Workflow Templates

How It Works This workflow automates end-to-end patient care coordination by monitoring appointment schedules, clinical events, and care milestones while orchestrating personalized communications across multiple channels. Designed for healthcare operations teams, care coordinators, and patient engagement specialists, it solves the challenge of manual patient follow-up, missed appointments, and fragmented communication across care teams. The system triggers on scheduled intervals and real-time clinical events, ingesting data from EHR systems, appointment schedulers, and lab result feeds. Patient records flow through validation and risk stratification layers using AI models that identify high-risk patients, predict no-show probability, and recommend intervention timing. The workflow applies clinical protocols for appointment reminders, medication adherence checks, and post-discharge follow-ups. Critical cases automatically route to care coordinators via Slack alerts, while routine communications deploy via SMS, email, and patient portal notifications. All interactions log to secure databases for compliance documentation. This eliminates manual outreach coordination, reduces no-shows by 40%, and ensures HIPAA-compliant patient engagement at scale. Setup Steps Configure EHR/FHIR API credentialsfor patient data access Set up webhook endpoints for real-time clinical event notifications Add OpenAI API key for patient risk stratification and communication personalization Configure Twilio credentials for SMS and voice call delivery Set Gmail OAuth or SMTP credentials for email appointment reminders Connect Slack workspace and define care coordination alert channels Prerequisites Active EHR system with FHIR API access or HL7 integration capability. Use Cases Automated appointment reminder campaigns reducing no-shows. Customization Modify risk scoring models for specialty-specific patient populations. Benefits Reduces patient no-show rates by 40% through timely, personalized reminders.

How It Works This workflow automates satellite data processing by ingesting raw geospatial data, applying AI analysis, and submitting formatted reports to regulatory authorities. Designed for environmental agencies, research institutions, and compliance teams, it solves the challenge of manually processing large satellite datasets and preparing standardized submissions for government agencies. The system triggers on scheduled intervals or event webhooks, fetching satellite imagery and sensor data from ECC/climate APIs. Raw data flows through parsing and normalization stages, then routes to AI models for analysis—detecting environmental changes, calculating metrics, and identifying anomalies. Processed results are validated against agency specifications, formatted into SDQAR reports, and automatically stored in designated repositories. The workflow generates submission packages with required metadata, notifies stakeholders via Slack and email, and logs all activities to Google Sheets for audit trails. This eliminates hours of manual data processing, ensures compliance with submission standards, and accelerates environmental monitoring workflows. Setup Steps Configure ECC/climate API credentials for satellite data access Set up webhook endpoints for event-driven data ingestion triggers Add OpenAI API key for geospatial analysis and anomaly detection Configure NVIDIA NIM API for specialized environmental modeling Set Google Sheets credentials for audit logging and tracking Connect Slack workspace and specify notification channels for submission updates Configure Gmail OAuth for automated stakeholder notifications Prerequisites Active satellite data API access (ECC, NASA, ESA) with authentication credentials. Use Cases Automated climate monitoring with monthly regulatory submissions. Customization Modify AI analysis prompts for specific environmental parameters. Benefits Reduces satellite data processing time by 85% through end-to-end automation.

Geopolitics Breaking News Alert System Workflow Name: Geopolitics Breaking News Alert System Author: Devjothi Dutta Category: Productivity, News & Media, AI/Machine Learning Complexity: Medium Setup Time: 45-60 minutes 📖 Description An intelligent geopolitical monitoring system that filters 200+ daily news articles down to only the critical breaking news that matters to you. This workflow uses smart keyword filtering and AI-powered scoring to eliminate noise, reduce AI costs, and deliver only high-priority geopolitical alerts to Telegram. The Problem: Traditional news monitoring is overwhelming - hundreds of articles per hour, 95% irrelevant to your region of interest, no urgency prioritization, and critical breaking news gets buried in noise. The Solution: This workflow combines dual-layer filtering (primary + secondary keywords) with AI scoring to distinguish actual breaking news from general news coverage. By filtering first and scoring second, you reduce AI API costs by 80-90% while ensuring you never miss critical geopolitical developments. Switch between monitoring India, China, Middle East, Russia-Ukraine, or any region by simply changing a configuration file. Perfect for government analysts, corporate security teams, investment research firms, news organizations, or anyone who needs to stay informed about geopolitical developments without information overload. 👥 Who's it for For Government & Defense Analysts: Monitor specific regions for military actions, diplomatic developments, and security threats Filter by mission-critical keywords to eliminate irrelevant news AI scoring identifies genuine breaking news vs routine coverage Reduce analyst workload by 90% through intelligent automation For Corporate Security & Risk Teams: Track geopolitical risks affecting global supply chains and operations Custom keyword filters for industry-specific concerns (e.g., "semiconductor", "tariff", "sanctions") Real-time alerts for events impacting business continuity Cost-efficient monitoring with minimal AI API usage For Investment Research Firms: Monitor emerging market geopolitical risks affecting portfolio companies AI scoring differentiates market-moving events from background noise Configurable alert thresholds based on investment strategy (conservative vs aggressive) Track multiple regions simultaneously with different configs For News Organizations & Journalists: Monitor breaking geopolitical developments for editorial coverage Filter by urgency to prioritize assignment desk resources Aggregate multiple international news sources in one place Extend alerts to newsroom Slack channels or email ✨ Key Features 🎯 Smart Dual-Layer Filtering - Primary keywords ensure regional relevance, secondary keywords filter by event type (military, diplomatic, economic) 🤖 AI-Powered Urgency Scoring - GPT-4o-mini scores articles 1-10 based on geopolitical urgency, distinguishing breaking news from routine coverage 💰 Cost-Efficient Design - Filter first, score second approach reduces AI API calls by 80-90% (only ~5 articles analyzed out of 200) 🌍 Multi-Region Support - Monitor India, China, Middle East, Russia-Ukraine, or any region by switching config files 📰 Multi-Source RSS Aggregation - Combines 6 international news sources (NYT, BBC, Al Jazeera, SCMP, regional feeds) 🔄 Duplicate Detection - Persistent storage prevents re-analyzing same articles across multiple executions 📊 Consolidated Alerts - Single Telegram message with all breaking news, grouped by urgency score ⏰ Flexible Scheduling - Configure trigger interval per your needs (15min for active conflicts, 3hr for routine monitoring) 💾 Config-Driven Architecture - All filters, keywords, and scoring rules in Google Drive JSON file 🔒 Production Ready - Tested end-to-end with real-world India and China configurations 📈 Scalable Design - Run multiple regional configs in parallel, extend to Slack/WhatsApp/Email delivery 🛠️ Requirements Required Services: n8n (version 1.0+) - Workflow automation platform Free tier: n8n cloud or self-hosted Docker Required feature: Data Tables (for duplicate tracking) OpenAI API (GPT-4o-mini) - AI scoring engine Cost: ~$0.10/day for 30min intervals Free tier: $5 credit for new accounts Telegram Bot - Alert delivery Free: Create via @BotFather on Telegram Get chat ID via @userinfobot Google Drive - Config file storage Free: Any Google account Used for publicly shared JSON config files Required Credentials: OpenAI API Key** - Get from platform.openai.com (GPT-4o-mini access) Telegram Bot Token** - Create bot via @BotFather, get token n8n Data Table** - Built-in n8n feature (no external credential) Optional: Slack Webhook URL (for extending alerts to Slack) SMTP credentials (for email alerts) Twilio account (for WhatsApp/SMS alerts) 📦 What's Included This workflow package includes: Complete n8n workflow JSON (ready to import) Complete setup guide - Detailed configuration with Data Table setup, troubleshooting Technical architecture documentation Use cases and customization guide 4 pre-built regional configs (India, China, Middle East, Russia-Ukraine) 🚀 Quick Start Full setup takes 45-60 minutes. For detailed step-by-step instructions, see SETUP_GUIDE.md Overview Create n8n Data Table (analyzed_articles with 2 columns) Upload config to Google Drive (choose region, share publicly, get file ID) Import workflow (22 nodes ready to configure) Configure nodes: Update Google Drive config URL with your file ID Update 6 RSS Feed URLs for your region Link 3 Data Table nodes to analyzed_articles table Add credentials (OpenAI API, Telegram Bot) Set schedule (15min-daily based on monitoring needs) Test workflow (verify filtering, scoring, alerts work) Activate (workflow runs automatically on schedule) Quick Start Result: ✅ 200+ articles processed → 5-7 filtered → 3-5 scored → 1-3 alerts sent ✅ Telegram receives consolidated breaking news message ✅ Workflow runs every 30min (or your chosen interval) ✅ Total monthly cost: $3-5 (OpenAI API only) Need help? See detailed SETUP_GUIDE.md for complete instructions with screenshots and troubleshooting. 📊 Workflow Stats Nodes:** 22 Complexity:** Medium Execution Time:** ~30-60 seconds per run Monthly Cost:** $3-5 (OpenAI API usage only) Maintenance:** Minimal (update RSS feeds if sources change) Scalability:** Handles 200+ articles per execution, easily scales to 10+ RSS feeds 🎨 Customization Options Add more regions:** Create new config JSON files for North Korea, Taiwan, Africa, Latin America, etc. Multi-channel alerts:** Extend to Slack, WhatsApp, Email, Discord, Microsoft Teams, SMS Severity-based routing:** Send critical alerts (score 9-10) via SMS, others to Telegram Custom scoring models:** Switch between GPT-4o-mini, GPT-4o, Claude based on config Exclude keywords:** Add "exclude_keywords" array to filter out sports, entertainment, weather Alert digest mode:** Aggregate alerts into daily/weekly summary emails instead of real-time Dashboard integration:** Connect to Grafana or Metabase for visual trend analysis Webhook triggers:** Use workflow output to trigger other n8n workflows or external systems Custom RSS feeds:** Add industry-specific or regional news sources Adjust alert threshold:** Change from score >= 6 to higher/lower based on notification preferences 🔧 How it Works Schedule Trigger (Configurable): Workflow runs at your configured interval (15min, 30min, 1hr, 3hr, daily, etc.) Trigger frequency depends on use case: active conflicts need more frequent monitoring Config Loading: HTTP Request node fetches JSON config from Google Drive Config contains: keywords, scoring rules, AI role, alert threshold, Telegram chat ID RSS Aggregation: 6 RSS Feed nodes fetch articles from international news sources Merge node combines all feeds (~200 articles per execution) RSS Cleanup node strips HTML and normalizes to 5 fields (60-75% size reduction) Smart Filtering (Cost Optimization Layer 1): Dynamic Filter checks PRIMARY keywords (geographic/entity: "india", "modi", "delhi") Also checks SECONDARY keywords (event type: "military", "conflict", "trade deal") Both conditions required: Article must mention at least one primary AND one secondary Result: 200 articles reduced to ~5-7 relevant articles (95% reduction) Why this matters: Eliminates noise BEFORE expensive AI scoring Duplicate Detection (Cost Optimization Layer 2): Queries Data Table for previously analyzed article links Filters out articles already scored in last 7 days Result: 5-7 filtered articles reduced to 3-5 new articles Why this matters: Prevents redundant AI API calls (saves 80% on repeat articles) Dynamic AI Prompt Generation: Code node builds system prompt from config.ai_role and config.scoring_criteria Instructs AI: "You are a geopolitical analyst for [REGION]. Score articles 1-10..." Includes scoring rubric: 9-10 = Military Action, 7-8 = Trade/Economic, etc. AI Urgency Scoring (Breaking News Detection): Breaking News Analyzer (GPT-4o-mini) evaluates geopolitical urgency Scores 1-10: Distinguishes genuine breaking news from routine coverage Returns: score, category, reasoning, should_alert (true/false based on threshold) Cost: $0.002 per article (only 3-5 articles scored per execution) Alert Decision: IF node checks: should_alert === true (score >= config.alert_threshold) Only high-priority alerts proceed to Telegram Articles below threshold are logged but not sent Alert Aggregation: Consolidates multiple breaking news alerts into single Telegram message Groups by urgency score with color-coded emojis (🔴 9-10, 🟠 7-8, 🟡 6-7) Includes: score, category, title, link for each alert Telegram Delivery: Sends consolidated alert to configured Telegram chat Uses HTML formatting for bold text and clickable links Chat ID dynamically loaded from config (different regions → different chats) 💡 Pro Tips Start with Higher Threshold:** Begin with alert_threshold = 7 to avoid alert fatigue, lower to 6 after tuning keywords Regional RSS Matters:** Use region-specific news sources for better coverage (e.g., Times of India for India, not just BBC/NYT) Test Keywords First:** Run workflow manually with "Test Workflow" to verify keyword filtering before activating schedule Monitor AI Costs:** Check OpenAI usage dashboard after first week to confirm ~$0.10/day cost estimate Tune Secondary Keywords:** Add domain-specific terms to secondary keywords (e.g., "semiconductor" for tech supply chain monitoring) Use Separate Configs for Critical Regions:** Clone workflow for high-priority regions instead of switching configs manually Schedule Based on Time Zones:** Align execution intervals with business hours in monitored region (e.g., 9AM-6PM IST for India) Clear Duplicates for Testing:** Manually clear analyzed_articles Data Table when testing new configs for fresh results Backup Working Configs:** Export and version control config files before making major keyword changes Consider Alert Fatigue:** Score 9-10 events are rare (0-1 per day), score 6-8 events are common (2-5 per day) - set threshold accordingly 🔗 Related Workflows Multi-Region Geopolitics Dashboard** - Combine multiple regional configs into single monitoring dashboard Geopolitical Risk Scoring for Portfolios** - Integrate with stock portfolio data to assess investment risk Automated Geopolitical Intelligence Reports** - Generate daily/weekly PDF reports from breaking news data Conflict Escalation Tracker** - Track score trends over time to detect escalating tensions Supply Chain Risk Alerting** - Focus on trade/sanctions news affecting global supply chains 📧 Support & Feedback For questions, issues, or feature requests: GitHub:** n8n-geopolitics-breaking-news-alert Repository n8n Community Forum:** Tag @devdutta Email:** devjothi@gmail.com 📄 License MIT License - Free to use, modify, and distribute ⭐ If you find this workflow useful, please share your feedback and star the workflow!

How It Works This workflow automates contract governance auditing by deploying a multi-agent AI system that validates contracts, assesses risk, checks compliance, and routes alerts based on risk level. Designed for legal, procurement, and compliance teams, it eliminates manual contract review bottlenecks and ensures timely escalation of high-risk issues. A schedule trigger initiates the workflow, simulating a contract audit data input. A Contract Validation Agent performs initial validation via OpenAI, then passes results to a Governance Orchestration Agent, which delegates to Risk Assessment and Compliance Checker sub-agents. Risk scores are routed by level—low, medium, or high—triggering appropriate notifications via Slack or email escalation before logging the audit trail. Setup Steps Set schedule trigger interval to match audit frequency requirements. Add OpenAI API credentials to all OpenAI Chat Model nodes. Configure Slack credentials and set target channel for risk notifications. Add Gmail/SMTP credentials to the Send Email Escalation node. Define risk thresholds in the Route by Risk Level rules node. Prerequisites Slack workspace with bot token Gmail or SMTP credentials Basic n8n workflow knowledge Use Cases Automated periodic contract risk auditing for procurement teams Compliance breach detection with instant escalation to legal Customization Replace simulated data with live contract database or webhook input Benefits Eliminates manual contract review with scheduled AI auditing

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Overview Automate your email management with this n8n workflow that fetches, summarizes, and shares critical emails from your Gmail inbox. Designed for busy professionals, this workflow runs daily to extract important emails from the past 24 hours, summarizes key details (like credentials, OTPs, deadlines, and action items), converts the summary into a PDF, and sends it to your Discord channel for quick access. Key Features Scheduled Automation**: Triggers daily at 8 PM to process emails from the last 24 hours. Gmail Integration**: Retrieves emails labeled "INBOX" and "IMPORTANT" using secure OAuth2 authentication (no hardcoded API keys). Smart Email Parsing**: Extracts essential fields (subject, sender, and plain text) while cleaning up URLs, extra lines, and formatting for clarity. AI-Powered Summarization**: Uses OpenAI's GPT-4.1-mini to create concise plain text and markdown summaries, highlighting urgent actions with "[Action Required]". PDF Conversion**: Converts the markdown summary into a professional PDF using PDF.co API. Discord Notifications**: Shares the PDF via a Discord webhook for seamless team communication. Why Use This Workflow? Save time by automating email triage and focusing on what matters. Stay organized with clear, actionable summaries delivered to Discord. Securely handle sensitive data with proper credential management. Perfect for teams, freelancers, or anyone managing high email volumes. Setup Instructions Configure Gmail OAuth2 credentials for secure access. Set up PDF.co API and Discord webhook credentials. Customize the schedule or filters as needed. Activate and let the workflow handle your daily email summaries!

Team Wellness - AI Burnout Detector Agent devex github 🎯 Demo sample report github action code alternative How it works 🎯 Overview A comprehensive n8n workflow that analyzes developer workload patterns from GitHub repositories to detect potential software engineering team burnout risks and provide actionable team wellness recommendations. This workflow automatically monitors team activity patterns, analyzes them using AI, and provides professional wellness reports with actionable recommendations which will automate GitHub issue creation and do email notifications for critical alerts. ✨ Features Automated Data Collection**: Fetches commits, pull requests, and workflow data from GitHub Pattern Analysis**: Identifies late-night work, weekend activity, and workload distribution AI-Powered Analysis**: Uses Groq's LLM for professional burnout risk assessment Automated Actions**: Creates GitHub issues and sends email alerts based on criticality Professional Guardrails**: Ensures objective, evidence-based analysis with privacy protection Scheduled Monitoring**: Weekly automated wellness checks 🏗️ Architecture 1. Data Collection Layer GitHub Commits API**: Fetches commit history and timing data GitHub Pull Requests API**: Analyzes collaboration patterns GitHub Workflows API**: Monitors CI/CD pipeline health 2. Pattern Analysis Engine Work Pattern Signals**: Late-night commits, weekend activity Developer Activity**: Individual contribution analysis Workflow Health**: Pipeline success/failure rates Collaboration Metrics**: PR review patterns and merge frequency 3. AI Analysis Layer Professional Guardrails**: Objective, evidence-based assessments Risk Assessment**: Burnout risk classification (Low/Medium/High) Health Scoring**: Team wellness score (0-100) Recommendation Engine**: Actionable suggestions for improvement 📊 Sample Output 📊 Team Health Report 📝 Summary Overall, the team is maintaining a healthy delivery pace, but there are emerging signs of workload imbalance due to increased after-hours activity. 🔢 Health Score Value:** 68 / 100 Confidence:** 87% Limitations:** Based solely on commit and PR activity; meeting load and non-code tasks not captured. 🔍 Observed Patterns ⏰ After-hours activity 29% of commits occurred between 10pm–1am (baseline: 12%). Confidence: 0.90 ⚠️ Systemic Risks Sustained after-hours work may indicate creeping burnout risk. Evidence: 3 consecutive weeks of elevated late-night commits. Confidence: 0.85 ✅ Recommendations 📌 Facilitate a team discussion on workload distribution and sprint commitments. (Priority: Medium) 🔔 Introduce automated nudges discouraging late-night commits. (Priority: Low) 🛠️ Rotate PR review responsibilities or adopt lightweight review guidelines. (Priority: High) 🚀 Quick Start Prerequisites n8n instance (cloud or self-hosted) GitHub repository with API access Groq API key Gmail account (optional, for email notifications) Setup Instructions Import Workflow Import the workflow JSON file into your n8n instance Configure Credentials GitHub API: Create a personal access token with repo access Groq API: Get your API key from Groq Console Gmail OAuth2: Set up OAuth2 credentials for email notifications Update Configuration { "repoowner": "your-github-username", "reponame": "your-repository-name", "period": 7, "emailreport": "your-email@company.com" } Test Workflow Run the workflow manually to verify all connections Check that data is being fetched correctly Verify AI analysis is working Schedule Automation Enable the schedule trigger for weekly reports Set up monitoring for critical alerts 🔧 Configuration Configuration Node Settings repoowner: GitHub username or organization reponame: Repository name period: Analysis period in days (default: 7) emailreport: Email address for critical alerts AI Model Settings Model**: openai/gpt-oss-120b (Groq) Temperature**: 0.3 (for consistent analysis) Max Tokens**: 2000 Safety Settings**: Professional content filtering 📈 Metrics Analyzed Repository-Level Metrics Total commits count Pull requests opened/closed Workflow runs and success rate Failed workflow percentage Work Pattern Signals Late-night commits (10PM-6AM) Weekend commits (Saturday-Sunday) Work intensity patterns Collaboration bottlenecks Developer-Level Activity Individual commit counts Late-night activity per developer Weekend activity per developer Workload distribution fairness 🛡️ Privacy & Ethics Professional Guardrails Never makes personal judgments about individual developers Only analyzes observable patterns in code activity data Always provides evidence-based reasoning for assessments Never suggests disciplinary actions or performance reviews Focuses on systemic issues and team-level recommendations Respects privacy and confidentiality of team members Data Protection No personal information is stored or transmitted Analysis is based solely on public repository data and public data All recommendations are constructive and team-focused Confidence scores indicate analysis reliability There is added redaction prompt. Note that LLM is not deterministic and usually, you will need to refine your own prompt to enhance difference level of criticality of privacy you need censored or displayed. In some cases ,you will need the engineer account names to help identify f2f conversation. 🔄 Workflow Nodes Core Nodes Schedule Trigger: Weekly automation (configurable) Config: Repository and email configuration Github Get Commits: Fetches commit history Github Get Workflows: Retrieves workflow runs Get Prs: Pulls pull request data Analyze Patterns Developer: JavaScript pattern analysis AI Agent: Groq-powered analysis with guardrails Update Github Issue: Creates wellness tracking issues Send a message in Gmail: Email notifications Data Flow Schedule Trigger → Config → Github APIs → Pattern Analysis → AI Agent → Actions 🚨 Alert Levels (Optional and Prompt configurable) Critical Alerts (Health Score < 90) GitHub Issue**: Automatic issue creation with detailed analysis Email Notification**: Immediate alert to team leads Slack Integration**: Critical team notifications Warning Alerts (Health Score 90-95) GitHub Issue**: Tracking issue for monitoring Slack Notification**: Team awareness message Normal Reports (Health Score > 95) Weekly Report**: Comprehensive team health summary Slack Summary**: Positive reinforcement message 🔧 Troubleshooting Common Issues GitHub API Rate Limits Solution: Use authenticated requests, implement rate limiting Check: API token permissions and repository access AI Analysis Failures Solution: Verify Groq API key, check model availability Check: Input data format and prompt structure Email Notifications Not Sending Solution: Verify Gmail OAuth2 setup, check email permissions Check: SMTP settings and authentication Workflow Execution Errors Solution: Check node connections, verify data flow Check: Error logs and execution history 🤝 Contributing Development Setup Fork the repository link above demo part Create a feature branch Make your changes Test thoroughly Submit a pull request Testing Test with different repository types Verify AI analysis accuracy Check alert threshold sensitivity Validate email and GitHub integrations 📄 License This project is licensed under the MIT License 🙏 Acknowledgments Groq**: For providing the AI analysis capabilities GitHub**: For the comprehensive API ecosystem n8n**: For the powerful workflow automation platform Community**: For feedback and contributions 📞 Support Getting Help Issues**: Create a GitHub issue for bugs or feature requests Discussions**: Use GitHub Discussions for questions Documentation**: Check the comprehensive setup guides Contact Email**:aiix.space.noreply@gmail.com LinkedIn**: SeanLon ⚠️ Important: This tool is designed for team wellness monitoring and should be used responsibly. Always respect team privacy and use the insights constructively to improve team health and productivity.

📄 PDF-to-Order Automation for Magento2 (Adobe commerce / open source) Description This n8n template demonstrates how to automatically process PDF purchase orders received via email and convert them into sales orders in Adobe Commerce (Magento 2) using Company Credit as the payment method. This is especially useful for B2B companies receiving structured orders from clients by email. Use cases include: Automating incoming B2B orders Reducing manual entry for sales teams Ensuring fast order creation in Adobe Commerce Reliable error handling and customer validation Good to know This workflow is tailored for Adobe Commerce, using the Company Credit payment method. It requires that the customer already has an account in Adobe Commerce and is authorized to use Company Credit. The same flow can be easily adapted for other payment methods (e.g. Purchase Order, Bank Transfer). No third-party services are required aside from n8n and access to Adobe Commerce with API credentials. How it works Trigger → Monitors an email inbox for incoming emails with PDF attachments. Extract PDF → Downloads the attached PDF and parses order data (e.g. SKU, quantity, customer reference). Validate Customer → Checks if the sender matches an existing customer in Adobe Commerce and verifies Company Credit eligibility. Create Order → Generates a new order in Magento using the extracted product data and Company Credit. Handle Errors → Logs issues and can notify a designated channel (email, Slack, etc.) if something goes wrong. Optional Enhancements → Add logging to Airtable, send confirmations to customers, or attach parsed order data to CRM entries. How to use A manual trigger is included as an example, but you can replace it with an IMAP Email Trigger, Gmail Trigger, or Webhook, depending on your setup. Customize the PDF parser node to fit your specific document layout and field structure. Configure Adobe Commerce API credentials in the HTTP nodes (or use environment variables). Optionally connect error steps to Slack, Email, or dashboards for monitoring. Requirements ✅ n8n instance (self-hosted or cloud) ✅ Adobe Commerce (Magento 2) instance with API access and Company Credit enabled ✅ Structured PDF templates used by your customers (Optional) Slack/Email/Airtable for notifications and logs Customising this workflow This workflow can be adapted for: Other payment methods (e.g. Purchase Orders, Online Payment) Magento open source ready. Just use your own payment method Alternate order sources (e.g. uploading PDFs via a portal instead of email) Parsing other document formats (e.g. CSV, Excel) Direct integration into ERP systems

🎓📺 Watching top YouTubers is now a mainstream way to learn, but watching dozens—or even hundreds—of videos isn’t realistic. This workflow gives learners a fast way to grasp an entire creator’s catalog at a glance. 📄🔗 Demo Google Sheet: click me 🧠🔍 YouTube Channel Research & Summarization Workflow 👥 Who’s it for 📚 Learners and educators who want a fast overview of a creator’s entire catalog. 🧩 Research, SEO, and content ops teams building an intelligence layer on top of YouTube channels. ⚙️ How it works 📝 Collects parameters via a Form Trigger. 🕷️ Launches an Apify YouTube Scraper, polls for completion, and fetches the final dataset. 💾 Saves the raw JSON to Google Drive, reloads it, and processes records in batches. 🗣️ Auto-selects English subtitles when available, extracts core metadata, and feeds transcript + metadata to an AI Summarization Agent. 📧 Sends a Gmail completion notification when done. 🛠️ How to set up 🔑 Connect credentials (once) 🗂️ Google Drive 📊 Google Sheets (OAuth enabled) ✉️ Gmail 🧠 DeepSeek API (or alternative LLM); Apify API (YouTube scraper actor) 📝 Configure the form 🔗 Youtuber_MainPage_URL (e.g., https://www.youtube.com/@n8n-io) 🔢 Total_number_video (tip: use the channel’s current total to crawl all) 🏷️ Storing_Name (used for the Drive filename & the Sheet tab) 🔑 Apify_API (Apify provides $5 free credit per month, which can crawl ~1,000 YouTube videos → https://console.apify.com/) 📧 Email 📁 Point Sheets & Drive 🔗 Create a Google Sheet and link it to all Google Sheets–related nodes. 💽 Select a Drive folder to save raw CSV backups (optional). 🎛️ How to customize the workflow 🈯 Subtitle logic:** Extend the language selector Select_Subtitle_Language to choose English, Mandarin, or another language. 🔔 Notifications:** Customize the Gmail subject/body, or add Slack/Teams alerts on success/failure with basic run stats. 📬 Need help? Contact me <owenlzyxg@gmail.com>

Employee Onboarding Automation with Multi-System Provisioning What this workflow does This workflow automates the end-to-end employee onboarding process by provisioning new hires across multiple internal systems and delivering a personalized welcome experience. Upon receiving new employee data via a webhook or form submission, it creates user accounts in Google Workspace, invites the employee to Slack, sets up a Notion onboarding page, generates an AI-powered welcome package, and notifies relevant stakeholders. All onboarding activities are logged for tracking and audit purposes. This template helps HR and People Operations teams reduce manual work, ensure consistency, and deliver a smooth onboarding experience from day one. How it works Employee data intake Triggered by a webhook or form submission. Collects employee details such as name, email, department, role, start date, and manager. Data preparation Generates a company email address. Assigns a unique onboarding ID. Standardizes employee information for downstream systems. Parallel account provisioning Creates a Google Workspace user account. Sends an invitation to the Slack workspace. Creates a dedicated Notion onboarding page. Executes these steps in parallel to minimize onboarding time. Provisioning result compilation Consolidates account creation statuses. Produces a single onboarding summary object. AI-powered welcome package Generates: A personalized welcome message A suggested first-week schedule Practical tips for success in the role Formats content for email delivery. Notifications & communication Sends a welcome email to the employee (if a personal email is provided). Notifies HR or People Ops via Slack. Logs onboarding details to Google Sheets. Webhook response Returns a structured JSON response confirming onboarding initiation. Setup requirements Before activating this workflow, ensure the following are configured: Enable the webhook endpoint and connect it to your form or HR system. Configure Google Workspace Admin API access. Set up Slack workspace permissions for user invitations. Define a parent Notion page for onboarding content. Prepare Google Sheets for onboarding logs. Customize email templates, departments, and org unit paths as needed. Required credentials This workflow requires the following credentials to be configured in n8n: Google API** (Google Workspace user provisioning) Slack** (workspace invitations and HR notifications) Notion** (onboarding page creation) OpenAI** (AI-generated welcome content) Gmail** (sending welcome emails) Google Sheets** (onboarding tracking and logs) Customization ideas Add role-based access provisioning (VPN, GitHub, Jira, etc.). Delay account creation until a specific start date. Generate localized onboarding content by region or language. Integrate with HRIS tools such as BambooHR or Workday. Add approval steps for managers or IT before provisioning. Who this is for HR & People Operations teams IT & Identity management teams Startups and scaling organizations Companies seeking consistent, automated onboarding This template provides a scalable, repeatable onboarding foundation that connects HR systems, IT provisioning, and AI-driven communication into a single automated workflow.

How It Works This workflow automates inventory management and customer engagement for e-commerce businesses and retail operations managing multiple product categories. It solves the critical challenge of maintaining optimal stock levels while personalizing customer communications across order fulfillment, product recommendations, and support interactions. The system processes webhook-triggered data across four parallel streams (orders, reviews, inventory, social media), applies AI-powered analysis for sentiment extraction, pricing optimization, promotion targeting, and demand forecasting, then distributes personalized communications through email campaigns and Slack/Microsoft Teams notifications. This eliminates manual inventory tracking, reduces stockouts, and delivers data-driven customer engagement. Setup Steps Configure webhook URLs for orders, reviews, inventory systems, and social media platforms Add AI model API credentials (OpenAI/Anthropic) for sentiment, pricing Connect CRM database for customer profile management and segmentation Set up email service (Gmail/SendGrid) with campaign templates for personalized communications Integrate Slack workspace or Microsoft Teams channels for internal inventory alerts Prerequisites Active e-commerce platform with webhook support, AI service API keys Use Cases Multi-channel retailers optimizing stock across locations, subscription box services Customization Adjust AI prompts for industry-specific sentiment rules, modify inventory thresholds for restocking alerts Benefits Reduces inventory management overhead by 70%, prevents stockouts through predictive forecasting

AI-Powered HR Candidate Evaluation Agent with LinkedIn Data Enrichment in CSV/XLSX Format 🎯 Overview Transform your manual hiring process into an intelligent evaluation system that saves 15-20 minutes per candidate! This workflow automates the entire candidate assessment pipeline - from CSV/XLSX upload to AI-powered scoring with LinkedIn insights. When you upload a candidate list, this workflow automatically: 📊 Converts your file into a formatted Google Sheet with RTL support 🔍 Researches each candidate's recent LinkedIn posts via Apify 🤖 Evaluates candidates using GPT-4.1 with context-aware scoring (0-100) 💬 Generates professional Hebrew explanations for each score 📈 Auto-sorts by score and applies professional formatting ⚠️ Sends error alerts to keep everything running smoothly Cost per candidate: ~$0.05 | Time saved: 15-20 minutes each 👥 Who's it for? HR teams drowning in candidate applications Recruitment agencies needing consistent evaluation criteria Hiring managers seeking data-driven candidate insights Companies looking to scale their team Anyone tired of manual spreadsheet juggling ⚡ How it works Form submission triggers with CSV/XLSX upload Google Drive stores the file and creates a new Sheet Data extraction processes the file content AI Agent loops through each candidate: Fetches up to 3 recent LinkedIn posts via Apify Analyzes qualifications against job requirements Generates evaluation score and Hebrew explanation Sheet formatting applies filters, sorting, and styling Error handling notifies admin of any issues 🛠️ Setup Instructions Time to deploy: 15 minutes Requirements: Google account (Drive + Sheets access) OpenAI API key (GPT-4.1 access) Apify API key (for LinkedIn scraping) Gmail account (for error notifications) Step-by-step: Import this template into your n8n instance Configure Google credentials: Connect Google Drive OAuth2 Connect Google Sheets OAuth2 Add OpenAI API key to the GPT-4.1 node Set up Apify credentials for LinkedIn scraping Configure Gmail for error alerts (update email in "Send a message" node) Update folder IDs in Google Drive nodes to your folders Test with a sample CSV containing 2-3 candidates Activate and share the form URL with your team! 📋 Input File Format Your CSV/XLSX should include these columns (Hebrew): שם פרטי (First name) שם משפחה (Last name) חשבון לינקדאין (LinkedIn URL) Your custom evaluation questions 🎨 Customization Options Easy tweaks: Scoring criteria**: Modify the AI agent's system message Language**: Switch from Hebrew to any language Scoring rubric**: Adjust the 50/25/15/10 weighting LinkedIn posts**: Change from 3 posts to more/fewer Sheet styling**: Customize colors and formatting Advanced modifications: Add integration with your ATS (Greenhouse, Lever, etc.) Connect to Slack for real-time notifications Add multiple evaluation agents for different roles Implement multi-language support Add candidate email automation 💡 Pro Tips Better LinkedIn data**: Ensure candidates provide complete LinkedIn URLs (not just usernames) Consistent scoring**: Run batches of similar roles together for normalized scoring Cost optimization**: Adjust Apify settings to fetch only essential data Scale smartly**: Process in batches of min 10-20 for optimal performance ⚠️ Important Notes LinkedIn scraping respects Apify's rate limits Scores are relative within each batch - don't compare across different job roles The workflow handles both CSV and XLSX formats automatically Error notifications help you catch issues before they cascade 📊 Expected Results After implementation, expect: Data-driven evaluation across candidates Professional explanation for hiring decisions Happy recruiters who can focus on human connection Built with ❤️ by Elay Guez

AI-Powered Feedback Automation with PDF Reports & Team Notifications Transform customer feedback into actionable insights automatically with AI analysis, professional PDF reports, personalized emails, and real-time team notifications. Table of Contents Overview Features Demo Prerequisites Quick Start Configuration Usage Troubleshooting License Overview AI-Powered Feedback Automation is a complete, production-ready n8n workflow that automatically processes customer feedback submissions with artificial intelligence, generates beautiful branded PDF reports, sends personalized email responses, logs data for analytics, and notifies your team in real-time. What Problem Does This Solve? Manual feedback processing is time-consuming and inconsistent. This workflow eliminates all manual work by: Automatically analyzing** sentiment and extracting key insights using OpenAI Generating professional** PDF reports with custom branding Sending personalized** thank-you emails to customers Logging everything** to Google Sheets for analytics and reporting Notifying your team** instantly via Slack with actionable summaries Perfect For Product Teams** - Collect and analyze user feedback systematically Educational Institutions** - Process student/parent feedback efficiently Customer Support** - Track customer satisfaction and sentiment trends E-commerce** - Manage product reviews and customer suggestions Healthcare** - Collect patient feedback and satisfaction scores Event Management** - Gather attendee feedback post-event Consulting Firms** - Streamline client feedback collection Features AI-Powered Analysis Sentiment Classification** - Automatically categorizes feedback as Positive, Neutral, or Negative Key Highlights Extraction** - Identifies the most important points from customer comments Actionable Recommendations** - AI generates specific suggestions based on feedback Executive Summaries** - Creates concise 2-3 sentence overviews of each submission Professional Report Generation Beautiful PDF Reports** - Branded, professional documents with custom styling Visual Elements** - Star ratings, color-coded sentiment badges, organized sections Responsive Design** - Mobile-friendly and print-optimized layouts 30-Day Hosting** - PDF reports automatically hosted with expiration dates Automated Email Communications Personalized Messages** - Thank-you emails customized with customer name and feedback PDF Attachments** - Direct download links to full feedback reports Sentiment Indicators** - Color-coded visual feedback summaries Professional Templates** - Modern, responsive email designs Data Logging & Analytics Google Sheets Integration** - Automatic logging of all feedback submissions Complete Audit Trail** - Tracks submission IDs, timestamps, and processing status Analytics Ready** - Structured data perfect for dashboards and trend analysis Historical Records** - Permanent storage of all feedback data Team Notifications Slack Integration** - Real-time alerts to team channels Rich Formatting** - Structured messages with highlights and action items Direct Links** - Quick access to full PDF reports from Slack Thread Discussions** - Enable team conversations around feedback Robust Error Handling Email Validation** - Automatically checks and handles invalid email addresses Fallback Mechanisms** - Continues workflow even if email sending fails Data Cleaning** - Sanitizes and normalizes all input data Graceful Degradation** - AI parsing failures handled with intelligent fallbacks Demo Workflow Overview User Submits Feedback ↓ Data Cleaning & Validation ↓ AI Sentiment Analysis (OpenAI) ↓ HTML Report Generation ↓ PDF Conversion ↓ Email Validation ─┬─ Valid → Send Email └─ Invalid → Skip ↓ Log to Google Sheets ↓ Notify Team (Slack) ↓ Webhook Response Sample Input { "name": "Sarah Johnson", "email": "sarah@example.com", "rating": 4, "comments": "Great product! Delivery was a bit slow but customer service was helpful.", "suggestions": "Improve shipping speed and tracking updates." } Sample Output ✅ AI Analysis: "Positive" sentiment with 3 key highlights ✅ PDF Report: Professional 2-page document with branding ✅ Email Sent: Personalized thank-you message delivered ✅ Data Logged: New row added to Google Sheet ✅ Team Notified: Slack message with summary posted ✅ Webhook Response: 200 OK with submission details Prerequisites Required Services & Accounts n8n Instance (v0.220.0 or higher) Self-hosted or n8n Cloud Installation Guide OpenAI Account API key with GPT-3.5-turbo or GPT-4 access Sign Up Google Account (Gmail + Google Sheets) OAuth2 setup for Gmail API OAuth2 setup for Google Sheets API Setup Guide Slack Workspace Admin access to create apps or OAuth Bot token with chat:write and channels:read scopes Create Slack App HTML to PDF API Service GET at: PDFMunk API key required VerifiEmail API GET at: VerfiEmail API key required Quick Start 1. Import Template Option A: Import via URL Copy the workflow JSON URL and paste in n8n: Settings → Import from URL → [Paste URL] Option B: Import via File Download workflow.json In n8n: Workflows → Import from File Select the downloaded JSON file Click "Import" 2. Configure Credentials (5 minutes) Navigate to: Settings → Credentials and add: ✅ OpenAI API - Add API key from OpenAI dashboard ✅ Gmail OAuth2 - Connect and authorize your Gmail account ✅ Google Sheets OAuth2 - Use same Google account ✅ Slack OAuth2 - Install app to workspace and authorize ✅ HTML to PDF API - Add API key from your PDF service ✅ VerifiEmail API - Add API key from VerifiEmail dashboard 3. Create Google Sheet (2 minutes) Create a new Google Sheet named "Feedback Log" with these column headers: Submission ID | Timestamp | Name | Email | Rating | Sentiment | Comments | Suggestions | AI Summary | PDF URL | PDF Available Until | Email Sent 4. Configure Workflow (3 minutes) Open the imported workflow Click "Log Feedback Data" node Select your "Feedback Log" spreadsheet Click "Notify Team" node Select your Slack channel (e.g., #feedback) 5. Test & Activate (5 minutes) Execute the "Webhook" node to get test URL Send test POST request (see test data below) Verify all nodes execute successfully Check email, Google Sheet, and Slack Click "Active" toggle to enable workflow Total Setup Time: ~15-20 minutes Configuration Webhook Configuration The workflow receives feedback via POST webhook: URL Format: https://your-n8n-domain.com/webhook/feedback-submission Expected Payload: { "name": "string (required)", "email": "string (optional, validated)", "rating": "integer 1-5 (required)", "comments": "string (optional)", "suggestions": "string (optional)" } Usage Testing the Workflow Using Postman/Insomnia: Create new POST request URL: https://your-n8n-domain.com/webhook/feedback-submission Headers: Content-Type: application/json Body (raw JSON): { "name": "Test User", "email": "your-email@example.com", "rating": 5, "comments": "This is a test feedback submission. Everything works great!", "suggestions": "Maybe add more features in the future." } Send request Expected response (200 OK): { "success": true, "message": "Thank you for your feedback! We've sent you a detailed report via email.", "data": { "submissionId": "FB-1234567890123-abc123xyz", "name": "Test User", "email": "your-email@example.com", "rating": "5", "sentiment": "Positive", "emailSent": "true", "reportUrl": "https://generated-pdf-url.com/report.pdf", "reportAvailableUntil": "2025-11-10" } } Using cURL: curl -X POST https://your-n8n-domain.com/webhook/feedback-submission \ -H "Content-Type: application/json" \ -d '{ "name": "Sarah Johnson", "email": "sarah@example.com", "rating": 4, "comments": "Great product! Delivery was a bit slow but customer service was helpful.", "suggestions": "Improve shipping speed and tracking updates." }' Monitoring & Maintenance Daily: Check Slack for new feedback notifications Review Google Sheet for any anomalies Weekly: Verify workflow execution success rate Check OpenAI API usage and costs Review sentiment trends in Google Sheet Monthly: Analyze feedback patterns and trends Update AI prompts if needed Check PDF service usage limits Review and optimize workflow performance Best Practices Rate Limiting Monitor for spam submissions Add rate limiting to webhook if needed Use n8n's built-in throttling Data Privacy Ensure GDPR/privacy compliance Add data retention policies Implement data deletion workflow Error Handling Set up error notifications Create error logging workflow Monitor execution failures Performance Keep Google Sheet under 50,000 rows Archive old data quarterly Use database for high volume (1000+/month) Troubleshooting Common Issues Issue 1: Webhook Not Receiving Data Symptoms: Webhook node shows no executions Forms submit but nothing happens Solutions: ✅ Verify workflow is Active (toggle at top right) ✅ Check webhook URL is correct in form ✅ Test webhook with Postman/cURL first ✅ Check n8n logs for errors: Settings → Log Streaming ✅ Verify firewall/network allows incoming webhooks Issue 2: OpenAI Node Fails Symptoms: Error: "API key invalid" Error: "Insufficient credits" Node times out Solutions: ✅ Verify API key is correct and active ✅ Check OpenAI account has sufficient credits ✅ Check API usage limits: platform.openai.com/usage ✅ Increase node timeout in workflow settings ✅ Try with shorter feedback text Issue 3: PDF Not Generating Symptoms: "PDF generation failed" error Empty PDF URL 404 when accessing PDF Solutions: ✅ Verify PDF API key is valid ✅ Check API service status ✅ Verify HTML content is valid (test in browser) ✅ Check API usage limits/quota ✅ Try alternative PDF service Issue 4: Email Not Sending Symptoms: Gmail node shows error Email doesn't arrive "Permission denied" error Solutions: ✅ Re-authenticate Gmail OAuth2 credential ✅ Check email address is valid ✅ Check spam/junk folder ✅ Verify Gmail API is enabled in Google Console ✅ Check daily sending limits not exceeded ✅ Test with different email address Issue 5: Google Sheets Not Updating Symptoms: No new rows added "Spreadsheet not found" error Permission errors Solutions: ✅ Verify spreadsheet ID is correct ✅ Check sheet name matches exactly (case-sensitive) ✅ Verify column headers match exactly ✅ Re-authenticate Google Sheets credential ✅ Check spreadsheet isn't protected/locked ✅ Verify spreadsheet isn't full (limit: 10M cells) Issue 6: Slack Not Posting Symptoms: Slack node fails Message doesn't appear in channel "Channel not found" error Solutions: ✅ Verify bot is invited to channel: /invite @BotName ✅ Check bot has chat:write permission ✅ Re-authenticate Slack credential ✅ Verify channel ID is correct ✅ Check Slack workspace isn't on free plan limits ✅ Test with different channel Debugging Tips Enable Debug Mode Settings → Executions → Save execution progress Watch each node execute step-by-step Check Execution Logs Click on failed node View "Input" and "Output" tabs Check error messages Test Nodes Individually Click "Execute Node" on each node Verify output before proceeding Use Browser Console Open Developer Tools (F12) Check for JavaScript errors Monitor network requests Enable Verbose Logging For self-hosted n8n N8N_LOG_LEVEL=debug npm start 📄 License This template is licensed under the MIT License - see the LICENSE file for details.