Workflow Templates

Usecase: When a new service ticket is created in Taiga, it's often unclear whether it contains sufficient details to begin work. This workflow automates the triage process by: Using an AI model to extract key information from the ticket description. Automatically assigning values for: Type (Bug, Enhancement, Onboarding, Question) Severity (Wishlist, Minor, Normal, Important, Critical) Priority (Low, Normal, High) Status (New, Needs More Info, etc.) Detecting missing critical data and blocking the ticket if incomplete. Setup instructions here: https://github.com/emooney/Service_Ticket_Triage_Helper

This workflow gives you the ability to reply to a long email with a voice note, rather than having to type everything out. ChatGPT will format your audio response and create an email draft for you. How it works When a new email arrives in your inbox, the workflow checks if it needs a response, and it it does, it sends a message to you on Telegram via a VoiceEmailer bot. When you reply to that message with an audio message, the second part of this workflow is triggered. It checks if the message is in the right format, transcribes the audio, and creates a draft response that shows up in the same email thread. Set up steps Add your credentials for Gmail and OpenAI Create an Telegram bot following the instructions here. Connect your telegram credentials so the workflow will use your bot. Turn on the workflow, and message the bot from your telegram. Find the Chat ID from the Executions tab of your workflow, and enter it in as a variable.

Description 📄 Turn your Slack workspace into a smart AI-powered HelpDesk using this workflow. This automation listens to Slack messages and uses an AI assistant (powered by OpenAI or any other LLM) to respond to employee questions about HR, IT, or internal policies by referencing your internal documentation (such as the Policy Handbook). If the answer isn't available, it can optionally email the relevant department (HR or IT) and ask them to update the handbook. It remembers recent messages per user, cleans up intermediate responses to keep Slack threads tidy, and ensures your team gets consistent and helpful answers—without manually searching docs or escalating simple questions. Perfect for growing teams who want to streamline internal support using n8n, Slack, and AI. How it works 🛠️ This workflow turns n8n into a Slack-based HelpDesk assistant powered by AI. It listens to Slack messages using the Events API, detects whether a real user is asking a question, and responds using OpenAI (or another LLM of your choice). Here's how it works step-by-step: Webhook Trigger: The workflow starts when a message is posted in Slack via the Events API. It filters out any messages from bots to avoid loops. Identify the User: It fetches the full Slack profile of the user who posted the message and stores their name. Send Receipt Message: An initial message is sent to the user saying, “I’m on it!”, confirming their request is being processed. AI Response Handling: The message is processed using the OpenAI Chat model (GPT-4o by default). Before responding, it checks if the query matches any HR or IT policy from the Policy Handbook. If the question can’t be answered based on internal data, it can optionally alert the HR or IT department via Gmail (after user confirmation). Memory Retention: It keeps track of the last 5 interactions per user using Simple Memory, so it remembers previous context in a Slack conversation. Cleanup and Final Reply: It deletes the initial receipt message and sends a final, clean response to the user. How to use 🚀 Clone the Workflow: Download or import the JSON workflow into your n8n instance. Connect Your Credentials: Slack API (for messaging) Google Sheets API (for department contact info) Google Docs API (for the Policy Handbook) Gmail API (optional, for notifying departments) OpenAI or another AI model Slack Setup: Set up a Slack App and enable the Events API. Subscribe to message events and point them to the Webhook URL generated by the workflow. Customize Responses: Edit the initial and final Slack message nodes if you want to personalize the wording. Swap out the LLM (ChatGPT) with your preferred model in the AI Agent node. Adjust AI Behavior: Tune the prompt logic in the “AI Agent” node if you want the AI to behave differently or access different data sources. Expand Memory or Integrations: Use external databases to store longer histories. Integrate with tools like Asana, Notion, or CRM platforms for further automation. Requirements 📋 n8n (self-hosted or cloud) Slack Developer Account & App OpenAI (or any LLM provider) Google Sheets with department contact details Google Docs containing the policy Handbook Gmail account (optional, for email alerts) Knowledge of Slack Events API setup

Universal Digital Device Support Assistant Transform any device manual into an intelligent AI assistant that provides 24/7 support for your users. This template works with ANY household appliance, electronic device, or technical equipment. 🎯 Use Cases Manufacturers**: Provide instant support for your products Support Teams**: Reduce ticket volume with AI-powered answers Smart Homes**: Centralized help for all devices Personal Use**: Never lose a manual again ✨ Features Universal Compatibility**: Works with any device type Multi-Language Support**: Serve global customers Intelligent Search**: Semantic understanding of user queries Context Awareness**: Remembers conversation history Easy Setup**: Just upload your manual and go 🛠️ What's Included Webhook Endpoint: Receive user queries via API AI Agent: Processes questions intelligently Vector Database: Stores and searches manuals Memory System: Maintains conversation context Upload Pipeline: Easy manual ingestion 📋 Setup Instructions Add Your Credentials: OpenAI API key (or alternative LLM) Pinecone API key (or alternative vector DB) Upload Device Manuals: Use the manual upload trigger Paste manual text or upload PDF System automatically indexes content Configure Webhook: Set your preferred endpoint path Enable CORS if needed Deploy and share URL Optional Customization: Adjust chunk size for your content Modify system prompts for your brand Add additional tools or integrations 🔧 Supported Devices (Examples) Kitchen Appliances (ovens, dishwashers, coffee machines) Home Entertainment (TVs, sound systems, gaming consoles) Smart Home Devices (thermostats, cameras, lights) Computer Equipment (printers, routers, monitors) Power Tools & Garden Equipment Medical Devices And many more! 🌐 Integration Options Embed in your website Connect to chat platforms Mobile app integration Voice assistant compatibility Email support automation 📈 Benefits Reduce support costs by 70% Available 24/7 in multiple languages Consistent, accurate responses Scales infinitely Improves with usage 🔐 Privacy & Security Your data stays in your control Can be deployed on-premise GDPR compliant architecture No data sharing between devices 💡 Pro Tips Upload manuals in sections for better accuracy Include troubleshooting guides and FAQs Add model numbers and specifications Regular updates keep content fresh Start providing world-class device support today!

This n8n template demonstrates the beginnings of building your own n8n-powered WhatsApp chatbot! Under the hood, utilise n8n's powerful AI features to handle different message types and use an AI agent to respond to the user. A powerful tool for any use-case! How it works Incoming WhatsApp Trigger provides a way to get messages into the workflow. The message received is extracted and sent through 1 of 4 branches for processing. Each processing branch uses AI to analyse, summarize or transcribe the message so that the AI agent can understand it. The supported types are text, image, audio (voice notes) and video. The AI Agent is used to generate a response generally and uses a wikipedia tool for more complex queries. Finally, the response message is sent back to the WhatsApp user using the WhatsApp node. How to use Once you have setup and configured your WhatsApp account, you'll need to activate your workflow to start processing messages. Good to know: Large media files may negatively impact workflow performance. Requirements WhatsApp Buisness account Google Gemini for LLM. Gemini is used specifically because it can accept audio and video files whereas at time of writing, many other providers like OpenAI's GPT, do not. Customising this workflow For performance reasons, consider detecting large audio and video before sending to the LLM. Pre-processing such files may allow your agent to perform better. Go beyond and create rich and engagement customer experiences by responding using images, audio and video instead of just text!

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Description This n8n workflow automatically scrapes Airbnb listings from a specified location and saves the data to a Google Sheet. It performs pagination to collect listings across multiple pages, extracts detailed information for each property, and organizes the data in a structured format for easy analysis. How it Works The workflow operates through these high-level steps: Search Initialization: Starts with an Airbnb search for a specific location (London) with defined check-in/check-out dates and guest count Pagination Loop: Automatically processes multiple pages of search results using cursor-based pagination Data Extraction: Parses listing information including names, prices, ratings, reviews, and URLs Detail Enhancement: Fetches additional details for each listing (house rules, highlights, descriptions, amenities) Data Storage: Saves all collected data to a Google Sheet with proper formatting Loop Control: Continues until reaching the page limit (2 pages) or no more results are available Setup Steps Prerequisites n8n instance with MCP (Model Context Protocol) support Google Sheets API credentials configured Airbnb MCP client properly set up Configuration Steps Configure MCP Client Set up the Airbnb MCP client with credential ID: Ensure the client has access to airbnb_search and airbnb_listing_details tools Google Sheets Setup Create a Google Sheet with ID: 15IOJquaQ8CBtFilmFTuW8UFijux10NwSVzStyNJ1MsA Configure Google Sheets OAuth2 credentials (ID: 6YhBlgb8cXMN3Ra2) Ensure the sheet has these column headers: "id, name, url, price_per_night, total_price, price_details beds_rooms, rating, reviews, badge, location houseRules, highlights, description, amenities" Search Parameters Location: "London" (can be modified in the "Airbnb Search" node) Adults: 7 Children: 1 Check-in: "2025-08-14" Check-out: "2025-08-17" Page limit: 2 (can be adjusted in the "If1" condition node) Execution Use the manual trigger "When clicking 'Execute workflow'" to start the process Monitor the workflow execution through the n8n interface Check the Google Sheet for populated data after completion Key Features Automatic Pagination: Processes multiple pages without manual intervention Comprehensive Data: Extracts both basic listing info and detailed property information Error Handling: Includes JSON parsing error handling and data validation Batch Processing: Uses split batches for efficient processing of individual listings Real-time Updates: Appends new data to existing Google Sheet records Output Data Structure Each listing contains: Basic info: ID, name, URL, pricing details, room/bed count Ratings: Average rating and review count Location: Latitude and longitude coordinates Enhanced details: House rules, highlights, descriptions, amenities Metadata: Page number, check-in/out dates, badges

Advanced Gmail AI Auto-Responder with Context Intelligence The next-generation email automation that knows your communication style, remembers conversations, and responds with human-like intelligence. 🚀 What Makes This Advanced? Unlike basic AI email responders, this workflow creates contextually intelligent responses by: 📄 Reading your communication profile from Google Drive 🧠 Remembering full conversation history with vector embeddings 🎯 Understanding context from previous emails in the thread 🤖 Using AI agents instead of simple prompt-response patterns 💾 Building memory of your communication style and preferences The Result: Responses that sound authentically like you, with perfect context awareness. ⏱️ Time & Impact Setup Time: 45 minutes Time Saved: 2-3 hours daily Skill Level: Intermediate-Advanced Monthly Cost: $20-30 (OpenAI API + storage) Intelligence Level: Human-like contextual awareness 🛠️ Prerequisites & Setup Required Accounts: n8n Cloud/Self-hosted (AI features required) Gmail Account with API access Google Drive with profile document OpenAI Account (GPT-4o recommended) Required Credentials in n8n: Gmail OAuth2 API Google Drive OAuth2 API OpenAI API (with sufficient credits)

🔥 Upgrade to V3 Longer blogs, Higher SEO ranking with images, charts and tables We’ve released Version 3 of our AI-Powered Blog Automation workflow. We heard your complains and made a complete redesign built for serious content creators. 📝 Read the New Articles Generated by v3 🛒 View the workflow on n8n.io ✅ Longer Blog contents 3-Agent AI Architecture as the Planner, Writer, Editor: simulate a full content team for structure, writing, and QC. A more continuous flow 📈 2x bump in SEO ranking SEO Scoring System so every article is graded on keyword density, readability, structure, backlinks, and uniqueness. IF quality doesnt meet threshold, we revise the content again. 🖼️ Smarter Visuals In-blog images via Leonardo, charts via QuickChart, tables and web scraped outbound links 🕸️ Multi-Platform Publishing Auto-posts to WordPress, Twitter (X), and Dev.to 🕵️‍♂️ Research Agent Adds quotes, stats, facts, outbound links, entities, and references to improve article credibility Content Farming V2 AI Powered Blog Automation for WordPress This workflow automatically generates and publishes 10 blog posts per day to a WordPress site. It collects tech-related news articles, filters and analyzes them for relevance, expands them with research, generates SEO-optimized long-form articles using AI, creates a matching image using Leonardo AI, and publishes them via the WordPress REST API. Every step is tracked and stored in MongoDB for reference and performance tracking. You can see the demo results for the AI based articles here: Emp0 Articles How it works A scheduler runs daily to fetch the latest news from RSS feeds including BBC, TechCrunch, Wired, MIT Tech Review, HackerNoon, and others. The RSS data is normalized and filtered to include only articles published within the past 24 hours. Each article is passed through an OpenAI-powered classifier to check for relevance to predefined user topics like AI, robotics, or tech policy. Relevant articles are then aggregated, researched, and summarized with supporting sources and citations. An AI agent generates five long-tail SEO blog title ideas, ranks them by uniqueness and performance score, and selects the top one. A blog outline is created including H1 and H2 headers, keyword targeting, content structure, and featured snippet optimization. A full-length article (1000 to 1500 words) is generated based on the outline, with analogies, citations, examples, and keyword density maintained. SEO metadata is produced including meta title, description, image alt text, slug, and a readability audit. An AI-generated image is created based on the blog theme using Leonardo AI, enhanced for emotional storytelling and visual consistency. The blog article, metadata, and image are uploaded to WordPress as a draft, the image is attached, Yoast SEO metadata is set, and the article is published. All outputs including article versions, metadata, generation steps, and final blog URLs are stored in MongoDB to allow for future analytics and feedback. Requirements To run this project, you need accounts and API access for the following: | Tool | Purpose | Notes | |--------------|------------------------------------------------------------------|-----------------------------------------------------------------------| | OpenAI | Used for blog classification, generation, summarization, SEO | Around $0.20 per day, using GPT-4o-mini. Estimated monthly: $6 | | MongoDB | Stores data flexibly including drafts, titles, metadata, logs | Free tier on MongoDB Atlas offers 512 MB, enough for 64,000 articles | | Leonardo AI | Generates featured images for blog articles | $9 for 3500 credits, $5 monthly top-up needed for 300 images | | WordPress | Final publishing platform via REST API | Hosted on Hostinger for $15/year including domain | Setup Instructions Import the provided JSON file into your n8n instance. Configure these credentials in n8n: OpenAI API key MongoDB Atlas connection string HTTP Header Auth for Leonardo AI WordPress REST API credentials Modify the classifier and prompt nodes to reflect your preferred content themes. Adjust scheduler nodes if you want to change post frequency or publishing times. Run the n8n instance continuously using Docker, PM2, or hosted automation platform. Cost Estimate | Component | Daily Usage | Monthly Cost Estimate | |---------------|------------------------------|------------------------| | OpenAI | 10 posts per day | ~$6 | | Leonardo AI | 10 images per day (15 credits each) | ~$14 (9 base + 5 top-up) | | MongoDB | Free up to 512 MB | $0 | | WordPress | Hosting and domain | ~$1.25 | | Total | | ~$21/month | Observations and Learnings This system can scale daily article publishing with zero manual effort. However, current limitations include inconsistent blog length and occasional coherence issues. To address this, I plan to build a feedback loop within the workflow: An SEO Commentator Agent will assess keyword strength, structure, and discoverability. An Editor-in-Chief Agent will review tone, clarity, and narrative structure. Both agents will loop back suggestions to the content generator, improving each draft until it meets human-level standards. The final goal is to consistently produce high-quality, readable, SEO-optimized content that is indistinguishable from human writing.

The blogblizt: polylang workflow streamlines the creation and publication of high-quality blog content using powerful automation with n8n, OpenAI’s GPT and the WordPress API. It enables effortlessly generate SEO-friendly articles complete with metadata and optimized featured images, improving content freshness and search engine visibility. 💡 Why Use blogblizt? Automate content creation** to keep your blog fresh and engaging Generate SEO-optimized posts** with expert-crafted titles, meta descriptions, and focus keyphrases Save hours** of manual writing, image sourcing, and SEO configuration Leverage AI** for topic ideation and high-quality writing tailored to international student audiences Seamlessly publish and manage drafts** directly on your WordPress site via API Produce captivating, relevant featured images** without external tools Support multilingual content creation** with randomized language selection for diversity ⚡ Who Is This For? Content strategists managing WordPress blogs needing efficient topic generation SEO specialists wanting automated post creation with optimized metadata Website owners aiming to maintain active, multilingual content Marketers who want to leverage AI for high-quality, consistent article production ❓ What Problem Does It Solve? This workflow automates the entire editorial cycle—from generating engaging topics with AI, drafting full-length articles, producing featured images automatically, to posting drafts configured for SEO on WordPress—dramatically reducing editor workload and improving content output. 🔧 What This Workflow Does ⏱ Trigger Runs on manual trigger or a weekly schedule to ensure consistent content flow 📎 Fetch Site Context Retrieves recent posts, taxonomies, and WordPress API schema to understand site structure 🔍 Generate Topic Uses OpenAI GPT-4.1-mini to roll a random language and craft a targeted blog post topic + SEO metadata 🤖 Draft Article Composes a comprehensive, SEO-friendly article tailored to the generated topic 💌 Create Draft Posts the draft on WordPress with Yoast SEO fields populated 🖼 Generate Image Creates a high-quality, cinematic featured image via AI 📤 Upload & Attach Uploads the image to the WordPress media library and sets it as the post’s featured image 🔐 Setup Instructions Import the workflow file into n8n: Add credentials: WordPress API (with create-post & media permissions) OpenAI API key (for GPT and image models) Customize categories, languages, and schedule in the relevant nodes Adjust the Schedule Trigger timing as desired (e.g. every Monday at 9 AM) Test end-to-end on a staging WordPress site to verify drafts and images publish correctly 🧩 Pre-Requirements An operational n8n instance (Cloud or self-hosted) (self-hosted or n8n cloud) WordPress site with REST API access & proper authentication OpenAI account with API access for both language and image models (Optional) Yoast SEO plugin installed for metadata recognition 🛠️ Customize It Further Tweak OpenAI prompts for niche topics or additional languages Add social-media nodes to auto-share new posts Insert an editorial review step before publishing Refine image prompts for different visual styles (e.g., “modern infographic” vs. “cinematic portrait”) 🧠 Nodes Used Manual Trigger** Schedule Trigger** (weekly) HTTP Request** (fetch posts, taxonomies, schema; upload media) Code** (JavaScript analyzers for API schema & taxonomy parsing) OpenAI Chat** (GPT-4.1-mini for topics & articles) OpenAI Image Generation** (for featured images) WordPress** (create draft post) Sticky Notes** (in-flow documentation) 📞 Support Built by: Khaisa Studio Tags: wordpress, marketing, polylang Category: Content Creation Need a custom? contact me on LinkedIn or Web

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This template is your personal launchpad into the world of AI-powered automation. It provides a fully functional, interactive AI chatbot that you can set up in minutes, designed specifically for those new to AI Agents. What is an AI Agent? Think of it as a smart assistant that doesn't just talk—it acts. You give it a set of "tools" (like other n8n tool nodes), and it intelligently decides which tool to use to answer your questions or complete your tasks. This starter kit comes with a pre-built "toolbox" of superpowers, allowing your agent to: Get the Weather:** Ask for the forecast anywhere in the world. Get the News:** Fetch the latest headlines from n8n, CNN, and others. The workflow is designed to be a hands-on learning experience, with detailed sticky notes explaining every component, from the chat interface to the agent's "brain" and "memory." Set up steps Setup time: ~2-3 minutes This workflow is designed to be incredibly easy to start. You only need one free API key to get it working. Add Your AI Key: The workflow uses Google's Gemini model by default. You will need a free Gemini API key. Find the Gemini node on the canvas. The sticky note right below it (How to Get Google Gemini Credentials) provides a link and simple instructions to get your key. In the Gemini node, click the Credential dropdown and select + Create New Credential to add your key. Activate the Workflow: At the top-right of the screen, click the "Inactive" toggle switch. It will turn green and say "Active". Your agent is now live! Start Chatting: Open the Example Chat Window node (it has a 💬 icon). In its parameter panel, you will see a Chat URL. Click the link to copy it. Paste the URL into a new browser tab and start asking your agent questions! Optional: The template also includes disabled OpenAI chat model node and tools for Google Calendar, and Gmail. You can enable and configure these later to change the underlying AI model or give your agent even more superpowers!

🎙️ AI Audio Assistant with Voice-to-Voice Response Who is this for? Businesses, customer service teams, content creators, and organizations who want to provide intelligent voice-based interactions through Telegram. Perfect for accessibility-focused services, multilingual support, or hands-free customer assistance. What problem does this solve? Enables natural voice conversations with AI Breaks down language and accessibility barriers Provides instant voice responses to customer queries Reduces typing requirements for users Offers 24/7 voice-based customer support Maintains conversation context across voice interactions What this workflow does: Receives voice messages via Telegram bot Transcribes audio using Deepgram's advanced speech-to-text Processes transcribed text through AI agent with knowledge base access Generates intelligent responses based on conversation context Converts AI response to natural-sounding speech using Deepgram TTS Sends audio response back to user via Telegram Maintains conversation memory for contextual interactions 🔧 Technical Architecture Core Components: Telegram Bot**: Receives and sends voice messages Deepgram STT**: Transcribes voice to text with high accuracy OpenAI GPT**: Processes queries and generates responses Supabase Knowledge Base**: Stores and retrieves business information Memory Management**: Maintains conversation context Deepgram TTS**: Converts text responses to natural speech Data Flow: Voice Message → Telegram API → File Download Audio File → Deepgram STT → Transcript Transcript → AI Agent → Response Generation Response → Deepgram TTS → Audio File Audio Response → Telegram → User 🛠️ Setup Instructions Prerequisites Telegram Bot Token Create bot via @BotFather Get bot token and configure webhook Deepgram API Key Sign up at deepgram.com Get API key for STT and TTS services Note: Currently hardcoded in workflow OpenAI API Key OpenAI account with API access Configure in OpenAI Chat Model node Supabase Database Create Supabase project Set up knowledge_base table Configure API credentials Step-by-Step Setup Configure Telegram Bot Update telegramToken in "Prepare Voice Message Data" node Set correct bot token in Telegram nodes Test bot connectivity Set Up Deepgram Integration Replace API key in "Transcribe with Deepgram" node Update TTS endpoint in "HTTP Request" node Test voice transcription accuracy Configure Knowledge Base -- Create knowledge_base table in Supabase CREATE TABLE knowledge_base ( id UUID DEFAULT gen_random_uuid() PRIMARY KEY, question TEXT NOT NULL, answer TEXT NOT NULL, category VARCHAR(100), keywords TEXT[], created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW() ); Customize AI Prompts Update system message in "Telegram AI Agent" node Adjust temperature and max tokens in OpenAI model Configure memory session keys Test End-to-End Flow Send test voice message to bot Verify transcription accuracy Check AI response quality Validate audio output clarity 🎛️ Configuration Options Voice Recognition Settings Model**: nova-2 (Deepgram's latest model) Language**: English (en) - can be changed Smart Format**: Enabled for better punctuation AI Response Settings Temperature**: 0.3 (conservative responses) Max Tokens**: 100 (adjust based on needs) Memory**: Session-based conversation context Text-to-Speech Settings Model**: aura-2-thalia-en (natural female voice) Alternative voices**: Available in Deepgram TTS API Audio Format**: Optimized for Telegram 🔒 Security Considerations API Key Management // Current implementation has hardcoded tokens // Recommended: Use environment variables const telegramToken = process.env.TELEGRAM_BOT_TOKEN; const deepgramKey = process.env.DEEPGRAM_API_KEY; Data Privacy Voice messages are processed by external APIs Consider data retention policies Implement user consent mechanisms Ensure GDPR compliance if applicable 📊 Monitoring & Analytics Key Metrics to Track Voice message processing time Transcription accuracy rates AI response quality scores User engagement metrics Error rates and failure points Recommended Logging // Add to workflow for monitoring console.log({ timestamp: new Date().toISOString(), user_id: userData.user_id, transcript_confidence: transcriptData.confidence, response_length: aiResponse.length, processing_time: processingTime }); 🚀 Customization Ideas Enhanced Features Multi-language Support Add language detection Support multiple TTS voices Translate responses Voice Commands Implement wake words Add voice shortcuts Create voice menus Advanced AI Features Sentiment analysis Intent classification Escalation triggers Integration Expansions Connect to CRM systems Add calendar scheduling Integrate with help desk tools Performance Optimizations Implement audio preprocessing Add response caching Optimize API call sequences Implement retry mechanisms 🐛 Troubleshooting Common Issues Voice Not Transcribing Check Deepgram API key validity Verify audio format compatibility Test with shorter voice messages Poor Audio Quality Adjust TTS model settings Check network connectivity Verify Telegram audio limits AI Responses Too Generic Improve knowledge base content Adjust system prompts Increase context window Memory Not Working Check session key configuration Verify user ID extraction Test conversation continuity 💡 Best Practices Voice Interface Design Keep responses concise and clear Use natural speech patterns Avoid technical jargon Provide clear next steps Knowledge Base Management Regular content updates Clear categorization Keyword optimization Quality assurance testing User Experience Fast response times (<5 seconds) Consistent voice personality Graceful error handling Clear capability communication 📈 Success Metrics Technical KPIs Response time: <3 seconds average Transcription accuracy: >95% User satisfaction: >4.5/5 Uptime: >99.5% Business KPIs Customer query resolution rate Support ticket reduction User engagement increase Cost per interaction decrease 🔄 Maintenance Schedule Daily Monitor error logs Check API rate limits Verify service uptime Weekly Review conversation quality Update knowledge base Analyze usage patterns Monthly Performance optimization Security audit Feature updates User feedback review 📚 Additional Resources Documentation Links Deepgram STT API Deepgram TTS API Telegram Bot API OpenAI API Supabase Documentation Community Support n8n Community Forum Telegram Bot Developers Group Deepgram Developer Discord OpenAI Developer Community Note: This template requires active API subscriptions for Deepgram and OpenAI services. Costs may apply based on usage volume.

How it works This workflow reads a list of URLs every 15 minutes, and sends an HTTP request to every URL on the list. Set up steps Schedule the workflow to run at your desired frequency (default is every 15 minutes). Add your desired URLs to the list. The list should be in the same format as the image below (Don't forget to have single quotes around every URL in the list, and separate each one with a comma!): Turn the workflow ON. Ideas to customize the workflow for your own use cases: Change the HTTP method Add headers Add a request body