-Text) Set up AI summary generation with custom prompts Define summary format and length preferences Email Configuration: Set up SMTP credentials for email distribution Create email templates for meeting summaries Configure participant list extraction from meeting metadata Import Instructions Get Workflow JSON: Copy the workflow JSON code Open n8n Editor: Navigate to your n8n dashboard Import Workflow: Click menu (⋯) → "Import from Clipboard" → Paste JSON → Import Configure Credentials: Add API keys for Google Meet, Vexa Bot, AI services, and SMTP Test Workflow: Run a test meeting to verify end-to-end functionality Your meetings will now automatically transform into actionable summaries delivered to your inbox!

Social Media Analysis and Automated Email Generation > by Thomas Vie Thomas@pollup.net Who is this for? This template is ideal for marketers, lead generation specialists, and business professionals seeking to analyze social media profiles of potential leads and automate personalized email outreach efficiently. What problem is this workflow solving? Manually analyzing social media profiles and crafting personalized emails can be time-consuming and prone to errors. This workflow streamlines the process by integrating social media APIs with AI to generate tailored communication, saving time and increasing outreach effectiveness. What this workflow does: Google Sheets Integration: Start with a Google Sheet containing lead information such as LinkedIn URL, Twitter handle, name, and email. Social Media Data Extraction: Automatically fetch profile and activity data from Twitter and LinkedIn using RapidAPI integrations. AI-Powered Content Generation: Use OpenAI's Chat Model to analyze the extracted data and generate personalized email subject lines and cover letters. Automated Email Dispatch: Send the generated email directly to the lead, with a copy sent to yourself for tracking purposes. Progress Tracking: Update the Google Sheet to indicate completed actions. Setup: Google Sheets: Create a sheet with the columns: LinkedIn URL, name, Twitter handle, email, and a "done" column for tracking. Populate the sheet with your leads. RapidAPI Accounts: Sign up for RapidAPI and subscribe to the Twitter and LinkedIn API plans. Configure API authentication keys in the workflow. AI Configuration: Connect OpenAI Chat Model with your API key for text generation. Email Integration: Add your email credentials or service (SMTP or third-party service like Gmail) for sending automated emails. How to customize this workflow to your needs: Modify the AI Prompt:** Adapt the prompt in the AI node to better align with your tone, style, or specific messaging framework. Expand Data Fields:** Add additional data fields in Google Sheets if you require further personalization. API Limits:** Adjust API configurations to fit your usage limits or upgrade to higher tiers for increased data scraping capabilities. Personalize Email Templates:** Tweak email formats to suit different audiences or use cases. Extend Functionality:** Integrate additional social media platforms or CRM tools as needed. By implementing this workflow, you’ll save time on repetitive tasks and create more effective lead generation strategies.

⚠️ Important Disclaimer: This template is only compatible with a self-hosted n8n instance using a community node. Who is this for? This workflow is ideal for digital content creators, marketers, social media managers, and automation enthusiasts who want to produce fully automated vertical video content featuring inspirational or motivational quotes. Specifically tailored for Thai language, it effectively demonstrates integration of AI-generated imagery, video, ambient sound, and visually appealing quote overlays. What problem is this workflow solving? Manually creating high-quality, vertically formatted quote videos is often repetitive, time-consuming, and involves multiple tedious steps like selecting suitable visuals, editing audio tracks, and correctly overlaying text. Additionally, manual uploading to platforms like YouTube and maintaining accurate content records are prone to errors and inefficiencies. What this workflow does: Fetches a quote, author, and scenic background description from a Google Sheet. Automatically generates a vertical background image using the Flux AI (txt2img) API. Transforms the AI-generated image into a subtly animated cinematic vertical video using the Kling video-generation API. Generates an immersive, ambient background sound using ElevenLabs’ sound generation API. Dynamically overlays the selected Thai-language quote and author text onto the generated video using FFmpeg, ensuring visually appealing typography (e.g., Kanit font). Automatically uploads the final video to YouTube. Updates the resulting YouTube video URL back to the Google Sheet, keeping your content records current and well-organized. Setup Requirements: This workflow requires a self-hosted n8n instance, as the execution of FFmpeg commands is not supported on n8n Cloud. Ensure FFmpeg is installed on your self-hosted environment. API keys and accounts setup for Flux, Kling, ElevenLabs, Google Sheets, Google Drive, and YouTube. Google Sheets Setup: Your Google Sheet must include these columns: Index** Unique identifier for each quote Quote (Thai)** Quote text in Thai language (or your chosen language) Pen Name (Thai)** Author or pen name of the quote's creator Background (EN)** Short English description of the scene (e.g., "sunrise over mountains") Prompt (EN)** Detailed English prompt describing the image/video scene (e.g., "peaceful sunrise with misty mountains") Background Image** URL of AI-generated image (updated automatically) Background Video** URL of generated video (updated automatically) Music Background** URL of generated ambient audio (updated automatically) Video Status** YouTube URL (updated automatically after upload) A ready-to-use Google Sheets template is provided [here (provide your actual link)]. To help you get started quickly, you can use this template spreadsheet. Next steps: Authenticate Google Sheets, Google Drive, YouTube API, Flux AI, Kling API, and ElevenLabs API within n8n. Ensure FFmpeg supports fonts compatible with your chosen language (for Thai, "Kanit" font is recommended). Prepare your Google Sheets with desired quotes, authors, and image/video prompts. How to customize this workflow to your needs: Fonts:** Adjust font type, size, color, and positioning within the provided FFmpeg commands in the workflow’s code nodes. Verify that selected fonts properly support your target language. Media Customization:** Customize the scene descriptions in your Google Sheet to change image/video backgrounds automatically generated by AI. Quote Management:** Easily manage, add, or update quotes and associated details directly via Google Sheets without workflow modifications. Audio Ambiance:** Customize or adjust the ambient sound prompt for ElevenLabs within the workflow’s HTTP Request node to match your video's desired mood. Benefits of using AI-generated content and localized fonts: Leveraging AI-generated visual and audio elements along with localized fonts greatly enhances audience engagement by creating visually appealing, professional-quality content tailored specifically for your target audience. This automated workflow drastically reduces production time and manual effort, enabling rapid, consistent content creation optimized for platforms such as YouTube Shorts, Instagram Reels, and TikTok.

Who Is This For? This workflow is designed for AI engineers, automation specialists, and content creators who need a scalable system to dynamically manage prompts stored in GitHub. It eliminates manual updates, enforces required variable checks, and ensures that AI interactions always receive fully processed prompts. 🚀 What Problem Does This Solve? Manually managing AI prompts can be inefficient and error-prone. This workflow: ✅ Fetches dynamic prompts from GitHub ✅ Auto-populates placeholders with values from the setVars node ✅ Ensures all required variables are present before execution ✅ Processes the formatted prompt through an AI agent 🛠 How This Workflow Works This workflow consists of three key branches, ensuring smooth prompt retrieval, variable validation, and AI processing. 1️⃣ Retrieve the Prompt from GitHub (HTTP Request → Extract from File → SetPrompt) The workflow starts manually or via an external trigger. It fetches a text-based prompt stored in a GitHub repository. The Extract from File Node retrieves the content from the GitHub file. The SetPrompt Node stores the prompt, making it accessible for processing. 📌 Note: The prompt must contain n8n expression format variables (e.g., {{ $json.company }}) so they can be dynamically replaced. 2️⃣ Extract & Auto-Populate Variables (Check All Prompt Vars → Replace Variables) A Code Node scans the prompt for placeholders in the n8n expression format ({{ $json.variableName }}). The workflow compares required variables against the setVars node: ✅ If all variables are present, it proceeds to variable replacement. ❌ If any variables are missing, the workflow stops and returns an error listing them. The Replace Variables Node replaces all placeholders with values from setVars. 📌 Example of a properly formatted GitHub prompt: Hello {{ $json.company }}, your product {{ $json.features }} launches on {{ $json.launch_date }}. This ensures seamless replacement when processed in n8n. 3️⃣ AI Processing & Output (AI Agent → Prompt Output) The Set Completed Prompt Node stores the final, processed prompt. The AI Agent Node (Ollama Chat Model) processes the prompt. The Prompt Output Node returns the fully formatted response. 📌 Optional: Modify this to use OpenAI, Claude, or other AI models. ⚠️ Error Handling: Missing Variables If a required variable is missing, the workflow stops execution and provides an error message: ⚠️ Missing Required Variables: ["launch_date"] This ensures no incomplete prompts are sent to AI agents. ✅ Example Use Case 📜 GitHub Prompt File (Using n8n Expressions) Hello {{ $json.company }}, your product {{ $json.features }} launches on {{ $json.launch_date }}. 🔹 Variables in setVars Node { "company": "PropTechPro", "features": "AI-powered Property Management", "launch_date": "March 15, 2025" } ✅ Successful Output Hello PropTechPro, your product AI-powered Property Management launches on March 15, 2025. 🚨 Error Output (If Missing launch_date) ⚠️ Missing Required Variables: ["launch_date"] 🔧 Setup Instructions 1️⃣ Connect Your GitHub Repository Store your prompt in a public or private GitHub repo. The workflow will fetch the raw file using the GitHub API. 2️⃣ Configure the SetVars Node Define the required variables in the SetVars Node. Make sure the variable names match those used in the prompt. 3️⃣ Test & Run Click Test Workflow to execute. If variables are missing, it will show an error. If everything is correct, it will output the fully formatted prompt. ⚡ How to Customize This Workflow 💡 Need CRM or Database Integration? Connect the setVars node to an Airtable, Google Sheets, or HubSpot API to pull variables dynamically. 💡 Want to Modify the AI Model? Replace the Ollama Chat Model with OpenAI, Claude, or a custom LLM endpoint. 📌 Why Use This Workflow? ✅ No Manual Updates Required – Fetches prompts dynamically from GitHub. ✅ Prevents Broken Prompts – Ensures required variables exist before execution. ✅ Works for Any Use Case – Handles AI chat prompts, marketing messages, and chatbot scripts. ✅ Compatible with All n8n Deployments – Works on Cloud, Self-Hosted, and Desktop versions.

🚀 Local Multi-LLM Testing & Performance Tracker This workflow is perfect for developers, researchers, and data scientists benchmarking multiple LLMs with LM Studio. It dynamically fetches active models, tests prompts, and tracks metrics like word count, readability, and response time, logging results into Google Sheets. Easily adjust temperature 🔥 and top P 🎯 for flexible model testing. Level of Effort: 🟢 Easy – Minimal setup with customizable options. Setup Steps: Install LM Studio and configure models. Update IP to connect to LM Studio. Create a Google Sheet for result tracking. Key Outcomes: Benchmark LLM performance. Automate results in Google Sheets for easy comparison. Version 1.0

Automatically scrape X (Twitter) for posts hiring specific roles (e.g., automation engineers, video editors, graphic designers), filter true hiring intent with AI, deduplicate in Google Sheets, and alert via Telegram. What it does Pulls recent X/Twitter posts for multiple role keywords via Apify. Normalizes each post (text, author, links, location). Uses an AI Agent to keep only posts where the author is hiring (not self-promo). Checks Google Sheets for duplicates by URL before saving. Writes qualified posts to a sheet and sends a Telegram notification. We are using n8n automation roles as the example here How it works (Step by Step) Schedule Trigger – Runs on an interval (currently every 12 hours). Scrape X/Twitter – Apify tweet-scraper fetches up to 50 latest posts for keywords like: n8n developer, looking for n8n, n8n expert, hire AI automation, looking for AI automation. Normalize Fields – Set node maps to: url, text, author.userName, author.url, author.location. AI Filter & Dedupe Check Accept only clear hiring posts for n8n/AI automation roles (reject self-promotion). Queries Google Sheets to see if url already exists; duplicates are dropped. Gate – IF node passes only non-empty AI outputs. Parse JSON Safely – Code node extracts/validates JSON from the AI output. Save to Google Sheets – Appends/updates a row (matching on url). Telegram Alert – Sends a message with the tweet URL, author, location, and text. Who it’s for Freelancers, agencies, and job seekers who want a steady radar of real hiring posts for their target roles. Customization Ideas Swap keywords to track other roles (video editors, designers, copywriters, etc.). Add Slack/Discord notifications. Extend the AI rules (e.g., different geographies or role scopes). Treat the sheet as a mini-CRM (status, outreach date, notes).

Turn plain-language chat like “Tomorrow 9 AM: write blog post” into neatly organised Todoist tasks with GPT-4o and n8n—zero code. 🪄 Ultimate Personal Todoist Agent Turn natural-language requests into perfectly-organized Todoist tasks—all on autopilot inside n8n. > “Add Finish quarterly report by Friday afternoon” → the agent creates the task, sets the due date & priority, and even drops it into the right project. ✨ 🌟 Why this workflow rocks All-in-one Todoist super‑powers** – create, update, complete, move, archive… every major Todoist endpoint is wired up (tasks, projects, sections, labels, comments). LLM‑powered intent detection** – an OpenAI model interprets plain-English (or emoji‑filled!) messages so you don’t have to remember slash‑commands. Minimal setup** – just two credentials and you’re live. Battle‑tested building block** – use it as‑is, or plug the Todoist Agent node into your own agents & chatbots. 🛠️ What you’ll need | Credential | Where it’s used | How to set it up | | ------------------ | -------------------------------------- | --------------------------------------------------------------------------------------------- | | OpenAI API | Orchestrator & LLM nodes | Paste your OpenAI secret key into an OpenAI credential in n8n. | | Todoist OAuth2 | Todoist node and HTTP Request node | Log in Todoist from your browser to set up credential in n8n. | > That’s it—no webhooks, no extra secrets. > Tested with *gpt‑4o‑latest* – the fastest & most accurate model in our trials. ⚡ Quick‑start (5 minutes) Import the JSON template (hit ▶️ Try it out on the n8n template page or drag‑drop the file into your canvas). Select your credentials in the two credential dropdowns. Click Test workflow. In the sample Function node, tweak the message field (e.g. “Tomorrow at 9 am: write blog post”). Run → watch your new Todoist task appear. (Optional) Swap the Function node for your favourite chat trigger (Telegram, Slack, WhatsApp, Discord, you name it). Boom—your personal Todoist genie is alive! 🧞‍♂️ 🧩 How it works (under the hood) [Trigger / Chat message] │ ▼ [🗂️ Orchestrator Agent] ← OpenAI Chat Model + Short‑term Memory │ ↳ Parses intent & entities │ ▼ [🤖 Todoist Agent] ← 15+ Todoist endpoints │ ↳ Executes the right call (create, update, complete, etc.) ▼ [Done ✅ ] The Orchestrator is an example. In production you can drop it and simply expose the Todoist Agent as a tool for any other agent workflow. 🎛️ Customising & extending | Idea | How to do it | | ------------------------- | ---------------------------------------------------------------------------------------- | | Notion / Sheets sync | After the Todoist Agent node, add a Notion or Google Sheets node to log completed items. | | Voice commands | Swap the chat trigger for a Speech‑to‑Text node (e.g. Whisper). | 🤝 Need custom automations? Want me to build or tweak something for you? → Email maxemelyanenko@gmail.com and let’s make it happen! ⚠️ What’s not included (yet) Shared projects & other Todoist Pro/Business endpoints. File attachments in the comments. Editing comments. Pull requests welcome! 🙌

Sort New Gmail messages by category with AI 👥 Who's it for This workflow is perfect for individuals or teams who receive a high volume of emails 📥 and want to automatically organize them into Gmail labels 🏷️ using AI. No coding required! For sorting existing emails messages in your gmail inbox, please use this free workflow: Categorize and Label Existing Gmail Emails Automatically with GPT-4o mini. 🤖 What it does It automatically processes new Gmail emails, skips those that already have labels, sends the content to an AI Agent powered by GPT-4o mini 🧠, and applies a relevant label based on the content. All labels must exist in Gmail beforehand. ⚙️ How it works 📬 Gmail Trigger – Activates on new email received. 🚫 Filter – Skips emails that already have a label. 🧠 AI Agent (GPT-4o mini) – Analyzes the message and decides which label fits best. 🧾 Structured Output Parser – Formats the AI output into a clean JSON. 🔀 Switch Node – Routes each email to the correct label path based on the AI result. 🏷️ Gmail Nodes – Assign the Gmail label to the original email. 📋 Requirements Gmail account connected to n8n Pre-created labels in Gmail matching the AI categories OpenAI credentials with GPT-4o mini access n8n's AI Agent & Structured Output Parser nodes 🛠️ How to set up Open the workflow and adjust the trigger interval (e.g., every minute, hours or Custom using Cron ⏱️) Check that the Filter skips emails with existing labels Define your categories in the AI Agent prompt and make sure they match the Gmail labels Configure the Switch Node conditions for each category Ensure each Gmail Label Node applies the correct label Save and activate the workflow ✅ 🎨 How to customize the workflow Add or remove categories in the AI prompt & Switch Node Fine-tune prompt instructions to match your specific use case

How it works • Transcribes a WhatsApp voice or text message from a prospect using Whisper or GPT • Extracts key information (name, need, context, urgency) via AI • Matches the most relevant service pack by comparing the prospect’s need with Airtable data • Dynamically fills a branded template via APITEMPLATE (HTML or PDF) • Generates a clean, personalized business proposal — including dynamic links (payment, calendar, etc.) • Sends the final PDF back instantly via WhatsApp or email Set up steps • ⏱ Estimated setup time: 45–60 minutes • ✅ You’ll need:  ◦ WhatsApp Business Cloud API access (with webhook configured)  ◦ OpenAI API key (Whisper + GPT)  ◦ Airtable (to store service packs and client input)  ◦ APITEMPLATE account (template with placeholders like {{nom}}, {{prix}}, {{lien_reservation}}, etc.)  ◦ n8n instance (cloud or self-hosted) • 📦 Create your service packs in Airtable with associated links (Stripe, Calendly…) • 🔗 The proposal auto-includes these links dynamically inside the PDF • 🚀 Workflow orchestrates the end-to-end process: from WhatsApp input to PDF delivery

This workflow allows you to scrape website content, clean the HTML, extract structured information using GPT-4o-mini, and store the results along with SEO keywords into Airtable. Ideal for building keyword lists and organizing web content for SEO research. Setup Instructions 1. Prerequisites n8n Community or Cloud instance Airtable account with a base and table ready OpenAI API Key with access to GPT-4o-mini 2. Airtable Structure Ensure your Airtable table has the following fields: | Field Name | Type | Notes | | ------------ | ------- | ------------------------------- | | Website Name | String | Name or URL of the website | | Data | String | Cleaned website text | | Keyword | String | Extracted SEO keyword list | | Status | Options | Values: Todo, In progress, Done | 3. Node Setup ✅ Form Trigger: Collects website URL from the user. ✅ HTTP Request: Fetches the website content. ✅ HTML Cleaner (Code Node): Strips out styles, tags, and whitespace to get clean text. ✅ Topic Extractor (AI Agent + GPT-4o-mini): Extracts topic-wise information from the cleaned website content. ✅ Text Cleaner (Code Node): Removes unwanted symbols like ### and **. ✅ Keyword Extractor (AI Agent + GPT-4o-mini): Generates a list of 90 important SEO keywords. ✅ Airtable Upsert: Stores the cleaned data, keywords, and status in Airtable. 4. Key Features ✅ Automatic website content scraping ✅ Clean HTML and extract plain text ✅ Use GPT-4o-mini for topic-wise information extraction ✅ Generate 90-keyword SEO lists ✅ Store and manage data in Airtable 5. Use Cases SEO Keyword Research Competitor Website Content Analysis Structured Website Data Collection Additional Workflow Recommendations ✅ Rename Nodes for Clarity | Current Name | Suggested Name | | ------------ | ------------------------------- | | Website Name | Website URL Input Form | | HTTP Request | Fetch Website Content | | Code | HTML to Plain Text Cleaner | | Split Out1 | Clean Text Splitter | | AI Agent1 | Topic Extractor (GPT-4o-mini) | | Code1 | Text Cleanup Formatter | | Split Out2 | Final Text Splitter | | AI Agent | Keyword Extractor (GPT-4o-mini) | | Airtable | Airtable Data Upsert | | Wait1 | Delay Before Merge | | Merge | Combine Data for Airtable |

🔐 Advanced SSL Health Monitor 👤 Who is this for? This workflow is designed for DevOps engineers, IT administrators, and security professionals who need comprehensive SSL certificate monitoring and health assessment across multiple domains — featuring dual verification and professional reporting without relying on expensive monitoring services. 🧩 What It Does Daily Trigger runs the workflow every morning for proactive monitoring. URL Collection fetches the list of website URLs to monitor from your data source. Dual SSL Analysis: Free SSL Assessment Script — Get from sysadmin-toolkit on Github SSL-Checker.io API — External verification for cross-validation Comprehensive Health Check: Certificate expiration monitoring (customizable threshold) SSL configuration security assessment Protocol support analysis (TLS 1.3, 1.2, deprecated protocols) Cipher suite strength evaluation Vulnerability scanning (POODLE, BEAST, etc.) Compliance checking (PCI DSS, NIST, FIPS) Smart Alert System sends Discord notifications when: Certificates expire within threshold (default: 30 days) SSL configuration issues detected (weak ciphers, deprecated protocols) Security vulnerabilities found Compliance standards not met Grade drops below acceptable level (configurable) 🎯 Key Features 🔄 Dual Verification**: Cross-checks results between internal scanner and external API 📊 SSL Labs-Style Grading**: A+ to F rating system with detailed analysis 🛡️ Security Assessment**: Vulnerability detection and compliance checking 📱 Discord Integration**: Rich embed notifications with color-coded alerts ⚙️ Setup Instructions Data Source: Configure your URL source from Notion Ensure it contains a URL column with domains to monitor Credentials: Set up Discord webhook for alert notifications Configure any required API credentials for data sources Customize Thresholds: Expiration Alert: Days before expiry (default: 30 days) Grade Threshold: Minimum acceptable SSL grade (default: B) Alert Severity: Choose which issues trigger notifications Advanced Configuration: Modify vulnerability checks based on your security requirements Adjust compliance standards for your industry needs Customize Discord message formatting and alert channels 🧠 Technical Notes Dual-Check Reliability**: Combines custom Bubobot scanner with ssl-checker.io for maximum accuracy No Vendor Lock-in**: Uses free public APIs and open-source tools Professional Reporting**: Generates SSL Labs-quality assessments Security-First Approach**: Comprehensive vulnerability and compliance checking Flexible Alerting**: Discord integration with rich formatting and conditional logic This workflow provide a comprehensive SSL security monitoring solution that rivals enterprise-grade tools while remaining completely open-source and free.

Description This workflow automates your email communication by listening for incoming emails and notifying you via Telegram. It then prompts you to provide a quick response, which it transforms into a polished, professional message inspired by Chick-fil-A’s renowned customer support style—super friendly, thoughtful, and smooth. This ensures your replies always sound top-notch, even if you’re not naturally great at writing customer messages. I use this exact flow for my own business to handle customer interactions with ease and exceptional care. Step-by-Step Setup Instructions 1. Email Connection Connect your email inbox (e.g., Gmail, Outlook) to the workflow to monitor incoming emails. Set the trigger to listen for new messages or specific labels/folders as needed. 2. Telegram Connection Connect your Telegram account using a Telegram Bot token. Configure the bot to send notifications when a new email arrives and to receive your reply input directly in Telegram. 3. OpenAI Connection Connect your OpenAI account by adding your API key. Use OpenAI to rephrase your raw responses into highly polished, friendly customer support messages. Workflow Description The system continuously monitors your email inbox. When a new email arrives, you receive an instant Telegram notification with the email summary. You reply quickly on Telegram with your initial thoughts or answers. The reply is sent to OpenAI, which “translates” it into a Chick-fil-A style, ultra-courteous response. The final message is either emailed back to the customer or saved for you to review and send manually. Target Audience and Problem Solved This workflow is perfect for: Small business owners who handle customer support alone. Entrepreneurs who want to maintain a high level of professionalism in their responses but struggle with wording. Teams looking to streamline email replies with fast, human-like, and warm communication. Problem solved: It removes the stress of crafting perfectly polite and engaging customer support emails from scratch, saving time and boosting customer satisfaction. Customization Guidance Adapting tone and style:** Change the OpenAI prompt to match your brand voice, whether more formal, casual, or playful. Different business contexts:** Adjust email filters or Telegram notifications to prioritize specific types of inquiries. Response automation:** Add extra steps to automatically send replies or integrate with CRM tools. Multilingual support:** Incorporate language detection and translation if your business serves customers in multiple languages.