Workflow Templates

Follow me on LinkedIn for more! Category: Lead Generation, Data Collection, Business Intelligence Tags: lead-generation, google-maps, rapidapi, business-data, contact-extraction, google-sheets, duplicate-prevention, automation Difficulty Level: Intermediate Estimated Setup Time: 15-20 minutes Template Description Overview This powerful n8n workflow automates the extraction of comprehensive business information from Google Maps using keyword-based searches via RapidAPI's Local Business Data service. Perfect for lead generation, market research, and competitive analysis, this template intelligently gathers business data including contact details, social media profiles, and location information while preventing duplicates and optimizing API usage. Key Features 🔍 Keyword-Based Google Maps Scraping**: Search for any business type in any location using natural language queries 📧 Contact Information Extraction**: Automatically extracts emails, phone numbers, and social media profiles (LinkedIn, Instagram, Facebook, etc.) 🚫 Smart Duplicate Prevention**: Two-level duplicate detection saves 50-80% on API costs by skipping processed searches and preventing duplicate business entries 📊 Google Sheets Integration**: Seamless data storage with automatic organization and structure 🌍 Multi-Location Support**: Process multiple cities, regions, or countries in a single workflow execution ⚡ Rate Limiting & Error Handling**: Built-in delays and error handling ensure reliable, uninterrupted execution 💰 Cost Optimization**: Intelligent batching and duplicate prevention minimize API usage and costs 📱 Comprehensive Data Collection**: Gather business names, addresses, ratings, reviews, websites, verification status, and more Prerequisites Required Services & Accounts RapidAPI Account with subscription to "Local Business Data" API Google Account for Google Sheets integration n8n Instance (cloud or self-hosted) Required Credentials RapidAPI HTTP Header Authentication** for Local Business Data API Google Sheets OAuth2** for data storage and retrieval Setup Instructions Step 1: RapidAPI Configuration Create RapidAPI Account Sign up at RapidAPI.com Navigate to "Local Business Data" API Subscribe to a plan (Basic plan supports 1000 requests/month) Get API Credentials Copy your X-RapidAPI-Key from the API dashboard Note the host: local-business-data.p.rapidapi.com Configure n8n Credential In n8n: Settings → Credentials → Create New Type: HTTP Header Auth Name: RapidAPI Local Business Data Add headers: X-RapidAPI-Key: YOUR_API_KEY X-RapidAPI-Host: local-business-data.p.rapidapi.com Step 2: Google Sheets Setup Enable Google Sheets API Go to Google Cloud Console Enable Google Sheets API for your project Create OAuth2 credentials Configure n8n Credential In n8n: Settings → Credentials → Create New Type: Google Sheets OAuth2 API Follow OAuth2 setup process Create Google Sheet Structure Create a new Google Sheet with these tabs: keyword_searches sheet: | select | query | lat | lon | country_iso_code | |--------|-------|-----|-----|------------------| | X | Restaurants Madrid | 40.4168 | -3.7038 | ES | | X | Hair Salons Brooklyn | 40.6782 | -73.9442 | US | | X | Coffee Shops Paris | 48.8566 | 2.3522 | FR | stores_data sheet: The workflow will automatically create columns for business data including: business_id, name, phone_number, email, website, full_address, rating, review_count, linkedin, instagram, query, lat, lon, and 25+ more fields Step 3: Workflow Configuration Import the Workflow Copy the provided JSON In n8n: Import from JSON Update Placeholder Values Replace YOUR_GOOGLE_SHEET_ID with your actual Google Sheet ID Update credential references to match your setup Configure Search Parameters (Optional) Adjust limit: 1-100 results per query (default: 100) Modify zoom: 10-18 search radius (default: 13) Change language: EN, ES, FR, etc. (default: EN) How It Works Workflow Process Load Search Criteria: Reads queries marked with "X" from keyword_searches sheet Load Existing Data: Retrieves previously processed data for duplicate detection Filter New Searches: Smart merge identifies only new query+location combinations Process Each Location: Sequential processing prevents API overload Configure Parameters: Prepares search parameters from sheet data API Request: Calls RapidAPI to extract business information Parse Data: Structures and cleans all business information Save Results: Stores new leads in stores_data sheet Rate Limiting: 10-second delay between requests Loop: Continues until all new searches are processed Duplicate Prevention Logic Search Level: Compares new queries against existing data using query+latitude combination, skipping already processed searches. Business Level: Each business receives a unique business_id to prevent duplicate entries even across different searches. Data Extracted Business Information Business name, full address, phone number Website URL, Google My Business rating and review count Business type, price level, verification status Geographic coordinates (latitude/longitude) Detailed location breakdown (street, city, state, country, zip) Contact Details Email addresses (when publicly available) Social media profiles: LinkedIn, Instagram, Facebook, Twitter, YouTube, TikTok, Pinterest Additional phone numbers Direct Google Maps and reviews links Search Metadata Original search query and parameters Extraction timestamp and geographic data API response details for tracking Use Cases Lead Generation Generate targeted prospect lists for B2B sales Build location-specific customer databases Create industry-specific contact lists Develop territory-based sales strategies Market Research Analyze competitor density in target markets Study business distribution

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. JSON Architect - Dynamically Generate JSON Output Formats for Any AI Agent Overview Version: 1.0 The JSON Architect Workflow is designed to instruct AI agents on the required JSON structure for a given context and create the appropriate JSON output format. This workflow ensures that the generated JSON is validated and tested, providing a reliable JSON output format for use in various applications. ✨ Features Dynamic JSON Generation**: Automatically generate the JSON format based on the input requirements. Validation and Testing**: Validate the generated JSON format and test its functionality, ensuring reliability before output. Iterative Improvement**: If the generated JSON is invalid or fails testing, the workflow will attempt to regenerate it until successful or until a defined maximum number of rounds is reached. Structured Output**: The final output is the generated JSON output format, making it easy to integrate with other systems or workflows. 👤 Who is this for? This workflow is ideal for developers, data scientists, and businesses that require dynamic JSON structures for the responses of AI agents. It is particularly useful for those involved in procedural generation, data interchange formats, configuration management and machine learning model input/output. 💡 What problem does this solve? The workflow addresses the challenge of generating optimal JSON structures by automating the process of creation, validation, and testing. This approach ensures that the JSON format is appropriate for its intended use, reducing errors and enhancing the overall quality of data interchange. Use-Case examples: 🔄 Data Interchange Formats 🛠️ Procedural Generation 📊 Machine Learning Model Input/Output ⚙️ Configuration Management 🔍 What this workflow does The workflow orchestrates a process where AI agents generate, validate, and test JSON output formats based on the provided input. This approach leads to a more refined and functional JSON output parser. 🔄 Workflow Steps Input & Setup: The initial input is provided, and the workflow is configured with necessary parameters. Round Start: Initiates the round of JSON construction, ensuring the input is as expected. JSON Generation & Validation: Generates and validates the JSON output format according to the input. JSON Test: Verifies whether the generated JSON output format works as intended. Validation or Test Fails: If the JSON fails validation or testing, the process loops back to the Round Start for correction. Final Output: The final output is generated based on successful JSON construction, providing a cohesive response. 📌 Expected Input input**: The input that requires a proper JSON structure. max_rounds**: The maximum number of rounds before stopping the loop if it fails to produce and test a valid JSON structure. Suggested: 10. rounds**: The initial number of rounds. Default: 0. 📦 Expected Output input**: The original input used to create the JSON structure. json_format_name**: A snake_case identifier for the generated JSON format. Useful if you plan to reuse it for multiple AI agents or Workflows. json_format_usage**: A description of how to use the JSON output format in an input. Meant to be used by AI agents receiving the JSON output format in their output parser. json_format_valid_reason**: The reason provided by the AI agents explaining why this JSON format works for the input. json_format_structure: The JSON format itself, intended for application through the **Advanced JSON Output Parser custom node. json_format_input: The **input after the JSON output format ( json_format_structure ) has been applied in an AI agent's output parser. 📌 Example An example that includes both the input and the final output is provided in a note within the workflow. ⚙️ n8n Setup Used n8n Version**: 1.100.1 n8n-nodes-advanced-output-parser**: 1.0.1 Running n8n via**: Podman 4.3.1 Operating System**: Linux ⚡ Requirements to Use/Setup 🔐🔧 Credentials & Configuration Obtain the necessary LLM API key and permissions to utilize the workflow effectively. This workflow is dependent on a custom node for dynamically inputting JSON output formats called n8n-nodes-advanced-output-parser. You can find the repository here. Warning: As of 2025-07-09, the custom node creator has warned that this node is not production-ready. Beware when using it in production environments without being aware of its readiness. ⚠️ Notes, Assumptions & Warnings This workflow assumes that users have a basic understanding of n8n and JSON configuration. This workflow assumes that users have access to the necessary API keys and permissions to utilize the Mistral API or other LLM APIs. Ensure that the input provided to the AI agents is clear and concise to avoid confusion in the JSON generation process. Ambiguous inputs may lead to invalid or irrelevant JSON output formats. ℹ️ About Us This workflow was developed by the Hybroht team of AI enthusiasts and developers dedicated to enhancing the capabilities of AI through collaborative processes. Our goal is to create tools that harness the possibilities of AI technology and more.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Transform email overload into actionable insights with this automated daily digest workflow that intelligently summarizes categorized emails using AI. Who's it for This workflow is perfect for busy professionals, content creators, and newsletter subscribers who need to stay informed without spending hours reading through multiple emails. Whether you're tracking industry news, monitoring competitor updates, or managing content subscriptions, this automation helps you extract key insights efficiently. How it works The workflow runs automatically each morning at 9 AM, fetching emails from a specific Gmail label received in the last 24 hours. Each email is processed through OpenAI's language model using LangChain to create concise, readable summaries that preserve important links and formatting. All summaries are then combined into a single, well-formatted digest email and sent to your inbox, replacing dozens of individual emails with one comprehensive overview. How to set up Create a Gmail label for emails you want summarized (e.g., "Tech News", "Industry Updates") Configure credentials for both Gmail OAuth2 and OpenAI API in their respective nodes Update the Gmail label ID in the "Get mails (last 24h)" node with your specific label Set your email address in the "Send Digested mail" node Adjust the schedule in the Schedule Trigger if you prefer a different time than 9 AM Test the workflow with a few labeled emails to ensure proper formatting Requirements Gmail account with OAuth2 authentication configured OpenAI API account and valid API key At least one Gmail label set up for email categorization Basic understanding of n8n workflow execution How to customize the workflow Change summarization style: Modify the prompt in the "Summarization Mails" node to adjust tone, length, or format of summaries. You can make summaries more technical, casual, or focus on specific aspects like action items. Adjust time range: Change the receivedAfter parameter in the Gmail node to fetch emails from different time periods (last 2 days, last week, etc.). Multiple labels: Duplicate the Gmail retrieval section to process multiple labels and combine them into categories within your digest. Add filtering: Insert additional conditions to filter emails by sender, subject keywords, or other criteria before summarization. Custom formatting: Modify the "Combine Subject and Body" code node to change the HTML structure, add styling, or include additional metadata like email timestamps or priority indicators.

This n8n template demonstrates how to automate YouTube content repurposing using AI. Upload a video to Google Drive and automatically generate transcriptions, A/B testable titles, AI thumbnails, short-form clips with captions, and YouTube descriptions with chapter timestamps. Use cases include: Content creators who publish 1-2 long-form videos per week and need to extract 5-10 short-form clips, YouTube agencies managing multiple channels, or automation consultants building content systems for clients. Good to know Processing time is approximately 10-15 minutes per video depending on length Cost per video is roughly $1.00 (transcription $0.65, AI generation $0.35) YouTube captions take 10-60 minutes to generate after upload - the workflow includes automatic polling to check when captions are ready Manual steps still required: video clipping (using provided timestamps), social media posting, and YouTube A/B test setup How it works When a video is uploaded to Google Drive, the workflow automatically triggers and creates an Airtable record The video URL is sent to AssemblyAI (via Apify) for transcription with H:MM:SS.mmm timestamps GPT-4o-mini analyzes the transcript and generates 3 title variations optimized for A/B testing When you click "Generate thumbnail" in Airtable, your prompt is optimized and sent to Kie.ai's Nano Banana Pro model with 2 reference images for consistent branding After uploading to YouTube, the workflow polls YouTube's API every 5 minutes to check if auto-generated captions are ready Once captions are available, click "Generate clips" and Grok 4.1 Fast analyzes the transcript to identify 3-8 elite clips (45+ seconds each) with proper start/end boundaries and action-oriented captions GPT-4o-mini generates a YouTube description with chapter timestamps based on the transcript All outputs are saved to Airtable: titles, thumbnail, clip timestamps with captions, and description How to use Duplicate the provided Airtable base template and connect it to your n8n instance Create a Google Drive folder for uploading edited videos After activating the workflow, copy webhook URLs and paste them into Airtable button formulas and automations Upload your edited video to the designated Google Drive folder to trigger the system The workflow automatically generates titles and begins transcription Add your thumbnail prompt and 2 reference images to Airtable, then click "Generate thumbnail" Upload the video to YouTube as unlisted, paste the video ID into Airtable, and check the box to trigger clip generation Use the provided timestamps to manually clip videos in your editor Copy titles, thumbnail, clips, and description from Airtable to publish across platforms Requirements Airtable account (Pro plan recommended for automations) Google Drive for video upload monitoring Apify account for video transcription via AssemblyAI actor OpenAI API key for title and description generation (GPT-4o-mini) OpenRouter API key for clip identification (Grok 4.1 Fast) Kie.ai account for AI thumbnail generation (Nano Banana Pro model) YouTube Data API credentials for caption polling Customising this workflow Tailor the system prompts to your content niche by asking Claude to adjust them without changing the core structure Modify the clip identification criteria (length, caption style, number of clips) in the Grok prompt Adjust thumbnail generation style by updating the image prompt optimizer Add custom fields to Airtable for tracking performance metrics or additional metadata Integrate with additional platforms like TikTok or Instagram APIs for automated posting

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automated Research Reports with AI and Tavily Search An intelligent research automation workflow designed for Japanese users that transforms user queries into comprehensive HTML reports via email. Using Google Gemini AI and Tavily search, this workflow generates optimized search queries, conducts multi-perspective research, and delivers structured analysis reports in Japanese. Who's it for Content creators, researchers, analysts, and businesses in Japan who need comprehensive research reports on various topics without manual information gathering. Particularly valuable for Japanese professionals conducting competitive analysis, market research, and technical comparisons who prefer reports in their native language. How it works The workflow follows a strategic four-step process: Query Optimization: Google Gemini AI analyzes user input and generates three optimized search queries for comprehensive coverage Multi-Query Research: Tavily's advanced search executes all queries with deep search parameters and AI-generated answers Report Synthesis: Another Gemini AI model consolidates findings, eliminates duplicates, and structures information into readable HTML format Email Delivery: Gmail automatically sends the final HTML report to specified recipients Requirements Google Gemini API credentials (for three separate AI nodes) Tavily API credentials for advanced search functionality Gmail authentication for email delivery Basic n8n workflow execution permissions How to set up Configure API credentials in all Google Gemini and Tavily nodes Update email settings in the "Send a message" node with your recipient address Customize your query in the "Edit Fields" node (default: "n8nとdifyの違い") Test the workflow to ensure all connections work properly How to customize the workflow Research depth: Increase max_results in Tavily search for more comprehensive data gathering. Query optimization: Modify system prompts in the Query Generator for domain-specific searches. Report format: Adjust the Report Agent's system message to change output structure, language, or focus areas. Multi-recipient delivery: Duplicate the Gmail node for multiple email destinations. The workflow processes Japanese and English queries effectively, with built-in support for Japanese language output, making it ideal for Japanese professionals who need multilingual research capabilities. Advanced search parameters ensure high-quality, relevant results for professional research applications.

Transform chaotic support requests into organized, actionable insights automatically. This intelligent workflow captures support tickets from forms, uses AI to categorize and analyze sentiment, stores everything in organized databases, and delivers comprehensive analytics reports to your team - eliminating manual sorting while providing valuable business intelligence. 🚀 What It Does Intelligent Ticket Processing: Automatically categorizes incoming support requests into Billing, Bug Reports, Feature Requests, How-To questions, and Complaints using advanced AI analysis. Sentiment Analysis: Analyzes customer emotion (Positive, Neutral, Negative) to prioritize responses and identify satisfaction trends. Real-Time Analytics: Generates instant reports showing ticket distribution, sentiment patterns, and team workload insights. Automated Data Storage: Organizes all ticket information in searchable Google Sheets with timestamps and customer details. Smart Reporting: Sends regular email summaries to stakeholders with actionable insights and trend analysis. 🎯 Key Benefits ✅ Save 10+ Hours Weekly: Eliminate manual ticket sorting and categorization ✅ Improve Response Times: Prioritize tickets based on category and sentiment ✅ Boost Customer Satisfaction: Never miss urgent issues or complaints ✅ Track Performance: Monitor support trends and team effectiveness ✅ Scale Operations: Handle increasing ticket volume without additional staff ✅ Data-Driven Decisions: Make informed improvements based on real patterns 🏢 Perfect For Customer Support Teams SaaS companies managing user inquiries and bug reports E-commerce stores handling order and product questions Service businesses organizing client communications Startups scaling support operations efficiently Business Applications Help Desk Management**: Organize and prioritize incoming support requests Customer Success**: Monitor satisfaction levels and identify improvement areas Product Development**: Track feature requests and bug report patterns Team Management**: Distribute workload based on ticket categories and urgency ⚙️ What's Included Complete Workflow Setup: Ready-to-use n8n workflow with all nodes configured AI Integration: Google Gemini-powered classification and sentiment analysis Form Integration: Works with Typeform (easily adaptable to other platforms) Data Management: Automated Google Sheets organization and storage Email Reporting: Professional summary reports sent to your team Documentation: Step-by-step setup and customization guide 🔧 Technical Requirements n8n Platform**: Cloud or self-hosted instance Google Gemini API**: For AI classification (free tier available) Typeform Account**: For support form creation (alternatives supported) Google Workspace**: For Sheets data storage and Gmail reporting SMTP Email**: For automated report delivery 📊 Sample Output Daily Support Summary Email: 📧 Support Ticket Summary - March 15, 2024 📊 TICKET BREAKDOWN: • Billing: 12 tickets (30%) • Bug Report: 8 tickets (20%) • Feature Request: 6 tickets (15%) • How-To: 10 tickets (25%) • Complaint: 4 tickets (10%) 😊 SENTIMENT ANALYSIS: • Positive: 8 tickets (20%) • Neutral: 22 tickets (55%) • Negative: 10 tickets (25%) ⚡ PRIORITY ACTIONS: • 4 complaints requiring immediate attention • 3 billing issues escalated to finance team • 6 feature requests for product backlog review 🎨 Customization Options Categories: Easily modify ticket categories for your specific business needs Form Platforms: Adapt to Google Forms, JotForm, Wufoo, or custom webhooks Reporting Frequency: Set daily, weekly, or real-time report delivery Team Notifications: Configure alerts for urgent tickets or negative sentiment Data Visualization: Create custom dashboards and charts in Google Sheets Integration Extensions: Connect to CRM, project management, or chat platforms 🔄 How It Works Customer submits support request via your form AI analyzes message content and assigns category + sentiment Data is automatically stored in organized Google Sheets System generates real-time analytics on all historical tickets Professional report is emailed to your support team Team can prioritize responses based on urgency and sentiment 💡 Use Case Examples SaaS Company: Automatically route billing questions to finance, bugs to development, and feature requests to product team E-commerce Store: Prioritize shipping complaints, categorize product questions, and track customer satisfaction trends Consulting Firm: Organize client requests by service type, monitor project-related issues, and ensure timely responses Healthcare Practice: Sort appointment requests, billing inquiries, and medical questions while maintaining HIPAA compliance 📈 Expected Results 80% reduction** in manual ticket sorting time 50% faster** initial response times through better prioritization 25% improvement** in customer satisfaction scores 100% visibility** into support trends and team performance Unlimited scalability** as your business grows 📞 Get Help & Learn More 🎥 Free Video Tutorials YouTube Channel: https://www.youtube.com/@YaronBeen/videos 💼 Professional Support LinkedIn: https://www.linkedin.com/in/yaronbeen/ Connect for implementation consulting Share your automation success stories Access exclusive templates and updates 📧 Direct Support Email: Yaron@nofluff.online Technical setup assistance Custom workflow modifications Integration with existing systems Response within 24 hours 🏆 Why Choose This Workflow Proven Results: Successfully deployed across 100+ businesses worldwide Expert Created: Built by automation specialist with 10+ years experience Continuously Updated: Regular improvements and new features added Money-Back Guarantee: Full refund if not satisfied within 30 days Lifetime Support: Ongoing help and updates included with purchase

How it works This template is a complete, hands-on tutorial for building a RAG (Retrieval-Augmented Generation) pipeline. In simple terms, you'll teach an AI to become an expert on a specific topic—in this case, the official n8n documentation—and then build a chatbot to ask it questions. Think of it like this: instead of a general-knowledge AI, you're building an expert librarian. The workflow is split into two main parts: Part 1: Indexing the Knowledge (Building the Library) This is a one-time process you run manually. The workflow automatically scrapes all the pages of the n8n documentation, breaks them down into small, digestible chunks, and uses an AI model to create a special numerical representation (an "embedding") for each chunk. These embeddings are then stored in your own private knowledge base (a Supabase vector store). This is like a librarian reading every book and creating a hyper-detailed index card for every paragraph. Part 2: The AI Agent (The Expert Librarian) This is the chat interface. When you ask a question, the AI agent doesn't guess the answer. Instead, it uses your question to find the most relevant "index cards" (chunks) from the knowledge base it just built. It then feeds these specific, relevant chunks to a powerful language model (like Gemini) with a strict instruction: "Answer the user's question using ONLY this information." This ensures the answers are accurate, factual, and grounded in your provided documents. Set up steps Setup time: ~15-20 minutes This is an advanced workflow that requires setting up a free external database. Follow these steps carefully. Set up Supabase (Your Knowledge Base): You need a free Supabase account. Follow the detailed instructions in the large Workflow Setup sticky notes in the top-right of the workflow to: Create a new Supabase project. Run the provided SQL query in the SQL Editor to prepare your database. Get your Project URL and Service Role Key. Configure n8n Credentials: In your n8n instance, create a new Supabase credential using the Project URL and Service Role Key from the previous step. Create a new Google AI credential with your Gemini API key. Configure the Workflow Nodes: Select your new Supabase credential in the three Supabase nodes: Your Supabase Vector Store, Official n8n Documentation and Keep Supabase Instance Alive. Select your new Google AI credential in the three Gemini nodes: Gemini Chunk Embedding, Gemini Query Embedding and Gemini 2.5 Flash. Build the Knowledge Base: Find the Start Indexing manual trigger node at the top-left. Click its "Execute workflow" button to start the indexing process. This will take several minutes as it scrapes and processes the entire n8n documentation. You only need to do this once. Chat with Your Expert Agent: Once the indexing is complete, Activate the entire workflow. Open the RAG Chatbot chat trigger node and copy its Public URL. Open the URL in a new tab and start asking questions about n8n! For example: "How does the IF node work?" or "What is a sub-workflow?".

AI Latest News Content Script Writer Overview This workflow automates the daily generation of viral short-form video content ideas tailored for founders and business leaders. It scrapes fresh AI-related news and trends from various topics, synthesizes the information, and then uses AI to craft complete content packages—including video scripts, captivating captions, and punchy text overlays. All generated content is saved to a Google Sheet, ready for your review and use. Use Case This workflow is perfect for: Founders & Entrepreneurs**: Consistently produce engaging content to build authority and attract inbound leads without a dedicated content team. AI Thought Leaders**: Stay on top of the latest AI news and effortlessly create shareable insights. Content Marketing Teams**: Automate the ideation and initial drafting phases for short-form video strategies. Agencies**: Offer a unique AI-powered content generation service to your clients. How It Works Scheduled Daily Trigger: The workflow runs automatically every day at 6 AM IST, ensuring you always have fresh content ideas to start your day. AI-Powered News Gathering: It uses Perplexity AI to fetch the latest, most interesting, and relevant stories across three key AI topics: Topic 1: General AI News Topic 2: AI Market and Industry Trends Topic 3: AI Business Automation Organize and Combine Content: The information from each topic is organized, and then all content and their respective citations are combined into a single, comprehensive input. Personalize "About Me": Crucially, a configurable "About me" node allows you to define the personal brand of the founder (e.g., Name, Niche, Business Name, Business Type). This context is fed to the AI to ensure generated content aligns perfectly with your persona and business objectives. Generate Content Packages: Leveraging OpenAI (acting as "CreatorAI"), the workflow takes the combined news and your "About me" information to: Identify a Unique Angle: Finds a distinct, engaging angle from the input that aligns with key content pillars (e.g., AI solving business pain points, future of work with AI). Craft Video Scripts: Generates concise video scripts (under 700 characters) with powerful hooks, mini-narratives (problem → AI solution → impact), and a focus on tangible business benefits. It subtly references your business as a thought leader, not a direct pitch. Write Captions: Creates friendly, expert-toned captions with engaging hooks, more context, a clear call to action (e.g., "Comment 'Workflow' for more"), and relevant hashtags. Design Text Overlays: Produces short, punchy text overlays (3-7 words, ALL CAPS or Title Case) perfect for video thumbnails or initial screens. Save to Google Sheet: Each generated content package (Text Overlay, Video Script, Caption) is appended as a new row in your designated Google Sheet ("Content Idea" sheet within "Video Automation (Vansh)"). Notify User: Finally, you'll receive an email notification confirming that new content ideas have been generated and saved to your Google Sheet. How to Set It Up To set up this AI Viral Content Generator, follow these steps: API Keys & Credentials: Perplexity AI API Key: Obtain your API key from Perplexity AI and replace the Bearer token in the "Topic 1", "Topic 2", and "Topic 3" HTTP Request nodes. OpenAI API Key: Connect your OpenAI API key in n8n and link it to the "Content Generation" node. Google Sheets Account: Ensure your Google Sheets OAuth2 API credentials are set up and connected to the "Save Data" node. Gmail Account: Connect your Gmail OAuth2 credentials to the "Notify user" node. Google Sheet Setup: Copy the Google Sheet Template provided. This template has predefined columns for "Text Overlay", "Video Script", "Caption", "Approval", and "Published". Update the documentId in the "Save Data" Google Sheets node with the ID of your copied template. Personalize "About me": Open the "About me" node. Fill in your Name, Niche, Business Name, Business Type, Website, and detailed Key Services & Products. This is crucial for the AI to generate relevant and personalized content. Configure Notification Email: In the "Notify user" node, update the sendTo field with your email address where you want to receive notifications. Set Schedule: The "Schedule Trigger" is set to run daily at 6 AM IST. You can adjust the time to your preference. Activate and Monitor: Activate the workflow. It will now automatically generate content ideas daily. Check your Google Sheet regularly to review the new content, mark it for approval, and track its publication status. This workflow is your secret weapon for consistently creating engaging, AI-driven short-form video content!

Overview An intelligent email automation workflow that revolutionizes how you handle email responses. This sophisticated system monitors your Gmail inbox, uses AI to determine which emails require replies, generates professional responses, and sends them only after your approval via Telegram. Perfect for busy professionals who want to maintain personalized communication while leveraging AI efficiency. 🌟 Key Features Intelligent Email Analysis Smart Detection**: Automatically identifies emails that genuinely need responses Context Understanding**: Distinguishes between promotional content, newsletters, and actionable emails Priority Filtering**: Focuses on emails with questions, requests, or time-sensitive matters AI-Powered Response Generation Professional Tone**: Maintains appropriate business communication standards Contextual Replies**: Generates responses based on email content and context Structured Output**: Creates properly formatted subject lines and email bodies Customizable Prompts**: Easily adjust AI behavior to match your communication style Human-in-the-Loop Approval Telegram Integration**: Review and approve responses directly from your mobile device Visual Preview**: See both original email and AI-generated response before sending Dual Approval System**: Approve or reject with simple Telegram buttons Timeout Protection**: Automatically expires after 5 minutes to prevent accidental sends 🔧 How It Works Workflow Architecture Email Monitoring: Continuous Gmail inbox surveillance (every minute) Inbox Filtering: Processes only emails in your main inbox folder AI Analysis: Determines response necessity using advanced language models Response Generation: Creates professional, contextual replies when needed Telegram Notification: Sends preview to your Telegram for approval Conditional Sending: Executes email send only upon your explicit approval Decision Logic The AI evaluates emails based on: Question Detection**: Identifies direct questions requiring answers Action Requests**: Recognizes requests for information or tasks Urgency Assessment**: Prioritizes time-sensitive communications Context Analysis**: Considers sender, subject, and content relevance 🚀 Setup Requirements Prerequisites Gmail Account**: With OAuth2 authentication enabled OpenAI API Key**: For AI language model access Telegram Bot**: Personal bot token and chat ID N8N Instance**: Cloud or self-hosted environment Required Credentials Gmail OAuth2 credentials OpenAI API authentication Telegram bot token and chat configuration 📊 Use Cases Business Applications Customer Support**: Automated responses to common inquiries Sales Teams**: Quick replies to prospect questions Account Management**: Timely responses to client communications HR Operations**: Efficient handling of employee inquiries Personal Productivity Email Management**: Reduce inbox overwhelm Professional Communication**: Maintain consistent response quality Time Management**: Focus on high-priority tasks while AI handles routine replies Mobile Workflow**: Approve emails anywhere via Telegram ⚙️ Customization Options AI Behavior Tuning Response Style**: Adjust tone from formal to casual Content Filters**: Modify email analysis criteria Response Length**: Control reply brevity or detail level Language Patterns**: Customize communication style Workflow Modifications Polling Frequency**: Adjust email checking intervals Approval Timeout**: Modify decision time limits Multi-Account Support**: Extend to multiple Gmail accounts Category Routing**: Different handling for different email types 🔒 Security & Privacy Data Protection Local Processing**: All email analysis occurs within your N8N instance No Data Storage**: Email content is not permanently stored Secure Authentication**: OAuth2 and API key protection Encrypted Communication**: Secure Telegram API integration Access Control Personal Approval**: You control every outgoing message Audit Trail**: Complete workflow execution logging Fail-Safe Design**: Defaults to no action if approval isn't received 📈 Performance & Reliability Efficiency Metrics Processing Speed**: Sub-second email analysis Accuracy**: High-quality response generation Reliability**: Robust error handling and retry mechanisms Scalability**: Handles high email volumes efficiently Resource Usage Lightweight Operation**: Minimal server resource consumption API Optimization**: Efficient OpenAI token usage Rate Limiting**: Respects Gmail and Telegram API limits 💡 Best Practices Optimization Tips Monitor AI Responses**: Regularly review and refine AI prompts Approval Patterns**: Establish consistent approval workflows Response Templates**: Create reusable response patterns Performance Monitoring**: Track workflow efficiency metrics Common Configurations Business Hours**: Limit processing to working hours VIP Senders**: Priority handling for important contacts Subject Filters**: Custom rules for specific email types Escalation Rules**: Forward complex emails to human review 🏆 Benefits Productivity Gains Time Savings**: Reduce manual email composition time by 60-80% Consistency**: Maintain professional communication standards Responsiveness**: Faster reply times improve customer satisfaction Focus**: Concentrate on high-value tasks while AI handles routine communications Professional Advantages Always Available**: Respond to emails even when busy Quality Assurance**: AI ensures grammatically correct, professional responses Scalability**: Handle increasing email volumes without proportional time investment Competitive Edge**: Faster response times improve business relationships Tags: Email Automation, AI Assistant, Gmail Integration, Telegram Bot, Workflow Automation, OpenAI, Business Productivity, Customer Service, Response Management, Professional Communication

This guide walks you through setting up an automated workflow that compares live flight fares across multiple booking platforms (e.g., Skyscanner, Akasa Air, Air India, IndiGo) using API calls, sorts the results by price, and sends the best deals via email. Ready to automate your flight fare comparison process? Let’s get started! What’s the Goal? Automatically fetch and compare live flight fares from multiple platforms using scheduled triggers. Aggregate and sort fare data to identify the best deals. Send the comparison results via email for review or action. Enable 24/7 fare monitoring with seamless integration. By the end, you’ll have a self-running system that delivers the cheapest flight options effortlessly. Why Does It Matter? Manual flight fare comparison is time-consuming and often misses the best deals. Here’s why this workflow is a game-changer: Zero Human Error**: Automated data fetching and sorting ensure accuracy. Time-Saving Automation**: Instantly compare fares across platforms, boosting efficiency. 24/7 Availability**: Monitor fares anytime without manual effort. Cost Optimization**: Focus on securing the best deals rather than searching manually. Think of it as your tireless flight fare assistant that always finds the best prices. How It Works Here’s the step-by-step magic behind the automation: Step 1: Trigger the Workflow Set Schedule Node**: Triggers the workflow at a predefined schedule to check flight fares automatically. Captures the timing for regular fare updates. Step 2: Process Input Data Set Input Data Node**: Sets the input parameters (e.g., origin, destination, departure date, return date) for flight searches. Prepares the data to be sent to various APIs. Step 3: Fetch Flight Data Skyscanner API Node**: Retrieves live flight fare data from Skyscanner using its API endpoint. Akasa Air API Node**: Fetches live flight fare data from Akasa Air using its API endpoint. Air India API Node**: Collects flight fare data directly from Air India’s API. IndiGo API Node**: Gathers flight fare data from IndiGo’s API. Step 4: Merge API Results Merge API Data Node**: Combines the flight data from Skyscanner and Akasa Air into a single dataset. Merge Both API Data Node**: Merges the data from Air India and IndiGo with the previous dataset. Merge All API Results Node**: Consolidates all API data into one unified result for further processing. Step 5: Analyze and Sort Compare Data and Sorting Price Node**: Compares all flight fares and sorts them by price to highlight the best deals. Step 6: Send Results Send Response via Email Node**: Sends the sorted flight fare comparison results to the user via email for review or action. How to Use the Workflow? Importing this workflow in n8n is a straightforward process that allows you to use this pre-built solution to save time. Below is a step-by-step guide to importing the Flight Fare Comparison Workflow in n8n. Steps to Import a Workflow in n8n Obtain the Workflow JSON Source the Workflow: The workflow is shared as a JSON file or code snippet (provided earlier or exported from another n8n instance). Format: Ensure you have the workflow in JSON format, either as a file (e.g., workflow.json) or copied text. Access the n8n Workflow Editor Log in to n8n: Open your n8n instance (via n8n Cloud or self-hosted). Navigate to Workflows: Go to the Workflows tab in the n8n dashboard. Open a New Workflow: Click Add Workflow to create a blank workflow. Import the Workflow Option 1: Import via JSON Code (Clipboard): In the n8n editor, click the three dots (⋯) in the top-right corner to open the menu. Select Import from Clipboard. Paste the JSON code (provided earlier) into the text box. Click Import to load the workflow. Option 2: Import via JSON File: In the n8n editor, click the three dots (⋯) in the top-right corner. Select Import from File. Choose the .json file from your computer. Click Open to import the workflow. Setup Notes API Credentials**: Configure each API node (Skyscanner, Akasa Air, Air India, IndiGo) with the respective API keys and endpoints. Check the API provider’s documentation for details. Email Integration**: Authorize the Send Response via Email node with your email service (e.g., Gmail SMTP settings or an email API like SendGrid). Input Customization**: Adjust the Set Input Data node to include specific origin/destination pairs and date ranges as needed. Schedule Configuration**: Set the desired frequency in the Set Schedule node (e.g., daily at 9 AM IST). Example Input Send a POST request to the workflow (if integrated with a webhook) with: { "origin": "DEL", "destination": "BOM", "departureDate": "2025-08-01", "returnDate": "2025-08-07" } Optimization Tips Error Handling**: Add IF nodes to manage API failures or rate limits. Rate Limits**: Include a Wait node if APIs have strict limits. Data Logging**: Add a node (e.g., Google Sheets) to log all comparisons for future analysis. This workflow transforms flight fare comparison into an automated, efficient process, delivering the best deals directly to your inbox!

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This n8n workflow automates invoice management by integrating Gmail, PDF analysis, and Azure OpenAI GPT-4.1, with an optional human verification step for accuracy and control. It's ideal for businesses or individuals who regularly receive invoice emails and want to streamline their accounts payable process with minimal manual effort. The system continuously monitors Gmail for new messages from specified senders. When it detects an email with a PDF attachment and relevant subject line (e.g., "Invoice"), it automatically extracts text from the PDF, analyzes it using Azure OpenAI, and determines if it is a valid invoice. If the AI is uncertain, the workflow sends a manual approval request to a human reviewer. Valid invoices are saved to local storage with a timestamped filename, and a confirmation email is sent upon successful processing. 🎯 Who This Is For Small to medium businesses Freelancers or consultants who receive invoices via email IT or automation teams looking to streamline document workflows Anyone using n8n with access to Gmail and Azure OpenAI ✅ Features Gmail Monitoring** – Automatically checks for new emails from trusted senders AI-Powered Invoice Detection** – Uses Azure GPT-4.1 to intelligently verify PDF contents PDF Text Extraction** – Extracts readable text for analysis Human-in-the-Loop Verification** – Requests approval when AI confidence is low Secure File Storag**e – Saves invoices locally with structured filenames Email Notifications** – Sends confirmations or manual review alerts ⚙️ Setup Instructions 1. Prerequisites An active n8n instance (self-hosted or cloud) A Gmail account with OAuth2 credentials An Azure OpenAI account with access to the GPT-4.1 model A local directory for saving invoices (e.g., C:/Test/Invoices/) 2. Gmail OAuth2 Setup In n8n, create Gmail OAuth2 credentials. Configure it with Gmail API access (read emails and attachments). Update the Gmail Trigger node to filter by sender email (e.g., sender@gmail.com). 3. Azure OpenAI Setup Create Azure OpenAI API credentials in n8n. Ensure your endpoint is correctly set and GPT-4.1 access is enabled. Link the credentials in the AI Analysis node. 4. Customize Workflow Settings Sender Email – Update in Gmail Trigger Notification Email – Update in Send Notification node Save Directory – Change in Save Invoice node 5. Testing the Workflow Send a test email from the configured sender with a PDF invoice. Wait for the workflow to trigger and check for: File saved in the directory Confirmation email received Manual review request (if needed) 🔄 Workflow Steps Gmail Trigger → Check for PDF Invoice → Extract PDF Text → Analyze with GPT-4.1 → ↳ If Invoice: Save & Notify ↳ If Uncertain: Request Human Review ↳ If Not Invoice: Send Invalid Alert

This n8n workflow automates the collection, enrichment, and analysis of e-commerce product listings using Bright Data and AI, then delivers an HTML email report with the most competitive offers. 🚀 What It Does Pulls product titles from a Google Sheet. For each product, searches a Bright Data marketplace dataset (Google Shopping) for available listings. Extracts relevant fields: price, title, seller name, and listing URL. Sends this data to Google Gemini for AI-powered Markdown report generation. Converts Markdown to HTML and styles the output for better email rendering. Sends an email report for each product with the top 20 most affordable offers. 🛠️ Step-by-Step Setup Load product list from Google Sheets. For each product title, run a Bright Data filter request (case-sensitive match). Poll the snapshot status until it is ready. Retrieve snapshot content and clean the results with a Code node. Pass the results to Gemini (PaLM/Gemini Flash) for analysis and report generation in Markdown. Convert Markdown into styled HTML using Markdown + Code nodes. Send formatted email to a predefined recipient. Return to the loop and repeat for the next product. 🧠 How It Works Loop Control: SplitInBatches handles product-by-product processing. Snapshot Handling: Snapshot status is polled every 30s until success/failure. AI Formatting: Gemini summarizes listings and formats content. Error Handling: Failed snapshots produce a warning message and resume the loop. 📨 Final Output Each email contains: The product name A clean HTML of up to 20 sellers with lowest prices Links to listings AI-generated pricing summary 🔐 Credentials Used Bright Data account Google Gemini (PaLM/Gemini Flash) Google Sheets (OAuth2) SMTP Email (emailSend node) ⚠️ Important Notes Item title search is case-sensitive. Typos or casing mismatches may result in no results. Requires n8n-nodes-brightdata community node to be installed.