Workflow Templates

This n8n template demonstrates how to audit your brand’s visibility across multiple AI systems and automatically log the results to Google Sheets. It sends the same prompt to OpenAI, Perplexity, and (optionally) a ChatGPT web actor, then runs sentiment and brand-hierarchy analysis on the responses. Use cases are many: benchmark how often (and how positively) your brand appears in AI answers, compare responses across models, and build a repeatable “AI visibility” report for marketing and comms teams. 💡 Good to know You’ll bring your own API keys for OpenAI and Perplexity. Usage costs depend on your providers’ pricing. The optional APIfy actor automates the ChatGPT web UI and may violate terms of service. Use strictly at your own risk. ⁉ How it works A Manual Trigger starts the workflow (you can replace it with any trigger). Input prompts are read from a Google Sheet (or you can use the included “manual input” node). The prompt is sent to three tools: -- OpenAI (via API) to check baseline LLM knowledge. -- Perplexity (API) to retrieve an answer with citations. -- Optionally, an APIfy actor that scrapes a ChatGPT response (web interface). Responses are normalized and mapped (including citations where available). An LLM-powered sentiment pass classifies each response into: -- Basic Polarity: Positive, Neutral, or Negative -- Emotion Category: Joy, Sadness, Anger, Fear, Disgust, or Surprise -- Brand Hierarchy: ordered list such as Nike>Adidas>Puma The consolidated record (Prompt, LLM, Response, Brand mentioned flag, Brand Hierarchy, Basic Polarity, Emotion Category, Source 1–3/4) is appended to your “Output many models” Google Sheet. A simplified branch shows how to take a single response and push it to a separate sheet. 🗺️ How to use Connect your Google Sheets OAuth and create two tabs: -- Input: a single “Prompt” column -- Output: columns for Prompt, LLM, Response, Brand mentioned, Brand Hierarchy, Basic Polarity, Emotion Category, Source 1, Source 2, Source 3, Source 4 Add your OpenAI and Perplexity credentials. (Optional) Add an APIfy credential (Query Auth with token) if you want the ChatGPT web actor path. Run the Manual Trigger to process prompts in batches and write results to Sheets. Adjust the included “Limit for testing” node or remove it to process more rows. ⚒️ Requirements OpenAI API access (e.g., GPT-4.1-mini / GPT-5 as configured in the template) Perplexity API access (model: sonar) Google Sheets account with OAuth connected in n8n (Optional) APIfy account/token for the ChatGPT web actor 🎨 Customising this workflow Swap the Manual Trigger for a webhook or schedule to run audits automatically. Extend the sentiment analyzer instructions to include brand-specific rules or compliance checks. Track more sources (e.g., additional models or vertical search tools) by duplicating the request→map→append pattern. Add scoring (e.g., “visibility score” per prompt) and charts by pointing the output sheet into Looker Studio or a BI tool.

Automated Weekly Newsletter with AI Research, Editorial Drafting, and Approval Flow This n8n template demonstrates how to automate the full production cycle of a professional weekly newsletter. It combines AI-powered market research, editorial drafting, compliance validation, and an approval loop — all before creating a final Gmail draft ready for distribution. Use cases are many: Wealth managers sending weekly market updates to clients Startups producing recurring research digests Teams creating automated newsletters for marketing or content distribution Good to know At time of writing, each AI call (research, editorial, QC) consumes API tokens from Perplexity and OpenAI. See provider pricing for updated info. Gmail integration requires OAuth setup with your account. You can adapt the prompts to any domain — from finance to tech to education. How it works Schedule Trigger runs every week and sets the date window. Research LLM fetches structured JSON market data using Perplexity. Editorial LLM transforms research into a polished ~2,000 word client-ready newsletter. QC LLM validates factual accuracy and compliance risks before approval. Preview Email is sent with Approve/Revise buttons. Clicking opens a secure n8n-hosted approval form. Final Draft Creation: Once approved, the workflow generates a clean Gmail draft, ready to send. How to use Replace the demo schedule trigger with your own (weekly, daily, or event-based). Set up Gmail OAuth credentials to enable email previews and final drafts. Update branding (logo, disclaimer, signature) in the HTML builder node. Adjust prompts to your audience — e.g., simplify tone for marketing, or keep institutional tone for financial clients. Requirements Perplexity account for research API (or your LLM of choice) OpenAI for editorial and QC steps (or your LLM of choice) Gmail account with OAuth credentials Optional: your own domain to host the approval webhook Customising this workflow This workflow can be extended beyond financial newsletters. Try: Content marketing: Automate weekly digests or trend reports Education: Generate curriculum summaries with approval loops for teachers Internal comms: Automate compliance-checked company updates

Who this is for This workflow is designed for teams that collect feedback or survey responses via Jotform and want to automatically: Analyze sentiment (positive, neutral, negative) of each response. Extract key topics and keywords from qualitative text. Generate AI summaries and structured insights. Store results in Google Sheets and n8n DataTables for easy reporting and analysis. Use Cases Customer experience analysis Market research & survey analysis Product feedback clustering Support ticket prioritization AI-powered blog or insight generation from feedback What this workflow does This n8n automation connects Jotform, Google Gemini, and Google Sheets to turn raw responses into structured insights with sentiment, topics, and keywords. Pipeline Overview Jotform → Webhook → Gemini (Topics + Keywords) → Gemini (Sentiment) → Output Parser → Merge → Google Sheets Jotform Trigger Captures each new submission from your Jotform (e.g., a feedback or survey form). Extracts raw fields ($json.body.pretty) such as name, email, and response text. Format Form Data (Code Node) Converts the Jotform JSON structure into a clean string for AI input. Ensures the text is readable and consistent for Gemini. Topics & Keyword Extraction (Google Gemini + Output Parser) Goal: Identify the main themes and important keywords from responses. { "topics": [ { "topic": "Product Features", "summary": "Users request more automation templates.", "keywords": ["AI templates", "automation", "workflow"], "sentiment": "positive", "importance_score": 0.87 } ], "global_keywords": ["AI automation", "developer tools"], "insights": ["Developers desire more creative, ready-to-use AI templates."], "generated_at": "2025-10-08T10:30:00Z" } Sentiment Analyzer (Google Gemini + Output Parser) Goal: Evaluate overall emotional tone and priority. { "customer_name": "Ranjan Dailata", "customer_email": "ranjancse@gmail.com", "feedback_text": "Please build more interesting AI automation templates.", "sentiment": "positive", "confidence_score": 0.92, "key_phrases": ["AI automation templates", "developer enablement"], "summary": "Customer requests more AI automation templates to boost developer productivity.", "alert_priority": "medium", "timestamp": "2025-10-08T10:30:00Z" } Merge + Aggregate Combines the topic/keyword extraction and sentiment output into a single structured dataset. Aggregates both results for unified reporting. Persist Results (Google Sheets) Writes combined output into your connected Google Sheet. Two columns recommended: feedback_analysis → Sentiment + Summary JSON topics_keywords → Extracted Topics + Keywords JSON Enables easy visualization, filtering, and reporting. Visualization (Optional) Add Sticky Notes or a logo image node in your workflow to: Visually describe sections (e.g., “Sentiment Analysis”, “Topic Extraction”). Embed brand logo: Example AI Output (Combined) { "feedback_analysis": { "customer_name": "Ranjan Dailata", "sentiment": "positive", "summary": "User appreciates current templates and suggests building more advanced AI automations.", "key_phrases": ["AI automation", "developer templates"] }, "topics_keywords": { "topics": [ { "topic": "AI Template Expansion", "keywords": ["AI automation", "workflow templates"], "sentiment": "positive", "importance_score": 0.9 } ], "global_keywords": ["automation", "AI development"] } } Setup Instructions Pre-requisite If you are new to Jotform, Please do signup using Jotform Signup For the purpose of demonstation, we are considering the Jotforms Prebuilt New Customer Registration Form as a example. However, you are free to consider for any of the form submissions. Step 0: Local n8n (Optional) If using local n8n, set up ngrok: ngrok http 5678 Use the generated public URL as your Webhook URL base for Jotform integration. Step 1: Configure the Webhook Copy the Webhook URL generated by n8n (e.g., /webhook-test/f3c34cda-d603-4923-883b-500576200322). You can copy the URL by double clicking on the Webhook node. Make sure to replace the base url with the above Step 0, if you are running the workflow from your local machine. In Jotform, go to your form → Settings → Integrations → Webhooks → paste this URL. Now, every new form submission will trigger the n8n workflow. Step 2: Connect Google Gemini Create a Google Gemini API Credential in n8n. Select the model models/gemini-2.0-flash-exp. Step 3: Create Data Storage Create a DataTable named JotformFeedbackInsights with columns: feedback_analysis (string) topics_keywords (string) Step 4: Connect Google Sheets Add credentials under Google Sheets OAuth2. Link to your feedback tracking sheet. Step 5: Test the Workflow Submit a form via Jotform. Check results: AI nodes return structured JSON. Google Sheet updates with new records. Customization Tips Change the Prompt You can modify the topic extraction prompt to highlight specific themes: You are a research analyst. Extract main topics, keywords, and actionable insights from this feedback: {{ $json.body }} Extend the Output Schema Add more fields like: { "suggested_blog_title": "", "tone": "", "recommendations": [] } Then update your DataTable or Sheets schema accordingly. Integration Ideas Send sentiment alerts to Slack for high-priority feedback. Push insights into Notion, Airtable, or HubSpot. Generate weekly reports summarizing trends across all submissions. Summary This workflow turns raw Jotform submissions into actionable insights using Google Gemini AI — extracting topics, keywords, and sentiment while automatically logging everything to Google Sheets.

Automated SSL/TLS Certificate Expiry Report for AWS > Automatically generates a weekly report of all AWS ACM certificates, including status, expiry dates, and renewal eligibility. The workflow formats the data into both Markdown (for PDF export to Slack) and HTML (for email summary), helping teams stay on top of certificate compliance and expiration risks. Who’s it for This workflow is designed for DevOps engineers, cloud administrators, and compliance teams who manage AWS infrastructure and need automated weekly visibility into the status of their SSL/TLS certificates in AWS Certificate Manager (ACM). It's ideal for teams that want to reduce the risk of expired certs, track renewal eligibility, and maintain reporting for audit or operational purposes. How it works / What it does This n8n workflow performs the following actions on a weekly schedule: Trigger: Automatically runs once a week using the Weekly schedule trigger. Fetch Certificates: Uses Get many certificates action from AWS Certificate Manager to retrieve all certificate records. Parse Data: Processes and reformats certificate data (dates, booleans, SANs, etc.) into a clean JSON object. Generate Reports: 📄 Markdown Report: Uses the Certificate Summary Markdown Agent (OpenAI) to generate a Markdown report for PDF export. 🌐 HTML Report: Uses the Certificate Summary HTML Agent to generate a styled HTML report for email. Deliver Reports: Converts Markdown to PDF and sends it to Slack as a file. Sends HTML content as a formatted email. How to set up Configure AWS Credentials in n8n to allow access to AWS ACM. Create a new workflow and use the following nodes in sequence: Schedule Trigger: Weekly (e.g., every Monday at 08:00 UTC) AWS ACM → Get many certificates Function Node → Parse ACM Data: Converts and summarizes certificate metadata OpenAI Chat Node (Markdown Agent) with a system/user prompt to generate Markdown Configure Metadata → Define file name and MIME type (.md) Create document file → Converts Markdown to document stream Convert to PDF Slack Node → Upload the PDF to a channel (Optional) Add a second OpenAI Chat Node for generating HTML and sending it via email Connect Output: Markdown report → Slack file upload HTML report → Email node with embedded HTML Requirements 🟩 n8n instance (self-hosted or cloud) 🟦 AWS account with access to ACM 🟨 OpenAI API key (for ChatGPT Agent) 🟥 Slack webhook or OAuth credentials (for file upload) 📧 Email integration (e.g., SMTP or SendGrid) 📝 Permissions to write documents (Google Drive / file node) How to customize the workflow Change report frequency**: Adjust the Weekly schedule trigger to daily or monthly as needed. Filter certificates**: Modify the function node to only include EXPIRED, IN_USE, or INELIGIBLE certs. Add tags or domains to include/exclude. Add visuals**: Enhance the HTML version with colored rows, icons, or company branding. Change delivery channels**: Replace Slack with Microsoft Teams, Discord, or Telegram. Send Markdown as email attachment instead of PDF. Integrate ticketing**: Create a JIRA/GitHub issue for each certificate that is EXPIRED or INELIGIBLE.

This n8n template demonstrates how to build O'Carla, an advanced all-in-one Discord AI assistant. It intelligently handles natural conversations, professional image generation, and visual file analysis within a single server integration. Use cases are many: Deploy a smart community manager that remembers past interactions, an on-demand artistic tool for your members, or an AI that can "read" and explain uploaded documents and images! Good to know API Costs:** Each interaction costs vary depending on the model used (Gemini vs. OpenRouter). Check your provider's dashboard for updated pricing. Infrastructure:* This workflow requires a separate Discord bot script (e.g., Node.js) to forward events to the n8n Webhook. It is recommended to host the bot using *PM2** for 24/7 uptime. How it works Webhook Trigger: Receives incoming data (text and attachments) from your Discord bot. Intent Routing: The workflow uses conditional logic to detect if the user wants an image (via keyword gambar:), a vision analysis (via attachments), or a standard chat. Multi-Model Intelligence: Gemini 2.5: Powers rapid and high-quality general chat reasoning. Llama 3.2 Vision (via OpenRouter): Specifically used to describe and analyze images or text-based files. Flux (via Pollinations): Uses a specialized AI Agent to refine prompts and generate professional-grade images. Contextual Memory: A 50-message buffer window ensures O'Carla maintains the context of your conversation based on your Discord User ID. Clean UI Output: Generated image links are automatically shortened via TinyURL to keep the Discord chat interface tidy. How to use Connect your Google Gemini and OpenRouter API keys in the respective nodes. Replace the Webhook URL in your bot script with this workflow's Production Webhook URL. Type gambar: [your prompt] in Discord to generate images. Upload an image or file to Discord to trigger the AI Vision analysis. Requirements n8n instance (Self-hosted or Cloud). Google Gemini API Key. OpenRouter API Key. Discord Bot Token and hosting environment. Customising this workflow O'Carla is highly flexible. You can change her personality by modifying the System Message in the Agent nodes, adjust the memory window length, or swap the LLM models to specialized ones like Claude 3.5 or GPT-4o.

Introduction Automates travel planning by aggregating flights, hotels, activities, and weather via APIs, then uses AI to generate professional itineraries delivered through Gmail and Slack. How It Works Webhook receives requests, searches APIs (Skyscanner, Booking.com, Kiwi, Viator, weather), merges data, AI builds itineraries, scores options, generates HTML emails, delivers via Gmail/Slack. Workflow Template Webhook → Extract → Parallel Searches (Flights/Hotels/Activities/Weather) → Merge → Build Itinerary → AI Processing → Score → Generate HTML → Gmail → Slack → Response Workflow Steps Trigger & Extract: Receives destination, dates, preferences, extracts parameters. Data Gathering: Parallel APIs fetch flights, hotels, activities, weather, merges responses. AI Processing: Analyzes data, creates itinerary, ranks recommendations. Delivery: Generates HTML email, sends via Gmail/Slack, confirms completion. Setup Instructions API Configuration: Add keys for Skyscanner, Booking.com, Kiwi, Viator, OpenWeatherMap, OpenRouter. Communication: Connect Gmail OAuth2, Slack webhook. Customization: Adjust endpoints, AI prompts, HTML template, scoring criteria. Prerequisites API keys: Skyscanner, Booking.com, Kiwi, Viator, OpenWeatherMap, OpenRouter Gmail account Slack workspace n8n instance Use Cases Corporate travel planning Vacation itinerary generation Group trip coordination Customization Add sources (Airbnb, TripAdvisor) Filter by budget preferences Add PDF generation Customize Slack format Benefits Saves 3-5 hours per trip Real-time pricing aggregation AI-powered personalization Automated multi-channel delivery

Wikipedia to LinkedIn AI Content Poster with Image via Bright Data 📋 Overview Workflow Description: Automatically scrapes Wikipedia articles, generates AI-powered LinkedIn summaries with custom images, and posts professional content to LinkedIn using Bright Data extraction and intelligent content optimization. 🚀 How It Works The workflow follows these simple steps: Article Input: User submits a Wikipedia article name through a simple form interface Data Extraction: Bright Data scrapes the Wikipedia article content including title and full text AI Summarization: Advanced AI models (OpenAI GPT-4 or Claude) create professional LinkedIn-optimized summaries under 2000 characters Image Generation: Ideogram AI creates relevant visual content based on the article summary LinkedIn Publishing: Automatically posts the summary with generated image to your LinkedIn profile URL Generation: Provides a shareable LinkedIn post URL for easy access and sharing ⚡ Setup Requirements Estimated Setup Time: 10-15 minutes Prerequisites n8n instance (self-hosted or cloud) Bright Data account with Wikipedia dataset access OpenAI API account (for GPT-4 access) Anthropic API account (for Claude access - optional) Ideogram AI account (for image generation) LinkedIn account with API access 🔧 Configuration Steps Step 1: Import Workflow Copy the provided JSON workflow file In n8n: Navigate to Workflows → + Add workflow → Import from JSON Paste the JSON content and click Import Save the workflow with a descriptive name Step 2: Configure API Credentials 🌐 Bright Data Setup Go to Credentials → + Add credential → Bright Data API Enter your Bright Data API token Replace BRIGHT_DATA_API_KEY in all HTTP request nodes Test the connection to ensure access 🤖 OpenAI Setup Configure OpenAI credentials in n8n Ensure GPT-4 model access Link credentials to the "OpenAI Chat Model" node Test API connectivity 🎨 Ideogram AI Setup Obtain Ideogram AI API key Replace IDEOGRAM_API_KEY in the "Image Generate" node Configure image generation parameters Test image generation functionality 💼 LinkedIn Setup Set up LinkedIn OAuth2 credentials in n8n Replace LINKEDIN_PROFILE_ID with your profile ID Configure posting permissions Test posting functionality Step 3: Configure Workflow Parameters Update Node Settings: Form Trigger:** Customize the form title and field labels as needed AI Agent:** Adjust the system message for different content styles Image Generate:** Modify image resolution and rendering speed settings LinkedIn Post:** Configure additional fields like hashtags or mentions Step 4: Test the Workflow Testing Recommendations: Start with a simple Wikipedia article (e.g., "Artificial Intelligence") Monitor each node execution for errors Verify the generated summary quality Check image generation and LinkedIn posting Confirm the final LinkedIn URL generation 🎯 Usage Instructions Running the Workflow Access the Form: Use the generated webhook URL to access the submission form Enter Article Name: Type the exact Wikipedia article title you want to process Submit Request: Click submit to start the automated process Monitor Progress: Check the n8n execution log for real-time progress View Results: The workflow will return a LinkedIn post URL upon completion Expected Output 📝 Content Summary Professional LinkedIn-optimized text Under 2000 characters Engaging and informative tone Bullet points for readability 🖼️ Generated Image High-quality AI-generated visual 1280x704 resolution Relevant to article content Professional appearance 🔗 LinkedIn Post Published to your LinkedIn profile Includes both text and image Shareable public URL Professional formatting 🛠️ Customization Options Content Personalization AI Prompts:** Modify the system message in the AI Agent node to change writing style Character Limits:** Adjust summary length requirements Tone Settings:** Change from professional to casual or technical Hashtag Integration:** Add relevant hashtags to LinkedIn posts Visual Customization Image Style:** Modify Ideogram prompts for different visual styles Resolution:** Change image dimensions based on LinkedIn requirements Rendering Speed:** Balance between speed and quality Brand Elements:** Include company logos or brand colors 🔍 Troubleshooting Common Issues & Solutions ⚠️ Bright Data Connection Issues Verify API key is correctly configured Check dataset access permissions Ensure sufficient API credits Validate Wikipedia article exists 🤖 AI Processing Errors Check OpenAI API quotas and limits Verify model access permissions Review input text length and format Test with simpler article content 🖼️ Image Generation Failures Validate Ideogram API key Check image prompt content Verify API usage limits Test with shorter prompts 💼 LinkedIn Posting Issues Re-authenticate LinkedIn OAuth Check posting permissions Verify profile ID configuration Test with shorter content ⚡ Performance & Limitations Expected Processing Times Wikipedia Scraping:** 30-60 seconds AI Summarization:** 15-30 seconds Image Generation:** 45-90 seconds LinkedIn Posting:** 10-15 seconds Total Workflow:** 2-4 minutes per article Usage Recommendations Best Practices: Use well-known Wikipedia articles for better results Monitor API usage across all services Test content quality before bulk processing Respect LinkedIn posting frequency limits Keep backup of successful configurations 📊 Use Cases 📚 Educational Content Create engaging educational posts from Wikipedia articles on science, history, or technology topics. 🏢 Thought Leadership Transform complex topics into accessible LinkedIn content to establish industry expertise. 📰 Content Marketing Generate regular, informative posts to maintain active LinkedIn presence with minimal effort. 🔬 Research Sharing Quickly summarize and share research findings or scientific discoveries with your network. 🎉 Conclusion This workflow provides a powerful, automated solution for creating professional LinkedIn content from Wikipedia articles. By combining web scraping, AI summarization, image generation, and social media posting, you can maintain an active and engaging LinkedIn presence with minimal manual effort. The workflow is designed to be flexible and customizable, allowing you to adapt the content style, visual elements, and posting frequency to match your professional brand and audience preferences. For any questions or support, please contact: info@incrementors.com or fill out this form: https://www.incrementors.com/contact-us/

Sona-Powered AI Sales Research & Personalized Email Automation 🎯 Overview Transform cold outreach from hours to minutes with AI-powered lead research and personalized email generation. This workflow combines Sona's B2B company intelligence with GPT-4 to automatically research prospects, identify pain points, and generate hyper-personalized cold emails—all synced to Google Sheets. ✨ What This Workflow Does Smart Lead Processing - Reads leads from Google Sheets and filters unprocessed contacts Deep Company Intelligence - Enriches each lead using Sona's API (industry, tech stack, revenue, employee count, social profiles) AI-Powered Research - GPT-4 analyzes company data to identify pain points, growth opportunities, and personalization hooks Email Generation - Creates 120-150 word personalized emails with curiosity-driven subject lines Automated Sync - Updates Google Sheets with research insights and one-click Gmail compose links 🔥 Key Features 5-Tier Smart Matching** - Proprietary algorithm matches leads to Sona's database with 95%+ accuracy Structured AI Output** - Consistent, high-quality research and email copy every time Zero Manual Work** - Processes 20-50 leads per hour completely hands-free Gmail Integration** - Pre-filled send links for instant outreach Progress Tracking** - Real-time status updates in Google Sheets 💼 Perfect For Sales teams doing cold outreach SDRs needing personalized emails at scale Agencies managing client prospecting Founders building their pipeline 📋 What You'll Need 1. Sona API Key Get yours at sonalabs.com Provides company data enrichment Add to HTTP Request node header: x-api-key: YOUR_KEY 2. OpenAI API Key Get from platform.openai.com Uses GPT-4.1-mini for research and email generation Add credentials in n8n 3. Google Sheets Setup Create a spreadsheet with these columns: Input columns:** Website Domain, Company Name, Contact Name, Email, Industry Status column:** Research Status (leave empty for new leads) Auto-populated:** Pain Points, Key Insight, Email Subject, Email Body, Send Email Link, Generated Date, Sent Status 4. Google Sheets API Enable in Google Cloud Console Set up OAuth2 with spreadsheets permission Add your spreadsheet ID to workflow nodes 🚀 Setup Instructions Import workflow into n8n Add credentials: Sona API key (HTTP Request node) OpenAI API credentials Google Sheets OAuth2 Update spreadsheet ID in all Google Sheets nodes Customize AI prompts (optional) to match your offering Test with 2-3 leads before running full list Execute workflow - it processes leads automatically in batches 📊 Expected Output Each processed lead gets: Pain points** (3-5 identified challenges) Growth opportunities** (2-3 actionable insights) Personalization hooks** (3-4 talking points) Email subject line** (max 8 words, curiosity-driven) Email body** (120-150 words, consultative tone) Gmail compose link** (one-click to send) Fit score** (High/Medium/Low) Processing time: 30-60 seconds per lead 🎓 How It Works Step 1: Data Input & Filtering Reads all leads from Google Sheets and filters out already-processed leads (those with a value in "Research Status" column). Step 2: Company Data Enrichment Updates status to "Pending" in Google Sheets Searches Sona database using domain or email 5-tier smart matching algorithm finds best company match Retrieves firmographic data and technology stack Step 3: AI Company Research GPT-4.1-mini analyzes company data to generate: Specific pain points based on industry, size, tech stack Growth opportunities and market positioning Personalization hooks from company description Recommended outreach tone and CTA One-liner insight for email opening Step 4: Personalized Email Generation AI crafts cold email following best practices: Curiosity-driven subject line (max 8 words) Opens with personalization hook showing research References ONE specific pain point Focuses on tangible outcomes (not product features) Natural CTA without being pushy Professional but conversational tone Step 5: Data Output & Loop Formats all data for Google Sheets Creates Gmail compose link with pre-filled content Updates sheet with complete results Sets status to "Completed" Waits 2 seconds, then processes next lead ⚡ Pro Tips Start small:** Test with 5-10 leads to validate personalization quality Review first emails:** Adjust AI prompts if tone needs calibration Clean your data:** Better input domains = better Sona matches Monitor fit scores:** Focus manual review on High/Medium fits Use status column:** Easily re-run workflow for new leads only Connect CRM:** Use webhooks to push data to Salesforce/HubSpot 🎯 Use Cases Sales Team Automation Process 100+ leads overnight with personalized research and emails ready by morning. Agency Client Work Deliver custom prospecting campaigns with unique emails for each client's target accounts. Founder Outreach Build pipeline systematically with AI-researched, personalized emails at scale. SDR Productivity Give SDRs pre-researched talking points and draft emails to speed up their workflow 10x. 📈 Expected Results Email personalization:** 10x better than templates Time saved:** 5-10 minutes per lead → 30 seconds automated Response rates:** 2-3x higher with AI-researched insights Scalability:** Process 50-100 leads per day hands-free 🔧 Customization Options Change AI model:** Swap GPT-4.1-mini for GPT-4 or other models Adjust email length:** Modify prompt to generate shorter/longer emails Add more enrichment:** Chain additional API calls (Clearbit, Apollo, etc.) Multi-language:** Update prompts for outreach in other languages Custom tone:** Adjust system prompts for industry-specific voice Webhook triggers:** Replace manual trigger with scheduled runs or form submissions 🐛 Troubleshooting No Sona data found? Verify API key is correct Check domain format (remove http://, trailing slashes) Fallback uses first search result if no exact match AI output not formatted correctly? Structured Output Parser ensures valid JSON Check OpenAI API key and model availability Google Sheets not updating? Verify OAuth2 credentials are connected Check spreadsheet ID matches your sheet Ensure column names match exactly (case-sensitive) Rate limits? Sona: 3 second delay between requests (built-in) OpenAI: Adjust batch size or add longer waits Google Sheets: No limit for standard usage 📝 Template Information Category:** Sales & Marketing Difficulty:** Intermediate Setup Time:** 5-10 minutes Run Time:** 30-60 seconds per lead Cost:** Pay-per-use (Sona API + OpenAI tokens) Updated:** December 2025

Who's it for Content creators, trainers, and educators who need to convert lengthy documents into digestible micro-learning experiences. How it works This workflow takes your source content (PDFs, articles, handbooks) and uses GPT-4 to intelligently break it into 2-3 minute learning modules. Each module includes a key concept, explanation, practical example, and knowledge check question. How to set up Configure OpenAI credentials with GPT-4 access Connect Slack workspace (optional) Set up Google Docs integration Optionally, Send content via webhook or paste directly Requirements OpenAI API key with GPT-4 access Google Docs account (for document creation) Slack workspace (optional, for notifications) How to customize the workflow Adjust module count and length in AI prompts Modify output formats (email, mobile, Slack) Change document structure and styling Add custom delivery channels Perfect for converting employee handbooks, training materials, and documentation into engaging micro-learning courses that people actually complete.

🔧 AI-Powered Auto-Maintenance System for n8n Transform your n8n instance management with this advanced automation system featuring artificial intelligence-driven workflow selection. This template provides comprehensive maintenance operations with smart filtering capabilities. ✨ Key Features 🤖 Artificial Intelligence Engine Multi-criteria scoring system for intelligent workflow selection Semantic analysis for business-critical pattern recognition Automated decision-making with configurable thresholds 🎯 Core Maintenance Operations Security Audits**: Automated vulnerability scanning with Google Sheets reporting Smart Pause/Resume**: Intelligent workflow suspension during maintenance windows AI Backup Creation**: Selective duplication of high-value workflows Intelligent Export**: Comprehensive system backups with metadata 🔐 Enterprise Security Token-based authentication with request validation Protected workflow safeguards (never modifies critical systems) Comprehensive error handling and logging ⚡ Automation & Scheduling Configurable maintenance schedules (daily, weekly, monthly) Webhook-driven operations for external integration Real-time monitoring and statistics 🎯 Perfect For DevOps Teams**: Streamline n8n maintenance operations Enterprise Users**: Manage large-scale workflow environments System Administrators**: Automated security and backup management Advanced Users**: Leverage AI for intelligent workflow management 🚀 Quick Setup Import the template Configure 4 credentials (n8n API, Google Sheets, Google Drive, Webhook Auth) Set your security token and Google Sheet ID Activate and enjoy automated maintenance! 🧠 AI Intelligence Highlights The system evaluates workflows using 6+ criteria including activity status, complexity, priority tags, business criticality, and recent updates. Workflows are automatically scored and selected based on intelligent thresholds. Selection Logic: Duplicate threshold: ≥3 points (smart backup selection) Export threshold: ≥5 points (comprehensive backup) System workflows always protected 📊 Includes 25+ configured nodes with emoji naming 4 detailed markdown documentation cards Pre-configured schedules and examples Comprehensive error handling Statistical reporting and monitoring Perfect for organizations looking to implement intelligent, automated n8n maintenance with minimal manual intervention.

About This Template This workflow automatically generates and sends AI-powered responses to user inquiries from a LINE Official Account. It uses RAG (Retrieval-Augmented Generation) technology to produce natural, context-aware answers based on your FAQ database (Supabase/PostgreSQL). How It Works Receive Questions: An n8n webhook receives messages from your LINE Official Account. FAQ Search: The n8n LangChain Agent analyzes the user’s question and performs a vector search on your Supabase FAQ database. It can also fetch user-specific data (e.g., reservation info) from PostgreSQL. AI Generation: The OpenAI GPT model generates a context-aware answer based on the retrieved information and conversation history. Reply: The response is sent back to the user via the LINE Messaging API. Admin Notifications: (Optional) If the AI cannot answer, the workflow can notify admins (e.g., via LINE WORKS or Slack). Who It’s For Businesses wanting to automate customer support on LINE. Developers building intelligent chatbots with existing FAQ data. Organizations aiming for 24/7 customer service. Requirements An n8n account (cloud or self-hosted) An OpenAI API key A Supabase account (for FAQ data) A PostgreSQL database (for conversation history) A LINE Official Account & Messaging API access token Setup Steps Configure Credentials: Register credentials for OpenAI, Supabase, PostgreSQL, and LINE Messaging API in n8n. Prepare Databases: Create your tables in Supabase (for FAQs) and PostgreSQL (for conversation history). Customize the Prompt: In the "RAG AI Agent" node, edit the system prompt to fit your business and tone. Set Environment Variables: Update URLs, Channel IDs, and API endpoints in the nodes to match your environment. Customization Options Change AI Model:** Select a different model (e.g., gpt-4o) in the "OpenAI Chat Model" node. Add Data Sources:** Add new "Tool" nodes (like an HTTP Request) to the "RAG AI Agent" to access other APIs (e.g., booking systems). Change Notifications:** Replace the "LINE Works" nodes with a Slack or Email node to change the admin notification channel.

Description Automatically capture customer onboarding help requests from Typeform, log them in Google Sheets, validate email addresses, and send a professional HTML welcome email via Gmail. Ensures smooth onboarding communication with audit-ready tracking and error handling. 📝📧 What This Template Does Monitors Typeform submissions for new onboarding help requests. 📥 Logs all responses into Google Sheets with structured fields. 📊 Validates email addresses to prevent errors. ✅ Generates professional HTML welcome emails with company branding. 🎨 Sends onboarding emails directly via Gmail. 📧 Handles missing or invalid emails with error logging. ⚠️ Key Benefits Streamlines customer onboarding request handling. ⏱️ Creates a centralized log for analytics and audits. 🧾 Improves customer experience with branded email communication. 💡 Reduces manual effort in follow-up and data entry. 🔄 Ensures reliable handling of incomplete or invalid submissions. 🛡️ Features Typeform trigger for new form submissions. 📝 Automatic Google Sheets logging of customer details. 📈 Conditional email validation before sending. 🔍 Dynamic HTML email generation with customer details. 🎨 Automated Gmail delivery of welcome emails. 📧 Error handling node for missing/invalid email submissions. 🚨 Requirements n8n instance (cloud or self-hosted). Typeform API credentials with webhook permissions. Google Sheets OAuth2 credentials with spreadsheet write access. Gmail OAuth2 credentials with send email permissions. Pre-configured Google Sheet for onboarding request tracking. Target Audience Customer success and onboarding teams. 👩‍💻 SaaS startups managing onboarding inquiries. 🚀 Support teams handling product/service onboarding. 🛠️ SMBs looking for efficient onboarding automation. 🏢 Remote teams needing structured onboarding workflows. 🌐 Step-by-Step Setup Instructions Connect Typeform, Google Sheets, and Gmail credentials in n8n. 🔑 Insert your Typeform form ID in the trigger node. 📝 Replace the Google Sheet ID with your tracking sheet. 📊 Map form fields to spreadsheet columns (ensure headers match). 🔗 Customize email HTML template with branding and company info. 🎨 Update sender email in the Gmail node. 📧 Test the workflow with a sample form submission. ✅