by Hans Wilhelm Radam
📌 Title (SEO-Friendly) Automate Facebook Messenger orders to Google Sheets and Google Calendar Introduction This workflow automates Facebook Messenger order management by connecting your Facebook Page with Google Sheets and Google Calendar. It’s designed to help small businesses save time, reduce errors, and streamline order-taking. Every time a customer messages your page, they receive a structured order form, their responses are parsed, and the details are saved directly to Google Sheets. The same workflow also creates a Google Calendar event, ensuring you never miss a delivery or pickup schedule. Who’s It For Small businesses** selling products through Facebook Messenger. Entrepreneurs** who want to eliminate manual order-taking. Teams** that need a centralized order tracker (Google Sheets) and automatic reminders (Google Calendar). How It Works Listen to incoming messages on Facebook Messenger. Send an automated greeting and order form to the customer. Parse their responses (items, quantity, payment method, etc.). Save order details into Google Sheets for easy tracking. Create a matching Google Calendar event for the order date/time. Send a confirmation message and an optional upsell suggestion. Requirements Facebook Page** with Messenger enabled. Meta for Developers account** to create a Facebook App and generate a Page Access Token. Google Sheets** account with a spreadsheet containing the following columns: Date, Customer Name, Order Details, Payment Method, Order Status, Notes Google Calendar** account for order scheduling. n8n instance** (cloud or self-hosted). 💡 Security Best Practice: Store your Page Access Token and Google credentials in n8n Credentials (not hardcoded in nodes). Setup Instructions 1. Facebook Messenger Connection Go to Meta for Developers. Create a Messenger App and generate a Page Access Token. Copy the Webhook URL from your n8n Webhook Trigger node. Add the webhook URL and verify it in your Facebook Page settings. 2. Google Sheets Setup Create a new spreadsheet named Messenger Orders. Add columns: Date, Customer Name, Order Details, Payment Method, Order Status, Notes. Share the sheet with the Google account connected in n8n. 3. Google Calendar Setup Connect your Google Calendar credentials in n8n. Select the calendar where orders should be added. 4. Import & Configure Workflow Download this workflow template. Replace placeholders ({{YOUR_PAGE_ACCESS_TOKEN}}, {{YOUR_GOOGLE_SHEET_ID}}, etc.). Test by sending a message to your Facebook Page. Customization Personalize messages** in the Messenger node (greeting, upsell suggestions). Add extra fields such as delivery address or contact number to both the form and the Google Sheet. Extend the workflow by adding Telegram, Email, or SMS notifications for customers or staff. Use Filter nodes to route VIP orders or high-value purchases to a separate workflow. ⚡ Final Flow: Facebook Messenger → Order Form → Google Sheets → Google Calendar → Customer Confirmation 💬 Call to Action: Clone this workflow, connect your accounts, and start automating your Messenger orders in minutes!
by Punit
WordPress AI Content Creator Overview Transform a few keywords into professionally written, SEO-optimized WordPress blog posts with custom featured images. This workflow leverages AI to research topics, structure content, write engaging articles, and publish them directly to your WordPress site as drafts ready for review. What This Workflow Does Core Features Keyword-to-Article Generation**: Converts simple keywords into comprehensive, well-structured articles Intelligent Content Planning**: Uses AI to create logical chapter structures and content flow Wikipedia Integration**: Researches factual information to ensure content accuracy and depth Multi-Chapter Writing**: Generates coherent, contextually-aware content across multiple sections Custom Image Creation**: Generates relevant featured images using DALL-E based on article content SEO Optimization**: Creates titles, subtitles, and content optimized for search engines WordPress Integration**: Automatically publishes articles as drafts with proper formatting and featured images Business Value Content Scale**: Produce high-quality blog posts in minutes instead of hours Research Efficiency**: Automatically incorporates factual information from reliable sources Consistency**: Maintains professional tone and structure across all generated content SEO Benefits**: Creates search-engine friendly content with proper HTML formatting Cost Savings**: Reduces need for external content creation services Prerequisites Required Accounts & Credentials WordPress Site with REST API enabled OpenAI API access (GPT-4 and DALL-E models) WordPress Application Password or JWT authentication Public-facing n8n instance for form access (or n8n Cloud) Technical Requirements WordPress REST API v2 enabled (standard on most WordPress sites) WordPress user account with publishing permissions n8n instance with LangChain nodes package installed Setup Instructions Step 1: WordPress Configuration Enable REST API (usually enabled by default): Check that yoursite.com/wp-json/wp/v2/ returns JSON data If not, contact hosting provider or install REST API plugin Create Application Password: In WordPress Admin: Users > Profile Scroll to "Application Passwords" Add new password with name "n8n Integration" Copy the generated password (save securely) Get WordPress Site URL: Note your full WordPress site URL (e.g., https://yourdomain.com) Step 2: OpenAI Configuration Obtain OpenAI API Key: Visit OpenAI Platform Create API key with access to: GPT-4 models (for content generation) DALL-E (for image creation) Add OpenAI Credentials in n8n: Navigate to Settings > Credentials Add "OpenAI API" credential Enter your API key Step 3: WordPress Credentials in n8n Add WordPress API Credentials: In n8n: Settings > Credentials > "WordPress API" URL: Your WordPress site URL Username: Your WordPress username Password: Application password from Step 1 Step 4: Update Workflow Settings Configure Settings Node: Open the "Settings" node Replace wordpress_url value with your actual WordPress URL Keep other settings as default or customize as needed Update Credential References: Ensure all WordPress nodes reference your WordPress credentials Verify OpenAI nodes use your OpenAI credentials Step 5: Deploy Form (Production Use) Activate Workflow: Toggle workflow to "Active" status Note the webhook URL from Form Trigger node Test Form Access: Copy the form URL Test form submission with sample data Verify workflow execution completes successfully Configuration Details Form Customization The form accepts three key inputs: Keywords**: Comma-separated topics for article generation Number of Chapters**: 1-10 chapters for content structure Max Word Count**: Total article length control You can modify form fields by editing the "Form" trigger node: Add additional input fields (category, author, publish date) Change field types (dropdown, checkboxes, file upload) Modify validation rules and requirements AI Content Parameters Article Structure Generation The "Create post title and structure" node uses these parameters: Model**: GPT-4-1106-preview for enhanced reasoning Max Tokens**: 2048 for comprehensive structure planning JSON Output**: Structured data for subsequent processing Chapter Writing The "Create chapters text" node configuration: Model**: GPT-4-0125-preview for consistent writing quality Context Awareness**: Each chapter knows about preceding/following content Word Count Distribution**: Automatically calculates per-chapter length Coherence Checking**: Ensures smooth transitions between sections Image Generation Settings DALL-E parameters in "Generate featured image": Size**: 1792x1024 (optimized for WordPress featured images) Style**: Natural (photographic look) Quality**: HD (higher quality output) Prompt Enhancement**: Adds photography keywords for better results Usage Instructions Basic Workflow Access the Form: Navigate to the form URL provided by the Form Trigger Enter your desired keywords (e.g., "artificial intelligence, machine learning, automation") Select number of chapters (3-5 recommended for most topics) Set word count (1000-2000 words typical) Submit and Wait: Click submit to trigger the workflow Processing takes 2-5 minutes depending on article length Monitor n8n execution log for progress Review Generated Content: Check WordPress admin for new draft post Review article structure and content quality Verify featured image is properly attached Edit as needed before publishing Advanced Usage Custom Prompts Modify AI prompts to change: Writing Style**: Formal, casual, technical, conversational Target Audience**: Beginners, experts, general public Content Focus**: How-to guides, opinion pieces, news analysis SEO Strategy**: Keyword density, meta descriptions, heading structure Bulk Content Creation For multiple articles: Create separate form submissions for each topic Schedule workflow executions with different keywords Use CSV upload to process multiple keyword sets Implement queue system for high-volume processing Expected Outputs Article Structure Generated articles include: SEO-Optimized Title**: Compelling, keyword-rich headline Descriptive Subtitle**: Supporting context for the main title Introduction**: ~60 words introducing the topic Chapter Sections**: Logical flow with HTML formatting Conclusions**: ~60 words summarizing key points Featured Image**: Custom DALL-E generated visual Content Quality Features Factual Accuracy**: Wikipedia integration ensures reliable information Proper HTML Formatting**: Bold, italic, and list elements for readability Logical Flow**: Chapters build upon each other coherently SEO Elements**: Optimized for search engine visibility Professional Tone**: Consistent, engaging writing style WordPress Integration Draft Status**: Articles saved as drafts for review Featured Image**: Automatically uploaded and assigned Proper Formatting**: HTML preserved in WordPress editor Metadata**: Title and content properly structured Troubleshooting Common Issues "No Article Structure Generated" Cause: AI couldn't create valid structure from keywords Solutions: Use more specific, descriptive keywords Reduce number of chapters requested Check OpenAI API quotas and usage Verify keywords are in English (default language) "Chapter Content Missing" Cause: Individual chapter generation failed Solutions: Increase max tokens in chapter generation node Simplify chapter prompts Check for API rate limiting Verify internet connectivity for Wikipedia tool "WordPress Publication Failed" Cause: Authentication or permission issues Solutions: Verify WordPress credentials are correct Check WordPress user has publishing permissions Ensure WordPress REST API is accessible Test WordPress URL accessibility "Featured Image Not Attached" Cause: Image generation or upload failure Solutions: Check DALL-E API access and quotas Verify image upload permissions in WordPress Review image file size and format compatibility Test manual image upload to WordPress Performance Optimization Large Articles (2000+ words) Increase timeout values in HTTP request nodes Consider splitting very long articles into multiple posts Implement progress tracking for user feedback Add retry mechanisms for failed API calls High-Volume Usage Implement queue system for multiple simultaneous requests Add rate limiting to respect OpenAI API limits Consider batch processing for efficiency Monitor and optimize token usage Customization Examples Different Content Types Product Reviews Modify prompts to include: Pros and cons sections Feature comparisons Rating systems Purchase recommendations Technical Tutorials Adjust structure for: Step-by-step instructions Code examples Prerequisites sections Troubleshooting guides News Articles Configure for: Who, what, when, where, why structure Quote integration Fact checking emphasis Timeline organization Alternative Platforms Replace WordPress with Other CMS Ghost**: Use Ghost API for publishing Webflow**: Integrate with Webflow CMS Strapi**: Connect to headless CMS Medium**: Publish to Medium platform Different AI Models Claude**: Replace OpenAI with Anthropic's Claude Gemini**: Use Google's Gemini for content generation Local Models**: Integrate with self-hosted AI models Multiple Models**: Use different models for different tasks Enhanced Features SEO Optimization Add nodes for: Meta Description Generation**: AI-created descriptions Tag Suggestions**: Relevant WordPress tags Internal Linking**: Suggest related content links Schema Markup**: Add structured data Content Enhancement Include additional processing: Plagiarism Checking**: Verify content originality Readability Analysis**: Assess content accessibility Fact Verification**: Multiple source confirmation Image Optimization**: Compress and optimize images Security Considerations API Security Store all credentials securely in n8n credential system Use environment variables for sensitive configuration Regularly rotate API keys and passwords Monitor API usage for unusual activity Content Moderation Review generated content before publishing Implement content filtering for inappropriate material Consider legal implications of auto-generated content Maintain editorial oversight and fact-checking WordPress Security Use application passwords instead of main account password Limit WordPress user permissions to minimum required Keep WordPress and plugins updated Monitor for unauthorized access attempts Legal and Ethical Considerations Content Ownership Understand OpenAI's terms regarding generated content Consider copyright implications for Wikipedia-sourced information Implement proper attribution where required Review content licensing requirements Disclosure Requirements Consider disclosing AI-generated content to readers Follow platform-specific guidelines for automated content Ensure compliance with advertising and content standards Respect intellectual property rights Support and Maintenance Regular Maintenance Monitor OpenAI API usage and costs Update AI prompts based on output quality Review and update Wikipedia search strategies Optimize workflow performance based on usage patterns Quality Assurance Regularly review generated content quality Implement feedback loops for improvement Test workflow with diverse keyword sets Monitor WordPress site performance impact Updates and Improvements Stay updated with OpenAI model improvements Monitor n8n platform updates for new features Engage with community for workflow enhancements Document custom modifications for future reference Cost Optimization OpenAI Usage Monitor token consumption patterns Optimize prompts for efficiency Consider using different models for different tasks Implement usage limits and budgets Alternative Approaches Use local AI models for cost reduction Implement caching for repeated topics Batch similar requests for efficiency Consider hybrid human-AI content creation License and Attribution This workflow template is provided under MIT license. Attribution to original creator appreciated when sharing or modifying. Generated content is subject to OpenAI's usage policies and terms of service.
by Jimmy Gay
🔧 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.
by Masaki Go
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.
by Cheng Siong Chin
How It Works This workflow automates enterprise ticket management by combining AI-powered classification with knowledge base retrieval. It receives support tickets via webhook, routes them through multiple AI models (OpenAI ChatGPT, NVIDIA's text classification APIs, and embeddings-based search) to determine optimal resolution strategies. The system generates contextual diagnostic logs, formats responses, updates ticket systems, notifies engineers when escalation is needed, and seamlessly integrates with knowledge bases for continuous learning. It solves the critical problem of manual ticket sorting and delayed responses by automating intelligent triage, reducing resolution time, and ensuring consistent quality across support operations. Target audience includes support operations teams, technical support managers, and enterprises managing high-volume ticket queues seeking to improve efficiency and SLA compliance. Setup Steps Configure the OpenAI API key in credentials. Add NVIDIA API credentials for embedding and classification models. Set up Google Sheets for knowledge base storage and retrieval. Connect your ticketing system (Jira, Zendesk, or webhook) for incoming tickets. Link a notification service (Gmail or Slack) for engineer alerts. Map custom fields to your ticket system schema. Prerequisites OpenAI API account with GPT access. NVIDIA API credentials (Embeddings & Classification). Google Sheets for KB management. Ticketing system with webhook capability. Use Cases SaaS support teams triaging 100+ daily tickets, reducing manual sorting by 80%. Technical support escalating complex issues intelligently while documenting solutions. Customization Swap OpenAI models for Claude or Anthropic APIs. Replace Google Sheets with database systems (PostgreSQL, Airtable). Benefits Reduces manual ticket sorting by 70-80%, freeing support staff for complex issues. Decreases average resolution time through intelligent routing.
by WeblineIndia
Zoho CRM – Deal Health Predictor with AI Scoring This n8n automation monitors open Zoho CRM Deals every week, identifies stalled opportunities, scores their health using Google Gemini AI and triggers sales intervention by emailing the deal owner and creating a high-priority task in Zoho CRM — before the deal goes cold. Quick Start — Implementation in 6 Steps Import workflow into your n8n instance. Connect Zoho OAuth2 credential in all Zoho nodes. Connect Gmail OAuth2 account for outbound alerts. Confirm stage names & inactivity thresholds match your CRM. Test with sample deals before scheduling. Activate the workflow once validated by your sales team. What It Does This workflow dynamically analyzes every open sales deal retrieved from Zoho CRM. It calculates key metrics per deal such as inactivity duration, stage aging and deal age to understand whether the opportunity has stalled. Only deals with significant inactivity move forward to AI scoring. Using Google Gemini, each deal receives a Health Score (0–100), along with a risk level, reasons and recommended next actions. If a deal is considered “At-Risk,” the system automatically: Sends an alert email to the assigned sales rep Creates a high-priority Task in Zoho CRM linked to that deal It ensures timely sales intervention without needing manual checks. Who’s It For Sales teams using Zoho CRM RevOps & Sales Managers monitoring deal movement Teams wanting data-backed alerts for slow-moving deals Businesses wanting proactive pipeline management with AI Requirements | Requirement | Why | |------------|-----| | n8n instance (Self-hosted or Cloud) | Runs the workflow | | Zoho CRM OAuth2 Credentials | Fetch deals + Create tasks | | Gmail (or SMTP) credentials | Send alert emails | | Google Gemini API access | AI scoring on deals | | Deals must have Stage + Owner + Activity history | Ensures accurate scoring | How It Works — Setup & Configuration Steps Step-by-Step Setup Import workflow into n8n Enable Zoho CRM OAuth2 credentials in: Fetch Open Deals Create At-Risk Task Enable Gmail OAuth2 on the email alert node Validate fields from Zoho API: Last_Activity_Time Stage Owner.email Update the deal stage list in the Fetch URL if needed: Example: Qualification, Negotiation, Proposal, etc. Confirm scanning frequency in the Weekly Trigger Run the workflow manually once → check logs + emails + tasks Turn workflow Active How To Customize Nodes | Node | What You Can Customize | Example | |------|-----------------------|---------| | Weekly Trigger | Change execution frequency | Daily scan | | Fetch Deals | Include additional deal stages | Add “Value Proposition” | | Filter Stalled Deals | Adjust inactivity threshold | > 15 days instead of 30 | | AI Prompt | Add more data points | Probability to close | | Email Alert | Modify message template | Localization | | Task creation | Add reminder / follow-up info | Due date +1 day | Add-Ons (Optional Enhancements) You can easily extend this workflow by adding: Stage Change Webhook Trigger** → near real-time monitoring Google Sheets or Database Logging** for reporting Duplicate task checker** so the same deal isn’t flagged repeatedly Slack / Microsoft Teams alerts** SLA-based scoring** (pipeline aging logic) Manager escalation** if no response in X days Practical Use Cases This workflow is ideal for: Sales manager auto-alert system for aging deals Leaderboard tracking for untouched deals Weekly CRM hygiene and rep performance tracking Early detection of churn risk in B2B sales cycles AI-assisted deal coaching and next-step suggestions Many more scenarios are possible based on deal movement automation. Troubleshooting Guide | Issue | Possible Cause | Fix / Solution | |------|----------------|----------------| | No deals processed | Stage filters too narrow | Update fetch URL stage list | | Emails not sent | Gmail credentials missing or expired | Reconnect Gmail OAuth2 | | Tasks not created | Zoho API permissions missing | Enable write permissions | | Owner email missing | CRM field not mapped correctly | Update sendTo expression | | Health score always null | Output parser mismatch | Check prompt & parser config | | Workflow runs but no alerts sent | No stalled deals or score >= threshold | Temporarily lower threshold for testing | Need Help? If you would like expert help customizing this workflow or implementing additional automation like stage-based triggers, dashboards or integration with Slack/Teams, our n8n automation team at WeblineIndia can assist you.
by Sona Labs
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
by Aslamul Fikri Alfirdausi
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.
by WeblineIndia
ETL Monitoring & Alert Automation: Jira & Slack Integration This workflow automatically processes ETL errors, extracts important details, generates a preview, creates a log URL, classifies the issue using AI and saves the processed data into Google Sheets. If the issue is important or needs attention, it also creates a Jira ticket automatically. The workflow reduces manual debugging effort, improves visibility and ensures high-severity issues are escalated instantly without human intervention. Quick Start – Implementation Steps Connect your webhook or ETL platform to trigger the workflow. Add your OpenAI, Google Sheets and Jira credentials. Enable the workflow. Send a sample error to verify Sheets logging and Jira ticket creation. Deploy and let the workflow monitor ETL pipelines automatically. What It Does This workflow handles ETL errors end-to-end by: Extracting key information from ETL error logs. Creating a short preview for quick understanding. Generating a URL to open the full context log. Asking AI to identify root cause and severity. Parsing the AI output into clean fields. Saving the processed error to Google Sheets. Creating a Jira ticket for medium/high-severity issues. This creates a complete automated system for error tracking, analysis and escalation. Who’s It For DevOps & engineering teams monitoring data pipelines. ETL developers who want automated error reporting. QA teams verifying daily pipeline jobs. Companies using Jira for issue tracking. Teams needing visibility into ETL failures without manual log inspection. Requirements to Use This Workflow n8n account or self-hosted instance. ETL platform capable of sending error payloads (via webhook). OpenAI API Key. Google Sheets credentials. Jira Cloud API credentials. Optional: log storage URL (S3, Supabase, server logs). How It Works & Setup Steps 1. Get ETL Error (Webhook Trigger) Receives ETL error payload and starts the workflow. 2. Prepare ETL Logs (Code Node) Extracts important fields and makes a clean version of the error.Generates a direct link to open the full ETL log. 3. AI Severity Classification (OpenAI / AI Agent) AI analyzes the issue, identifies cause and assigns severity. 4. Parse AI Output (Code Node) Formats AI results into clean fields: severity, cause, summary, recommended action. 5. Prepare Data for Logging (Set / Edit Fields) Combines all extracted info into one final structured record. 6. Save ETL Logs (Google Sheets Node) Logs each processed ETL error in a spreadsheet for tracking. 7. Create Jira Ticket (Jira Node) Automatically creates a Jira issue when severity is Medium, High or Critical. 8. ETL Failure Alert (Slack Node) Sends a Slack message to notify the team about the issue. 9. ETL Failure Notify (Gmail Node) Sends an email with full error details to the team. How to Customize Nodes ETL Log Extractor Add/remove fields based on your ETL log structure. AI Classification Modify the OpenAI prompt for custom severity levels or deep-dive analysis. Google Sheets Logging Adjust columns for environment, job name or log ID. Jira Fields Customize issue type, labels, priority and assignees. Add-Ons (Extend the Workflow) Send Slack or Teams alerts for high severity issues Store full logs in cloud storage (S3, Supabase, GCS) Add daily/weekly error summary reports Connect monitoring tools like Datadog or Grafana Trigger automated remediation workflows Use Case Examples Logging all ETL failures to Google Sheets Auto-creating Jira tickets with AI-driven severity Summarizing large logs with AI for quick analysis Centralized monitoring of multiple ETL pipelines Reducing manual debugging effort across teams Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | Sheets not updating | Wrong Sheet ID or missing permission | Reconnect and reselect the sheet | | Jira ticket fails | Missing required fields or invalid project key | Update Jira mapping | | AI output empty | Invalid OpenAI key or exceeded usage | Check API key or usage limits | | Severity always “low” | Prompt too broad | Adjust AI prompt with stronger rules | | Log preview empty | Incorrect error field mapping | Verify the structure of the ETL error JSON | Need Help? For assistance setting up this workflow, customizing nodes or adding additional features, feel free to contact our n8n developers at WeblineIndia. We can help configure, scale or build similar automation workflows tailored to your ETL and business requirements.
by inderjeet Bhambra
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.
by Yusuke
🧠 Overview Generate empathetic, professional reply drafts for customer or user messages. The workflow detects sentiment, tone, and risk level, drafts a concise response, sanitizes PII/links/emojis, and auto-escalates risky or low-confidence cases to human review. ⚙️ How It Works Input — Manual Test or Webhook Trigger AI Agent (Empathy) — returns { sentiment, tone, reply, confidence, needs_handover } Post-Process & Sanitize — removes URLs/hashtags, masks PII, caps length Risk & Handover Rules — checks confidence threshold, risk words, and negativity Routing — auto-send safe replies or flag to Needs Review 🧩 Setup Instructions (3–5 min) Open Set Config1 and adjust: MAX_LEN (default 600) ADD_FOLLOWUP_QUESTION (true/false) FORMALITY (auto | casual | polite) EMOJI_ALLOWED (true/false), BLOCK_LINKS (true/false) RISK_WORDS (e.g., refund, lawsuit, self-harm) Connect Anthropic credential to Anthropic Chat Model (Optional) Replace Manual Trigger with Webhook Trigger for real-time use > Tip: If you need to show literal angle brackets in messages, use backticks like `<example>` (no HTML entities needed). 📚 Use Cases 1) SaaS Billing Complaints Input:** “I was billed after canceling. This is unacceptable.” Output:** Calm, apologetic reply with refund steps; escalates if refund is in RISK_WORDS or confidence < 0.45. 2) Product Bug Reports Input:** “Upload fails on large files since yesterday.” Output:** Acknowledges impact, requests logs, offers workaround; routes to auto-send if low risk and high confidence. 3) Delivery/Logistics Delays Input:** “My order is late again. Should I file a complaint?” Output:** Empathetic apology, ETA guidance, partial credit policy note; escalates if language indicates legal action. 4) Community Moderation / Abuse Input:** “Support is useless—you’re all scammers.” Output:** De-escalating, policy-aligned response; auto-flags due to negative sentiment + risk keyword match. 5) Safety / Self-harm Mentions Input:** “I feel like hurting myself if this isn’t fixed.” Output:* *Immediate escalation**, inserts approved resources; never auto-sends. 🚨 Auto-Escalation Rules (defaults) Negative** sentiment Message matches any RISK_WORDS confidence < 0.45 Mentions of legal, harassment, or self-harm context 🧪 Notes & Best Practices 🔐 No hardcoded API keys — use n8n Credentials 🧭 Tune thresholds and RISK_WORDS to your org policy 🧩 Works on self-hosted or cloud n8n ✅ Treat outputs as drafts; ship after human/policy review 🔗 Resources GitHub (template JSON):** https://github.com/yskmtb0714/n8n-workflows/blob/main/empathy-reply-assistant.json
by Țugui Dragoș
This workflow is a comprehensive, production-grade automation for B2B lead management and multichannel outreach, designed for Sales Development Representatives (SDRs), growth teams, and sales operations. It covers the entire SDR pipeline: from lead ingestion and validation, through enrichment, scoring, AI-powered outreach, reply handling, analytics, and reporting. Key Features: Lead validation (email, suppression, geo/GDPR) Multi-source data enrichment Lead scoring and tiering (HIGH/MEDIUM/LOW) AI-generated personalized cold emails (with A/B subject testing) Multichannel outreach (Email, LinkedIn, WhatsApp) with rate limiting and compliance AI-based reply simulation and intent classification Automated routing (qualification, follow-up, manual review) Full event logging to database Aggregated analytics and daily reporting Human-readable AI summary and Slack notifications What This Workflow Does 1. Lead Ingestion & Validation Loads leads from a source (test data, CRM, webhook, etc.) Validates email format and checks against suppression lists (blocked domains/emails) Applies geo and GDPR compliance logic (blocks/flags leads from restricted countries) 2. Data Enrichment Enriches each lead via one or more external APIs (company info, tech stack, revenue, etc.) Handles enrichment failures gracefully and logs them for analytics 3. Lead Scoring & Segmentation Scores leads based on industry, country, company size, revenue, and pain points Segments leads into HIGH, MEDIUM, or LOW tiers for tailored outreach 4. AI-Powered Outreach Generation Uses OpenAI (or compatible LLM) to generate personalized cold email content Creates A/B tested subject lines for each email Generates LinkedIn and WhatsApp message variants for multichannel outreach 5. Multichannel Outreach Execution Sends emails via SMTP (with rate limiting and quiet hours) Simulates LinkedIn and WhatsApp sends (can be replaced with real integrations) Logs all outreach events to a Postgres database 6. Reply Simulation & AI Classification Simulates a variety of lead replies (interested, not interested, follow-up, unclear) Uses AI to classify reply intent and suggest next actions 7. Automated Routing & Follow-up Routes leads based on AI classification: Interested: Schedules meeting, logs qualification, proposes follow-up Follow-up Later: Schedules future follow-up Not Interested: Marks as closed/lost Unclear: Flags for manual review and notifies team via Slack 8. Event Logging & Analytics Logs every significant event (enrichment, outreach, reply, status change) to a database Aggregates results by lead score, channel, and status Calculates key metrics (qualification rate, enrichment success, multichannel rate, etc.) 9. Reporting & Team Notification Generates a daily analytics row and stores it in the database Uses AI to create a human-readable summary of the run Posts a detailed summary to a Slack channel Use Cases Automated SDR Workflows:** Replace manual lead research, outreach, and follow-up with a fully automated, auditable process. Growth Experiments:** Run A/B tests on messaging, subject lines, and channels at scale. Sales Analytics:** Get transparent, granular reporting on every step of the SDR funnel. Compliance-First Outreach:** Ensure all outreach respects geo, GDPR, and suppression rules. AI-Driven Personalization:** Use LLMs to generate highly relevant, non-generic outreach at scale. Installation & Setup 1. Import the Workflow Download or copy the workflow from the n8n Template Store. In your n8n editor, click Import and paste the workflow JSON, or use the "Use Template" button. 2. Configure Required Credentials Postgres:** Set up a Postgres credential for event and analytics logging. SMTP:** Add your email provider's SMTP credentials for sending emails. OpenAI:** Add your OpenAI API key for AI-powered nodes. Slack:** Add your Slack API credential for notifications. Enrichment APIs:** Add credentials for any external enrichment APIs you use. 3. Customize Lead Source Replace the test data in the Load Test Leads node with your real lead source (e.g., webhook, CRM, Google Sheets, etc.). 4. Adjust Compliance & Suppression Logic Update the suppression lists and geo/GDPR logic in the relevant nodes to match your organization's requirements. 5. Review Multichannel Logic The workflow simulates LinkedIn and WhatsApp sends. Replace these with real integrations if needed. 6. Database Preparation Ensure your Postgres database has the following tables (or adjust node configs): lead_events (for all event logs) analytics_daily (for daily summary rows) meetings (for scheduled meetings) execution_runs (for workflow run metadata) 7. Test the Workflow Run the workflow manually with sample data. Check the database and Slack for logs and notifications. Review AI-generated content for tone and compliance. Configuration Details Rate Limiting:** Email, LinkedIn, and WhatsApp sends are rate-limited and respect quiet hours. A/B Testing:** Each email uses a randomly selected subject variant for ongoing optimization. AI Models:** Uses OpenAI GPT-4o-mini by default; can be swapped for other models. Event Logging:** Every action (enrichment, outreach, reply, status change) is logged with timestamp and payload for full traceability. Analytics:** Aggregates by lead score, channel, and status; calculates rates and averages. Slack Notifications:** Posts a summary of each run, including key metrics and AI-generated insights. Advanced Customization Add/Replace Enrichment APIs:** Plug in any HTTP-based enrichment service. Custom Lead Scoring:** Adjust the scoring logic in the Compute Lead Score node to fit your ICP. Custom AI Prompts:** Edit the system messages in AI nodes for your brand voice. Additional Channels:** Integrate SMS, phone, or other channels as needed. Webhook Triggers:** Replace manual trigger with webhook for real-time automation. Requirements n8n version 1.123.0 or later Postgres database (or adapt for your DB) SMTP email provider OpenAI API key (or compatible LLM) Slack workspace (for notifications) (Optional) Enrichment API keys Template Store Submission Notes All credentials are handled via n8n's credential system (no hardcoded secrets). The workflow is modular, well-commented, and ready for production use. All event and analytics logging is auditable and GDPR-compliant. Please review and test all integrations in your environment before using in production. Example Analytics Output | Metric | Value | |-----------------------|---------| | Total Leads | 100 | | Qualified | 22 | | Follow-up Scheduled | 15 | | Closed Lost | 40 | | Manual Review | 3 | | Qualification Rate | 22% | | Enrichment Success | 90% | | Multichannel Rate | 60% | Ready to automate your SDR pipeline? Import this workflow and start scaling your B2B outreach today!