Workflow Templates

Turn Your Ideas into Videos—Right from Google Sheets! This workflow helps you make cool 8-second videos using Fal.AI and Veo 3, just by typing your idea into a Google Sheet. You can even choose if you want your video to have sound or not. It’s super easy—no tech skills needed! Why use this? Just type your idea in a sheet—no fancy tools or uploads. Get a video link back in the same sheet. Works with or without sound—your choice! How does it work? You write your idea, pick the video shape, and say if you want sound (true or false) in the Google Sheet. n8n reads your idea and asks Fal.AI to make your video. When your video is ready, the link shows up in your sheet. What do you need? A Google account and Google Sheets connected with service account (check this link for reference) A copy of the following Google Spreadsheet: Spreadsheet to copy An OpenAI API key A Fal.AI account with some money in it That’s it! Just add your ideas and let the workflow make the videos for you. Have fun creating! if you have any questions, just contact me at max@nervoai.com

Description This workflow automatically generates Facebook ad headlines for your product using OpenAI and evaluates their quality using custom AI-generated criteria. It ensures you get high‑quality, scroll‑stopping headlines without needing a copywriter. Overview This workflow captures a product description via a form, generates a Facebook ad headline, invents a scoring rubric, evaluates the headline against it, and optionally loops for revisions — all autonomously. Ideal for marketers and media buyers looking to scale creative testing. Tools Used n8n**: The automation platform that powers and orchestrates the entire workflow. OpenAI**: Used for headline generation, scoring criteria creation, and evaluation logic. (Optional)** Google Sheets / Notion / Email: For logging approved headlines or sharing results. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Connect OpenAI: Add your OpenAI credentials to the GPT nodes. Customize the Prompt (optional): Tweak the system prompt inside the Set_PromptForHeadline node. Add Output Handling (optional): Connect the “NO” path in the If_NeedMoreIterations node to Google Sheets, Slack, etc. (Optional) Add loop limits or storage logic to manage iterations or save results. Use Cases Media Buyers**: Generate and test hooks at scale with no creative bottlenecks. Solo Marketers**: Get high-converting headlines even without a copywriter. Agencies**: Streamline copy testing and evaluation in client campaigns. Startup Teams**: Automate creative generation during product launches or A/B tests. Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Hashtags #n8n #openai #automation #copywriting #facebookads #headlines #aicopy #promptengineering #marketingautomation #nocode #llm #creativeautomation #mediabuying #adtesting #adcreative #marketingtools #digitalmarketing #copytesting #scalablecreative #chatgpt #adhooks #growthmarketing #automatedworkflows #aiworkflow #creativeops #marketingops #growthtools

Title: Automatic Strava Titles & Descriptions Generation with AI Description: This n8n workflow connects your Strava account to an AI to automatically generate personalized titles and descriptions for every new cycling activity. It leverages the native Strava trigger to detect new activities, extracts and formats ride data, then queries an AI agent (OpenRouter, ChatGPT, etc.) with an optimized prompt to get a catchy title and inspiring description. The workflow then updates the Strava activity in real time, with zero manual intervention. Key Features: Secure connection to the Strava API (OAuth2) Automatic triggering for every new activity Intelligent data preparation and formatting AI-powered generation of personalized content (title + description) Instant update of the activity on Strava Use Cases: Cyclists wanting to automatically enhance their Strava rides Sports content creators Community management automation for sports groups Prerequisites: Strava account Strava OAuth2 credentials set up in n8n Access to a compatible AI agent (OpenRouter, ChatGPT, etc.) Benefits: Saves time Advanced personalization Boosts the appeal of every ride to your community

Use case Automatically create todo items in Todoist every morning. This workflow has two flows At 5am, delete any uncompleted tasks every morning At 5:10 am, copy all template tasks into Inbox In each template task, set the due dates and days to add the task. You can do that like this days:mon,tues; due:8pm which will add the task every Monday and Tuesday and make it due at 8pm. How to setup Add Todoist creds Create a template list to copy from in Todoist. Add days and due times on each task as necessary. Set the projects to copy from and to write to in each Todoist node

This workflow analyzes the sentiments of the feedback provided by users and sends them to a Mattermost channel. Typeform Trigger node: Whenever a user submits a response to the Typeform, the Typeform Trigger node will trigger the workflow. The node returns the response that the user has submitted in the form. Google Cloud Natural Language node: This node analyses the sentiment of the response the user has provided and gives a score. IF node: The IF node uses the score provided by the Google Cloud Natural Language node and checks if the score is negative (smaller than 0). If the score is negative we get the result as True, otherwise False. Mattermost node: If the score is negative, the IF node returns true and the true branch of the IF node is executed. We connect the Mattermost node with the true branch of the IF node. Whenever the score of the sentiment analysis is negative, the node gets executed and a message is posted on a channel in Mattermost. NoOp: This node here is optional, as the absence of this node won't make a difference to the functioning of the workflow. This workflow can be used by Product Managers to analyze the feedback of the product. The workflow can also be used by HR to analyze employee feedback. You can even use this node for sentiment analysis of Tweets. To perform a sentiment analysis of Tweets, replace the Typeform Trigger node with the Twitter node. Note:* You will need a Trigger node or Start node to start the workflow. Instead of posting a message on Mattermost, you can save the results in a database or a Google Sheet, or Airtable. Replace the Mattermost node with (or add after the Mattermost node) the node of your choice to add the result to your database. You can learn to build this workflow on the documentation page of the Google Cloud Natural Language node.

This workflow analyzes the sentiments of the feedback provided by users and sends them to a Mattermost channel. Typeform Trigger node: Whenever a user submits a response to the Typeform, the Typeform Trigger node will trigger the workflow. The node returns the response that the user has submitted in the form. AWS Comprehend node: This node analyses the sentiment of the response the user has provided and gives a score. IF node: The IF node uses the data provided by the AWS Comprehend node and checks if the sentiment is negative. If the sentiment is negative we get the result as true, otherwise false. Mattermost node: If the score is negative, the IF node returns true and the true branch of the IF node is executed. We connect the Mattermost node with the true branch of the IF node. Whenever the score of the sentiment analysis is negative, the node gets executed and a message is posted on a channel in Mattermost. NoOp: This node here is optional, as the absence of this node won't make a difference to the functioning of the workflow. This workflow can be used by Product Managers to analyze the feedback of the product. The workflow can also be used by HR to analyze employee feedback. You can even use this node for sentiment analysis of Tweets. To perform a sentiment analysis of Tweets, replace the Typeform Trigger node with the Twitter node. Note: You will need a Trigger node or Start node to start the workflow. Instead of posting a message on Mattermost, you can save the results in a database or a Google Sheet, or Airtable. Replace the Mattermost node with (or add after the Mattermost node) the node of your choice to add the result to your database.

UX Interview Analysis with OpenAI: Transcipt, Summarize, and Export to Google Sheets!* About Easily analyze and summarize UX interviews. Just upload your files to Google Drive and get the insights directly in Google Sheets. How It Works The workflow is triggered manually Upload the interview recordings in MP3 format to Google Drive (or modify the node “Filter by MP3” to support other formats) OpenAI transcribes the audio An AI agent generates a summary Store the results in Google Sheets How To Use Import the package into your n8n interface Set up credentials for each node to access the required tools Upload your interview files to Google Drive Create a Google Sheet with the following columns: • Persona • User Needs • Pain Points • New Feature Requests Connect the Google Sheets node titled “Insert results to Google Sheets” to your created document Start the workflow Requirements OpenAI for transcription and summarization (you can replace it with Gemini if preferred)

This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. Welcome to my Wikipedia Podcast Telegram Bot Workflow! This workflow creates an intelligent Telegram bot that transforms Wikipedia articles into engaging 5-minute podcast episodes using natural language queries and voice messages. What this workflow does This workflow processes incoming Telegram messages (text or voice, e.g. "Berlin") and generates professional podcast content about any Wikipedia topic (e.g. "Berlin", "Shakespeare", etc.). The AI agent researches the requested subject, creates a structured podcast script, and delivers it as high-quality audio directly through Telegram. Key Features: Voice message support (speech-to-text and text-to-speech) Wikipedia research integration for accurate content Professional podcast structure (intro, main content, outro) Natural-sounding AI voice synthesis Conversational and educational tone optimized for audio consumption This workflow has the following sequence: Telegram Trigger - Receives incoming messages (text or voice) from users via Telegram bot Text or Voice Switch - Routes the message based on input type (text message vs. voice message) Voice Message Processing (if voice input): Retrieval of voice file from Telegram Transcription of voice message to text using OpenAI Whisper Text Message Preparation (if text input) - Prepares the text message for the AI agent Wikipedia Podcast Agent - Core AI agent that: Researches the requested topic using Wikipedia tool Creates a professional 5-minute podcast script (600-750 words) Follows structured format: intro, main content, outro Uses conversational, accessible, and enthusiastic tone ElevenLabs Text to Speech - Converts the podcast script into natural-sounding audio using AI voice synthesis Send Voice Response - Delivers the generated podcast audio back to the user via Telegram Requirements: Telegram Bot API**: Documentation Create a bot via @BotFather on Telegram Get bot token and configure webhook Anthropic API** (Claude 4 Sonnet): Documentation Used for AI agent processing and podcast script generation Provides Wikipedia research capabilities OpenAI API**: Documentation Used for speech transcription (Whisper model) ElevenLabs API**: Documentation Used for high-quality text-to-speech generation Provides natural-sounding voice synthesis Important: The workflow uses the Wikipedia tool integrated with Claude 4 Sonnet to ensure accurate and comprehensive research. The AI agent is specifically prompted to create engaging, educational podcast content suitable for audio consumption. Configuration Notes: Update the Telegram chat ID in the trigger for your specific bot Modify the voice selection in ElevenLabs for different narrator styles The system prompt can be customized for different podcast formats or target audiences Supports both individual users and can be extended for group chats Feel free to contact me via LinkedIn, if you have any questions!

🧪 Binance SM 1hour Indicators Tool A precision trading signal engine that interprets 1-hour candlestick indicators for Binance Spot Market pairs using a GPT-4.1-mini LLM. Ideal for swing traders seeking directional bias and momentum clarity across medium timeframes. 🎥 Watch Tutorial: 🎯 Purpose This tool provides a structured 1-hour market read using: RSI** (Relative Strength Index) MACD** (Moving Average Convergence Divergence) BBANDS** (Bollinger Bands) SMA & EMA** (Simple and Exponential Moving Averages) ADX** (Average Directional Index) It’s invoked as a sub-agent in broader AI workflows, such as the Binance Financial Analyst Tool and the Spot Market Quant AI Agent. ⚙️ Key Features | Feature | Description | | ---------------------- | ------------------------------------------------------------- | | 🔄 Subworkflow Trigger | Runs only when called by parent agent (not standalone) | | 🧠 GPT-4.1-mini LLM | Translates numeric indicators into natural-language summaries | | 📊 Real-time Data | Pulls latest 40×1h candles via internal webhook from Binance | | 📥 Input Format | { "message": "ETHUSDT", "sessionId": "telegram_chat_id" } | | 📤 Output Format | JSON summary + Telegram-friendly HTML overview | 💡 Example Output 📊 1h Technical Overview – ETHUSDT • RSI: 59 (Neutral) • MACD: Bullish Crossover • BBANDS: Price at Upper Band • EMA > SMA → Positive Slope • ADX: 28 → Moderate Trend Strength 🧩 Use Cases | Scenario | Result | | -------------------------------------- | ----------------------------------------------- | | Mid-frame market alignment | Verifies momentum between 15m and 4h timeframes | | Quant AI Agent input | Supplies trend context for entry/exit decisions | | Standalone medium-term signal snapshot | Validates swing trade setups or filters noise | 📦 Installation Instructions Import workflow into your n8n instance Confirm internal webhook /1h-indicators is live and authorized Insert your OpenAI credentials for GPT-4.1-mini node Use only when triggered via: Binance Financial Analyst Tool Binance Spot Market Quant AI Agent 🧾 Licensing & Support 🔗 Don Jayamaha – LinkedIn linkedin.com/in/donjayamahajr © 2025 Treasurium Capital Limited Company Architecture, prompts, and signal logic are proprietary. Redistribution or commercial use requires explicit licensing. No unauthorized cloning permitted.

🤖 Discord AI Workflow: Your Automated Assistant! 🚀 🌟 Workflow Overview Transforms your Discord server into an intelligent, responsive powerhouse of communication and automation! 🔧 Core Components 💬 AI-Powered Messaging 🤝 Multi-Channel Interaction 🧠 Smart Response Generation 🔗 Seamless Workflow Integration 🚦 Trigger Modes 1️⃣ Workflow Trigger 🔓 Activated by external workflows 📨 Processes incoming tasks 🌐 Supports complex automation scenarios 2️⃣ Chat Message Trigger 🗣️ Responds to direct Discord messages 🤔 Contextual understanding 🔍 Real-time interaction 🛠️ Key Features 🤖 AI-Driven Conversations 📊 Dynamic Message Handling 🔒 Secure Credential Management 🌈 Flexible Configuration 🚀 Use Cases 📢 Automated Announcements 🆘 Support Ticket Management 📝 Content Generation 🤝 Community Engagement 💡 Smart Capabilities 🧩 Modular Design 🔄 Seamless Data Flow 📝 Character Limit Management 🌐 Multi-Channel Support 🛡️ Security & Performance 🔐 OAuth Integration 🚧 Error Handling 📊 Performance Optimization 🛠️ Continuous Improvement 🎯 Workflow Magic User Input ➡️ AI Processing ➡️ Smart Response ➡️ Discord Channel 🌟 🤖 💬 📨 🔍 Customization Playground 🎨 Personalize AI Responses 🔧 Adjust Interaction Rules 📐 Fine-Tune Workflow Behavior 🚧 Troubleshooting Toolkit 🕵️ Credential Verification 🔬 Permissions Check 📋 Comprehensive Logging 🆘 Error Handling Strategies 🌈 Future Possibilities 🤖 Advanced AI Integration 🚀 Expanded Interaction Modes 🧠 Machine Learning Enhancements 🌐 Ecosystem Expansion

Vacation Planning Agent - n8n Workflow Overview This n8n workflow creates an intelligent vacation planning chatbot that helps users find and book the perfect hotel accommodations. The agent acts as a professional travel consultant, systematically gathering travel requirements and providing personalized hotel recommendations through an interactive chat interface. Core Functionality The workflow provides a conversational AI agent that: Conducts structured information gathering** through natural conversation Automatically searches for hotels** using real-time data from Google Hotels Provides personalized recommendations** with detailed hotel information Maintains conversation context** throughout the planning process Delivers professional travel consultation** in a friendly, accessible format User Experience Flow Initial Interaction Users are greeted with a warm welcome message in German: "Hallo! Ich helfe dir, deinen perfekten Urlaub zu planen. Bitte beanworte mir die folgenden Fragen :)" Information Collection Process The agent systematically collects essential travel details: Destination - City and country/state Travel Dates - Check-in and check-out dates Guest Count - Number of travelers Room Requirements - Number of rooms needed Budget Preferences - Optional price range Automated Hotel Search Once core information is gathered, the agent automatically searches for available accommodations without requiring user permission. Recommendation Delivery Results are presented in a structured format including: Hotel names and star ratings Pricing information Location details Guest ratings and reviews Key amenities and highlights Direct booking links Required Integrations OpenAI API Purpose**: Powers the conversational AI agent Model**: GPT-4o-mini for cost-effective, intelligent responses Requirement**: Valid OpenAI API credentials SerpAPI (Google Hotels) Purpose**: Real-time hotel search and pricing data Service**: Google Hotels search engine integration Requirement**: Active SerpAPI account and API key Key Features Intelligent Conversation Management Maintains conversation context with 20-message memory buffer Handles edge cases like no available hotels or unclear responses Provides alternative suggestions when initial searches yield limited results Flexible Search Parameters Supports location-based searches worldwide Accommodates date range specifications Handles guest count and room quantity requirements Optional budget filtering (min/max price ranges) Currency customization support Professional Presentation Structured hotel recommendation format Clear pricing and availability information Contextual explanations for recommendations Additional destination insights when relevant Use Cases This workflow is ideal for: Travel websites** seeking to add AI-powered hotel booking assistance Travel agencies** wanting to automate initial consultation processes Hospitality businesses** providing customer service automation Personal travel planning** applications Customer support** for travel-related inquiries User Benefits Time-saving**: Eliminates manual hotel research Personalized results**: Tailored recommendations based on specific needs Real-time data**: Current pricing and availability information Professional guidance**: Expert-level travel consultation Seamless experience**: Natural conversation flow without complex forms Technical Requirements Essential Services n8n workflow automation platform OpenAI API access (GPT-4o-mini model) SerpAPI account with Google Hotels access Configuration Needs API credential setup for both OpenAI and SerpAPI Webhook endpoint configuration for chat trigger Memory buffer configuration for conversation context Optional Enhancements Custom branding for chat interface Additional language support beyond German greeting Integration with booking platforms for direct reservations Analytics tracking for usage insights

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🧠 Market Research & Business Case Study Generator Category: AI + Research | GPT + Perplexity | Business Strategy Skill Level: Intermediate Use Case: Market Research, Business Planning, Strategic Analysis 📌 Description: This template automates the creation of comprehensive, data-backed business case studies—perfect for entrepreneurs, analysts, consultants, and market researchers. For more of such build + step-by-step video tutorials, check out: https://www.youtube.com/@Automatewithmarc Just send a simple message like: “Give me a market opportunity analysis of a bicycle rental business in North Africa.” And the workflow does the rest. It scopes your research topic, performs live web research, and crafts a well-structured 1500-word business case study—all automatically saved to Google Docs. 🔧 How It Works: 🟢 Chat Trigger: Start the workflow by sending a prompt via the built-in Chat interface (Langchain Chat Trigger). 🧭 Research Scope Definer (GPT-4o): Breaks down the user input into structured components like industry, geography, trends, and challenges. 🌐 Deep Research (Perplexity Sonar): Performs live research to retrieve relevant industry data, consumer trends, competitive insights, and more. 📘 Business Case Writer (Claude Sonnet): Synthesizes the findings into a detailed case study with sections including: Executive Summary Market Overview Opportunity Analysis Competitive Landscape Risks & Challenges Strategic Recommendations Conclusion 📄 Google Docs Integration: The final output is appended to a connected Google Doc, so all your insights are neatly stored and ready to share. 🧰 Tools Used: OpenAI GPT-4o Perplexity Sonar Deep Research Anthropic Claude Sonnet Google Docs Chat Trigger ✅ Ideal For: Business consultants & strategy teams Market researchers & analysts Startup founders & product managers Educators & MBA students