by Automate With Marc
Auto-Edit Google Drive Images with Nano Banana + Social Auto-Post Drop an image into Google Drive and let this workflow handle the rest: it auto-cleans and enhances the image with Google’s Nano Banana (via Wavespeed API), generates a catchy caption with GPT-5, and publishes directly to your connected social accounts using Postiz. 👉 Watch step-by-step video tutorials of workflows like these on *https://www.youtube.com/watch?v=4wk6PYgBtBM&list=PL05w1TE8X3bb1H9lXBqUy98zmTrrPP-s1* What it does Triggers from Google Drive when a new image is uploaded Sends the image to Nano Banana to declutter, brighten, and make it real-estate/photo-listing ready Polls for the edited result until it’s complete Logs the edited image URL into Google Sheets for tracking Downloads and uploads the edited image into Postiz media library Generates an engaging caption with GPT-5 Caption Agent Publishes instantly to Instagram (can be extended to TikTok, LinkedIn, etc.) Perfect for Real-estate agents posting property shots Ecommerce sellers updating product catalogs Social media marketers needing fast, polished posts Apps & Services Tools Used Google Drive (Trigger) Wavespeed API – Google Nano Banana (Image editing) Google Sheets (Logging) Postiz (Social scheduling/posting) OpenAI GPT-5 (Caption agent) Setup Connect your Google Drive and select the upload folder. Add your Wavespeed API key for Nano Banana. Connect Google Sheets for logging. Add Postiz API credentials and set the integration ID for your channel(s). Enter your OpenAI API key for GPT-5 captioning. Customization Adjust the edit prompt for different use cases (e.g., product cleanup, lighting tweaks). Change Postiz post type to scheduled instead of “now.” Add more Postiz posts for multi-platform publishing. Insert an approval loop (Slack/Email) before posting. Logs Edited Image Log (Sheets): stores final image URL + timestamp. Publishing Log (Sheets): tracks workflow status per asset. Notes Sticky notes in the template explain each major block. Replace sample IDs with your own (folder IDs, sheet IDs, Postiz integration). Keep all API keys in n8n Credentials, not in node parameters.
by Davide
This workflow automates analyzing Gmail threads and drafting AI-powered replies with the new model Anthropic Sonnet 4.5. This workflow automates the process of analyzing incoming emails and generating context-aware draft replies by examining the entire email thread. Key Advantages ✅ Time-Saving – Automates repetitive email replies, reducing manual workload. ✅ Context-Aware Responses – Replies are generated using the entire email thread, not just the latest message. ✅ Smart Filtering – The classifier prevents unnecessary drafts for spam or promotional emails. ✅ Human-in-the-Loop – Drafts are created instead of being sent immediately, allowing manual review and corrections. ✅ Scalable & Flexible – Can be adapted to different accounts, reply styles, or workflows. ✅ Seamless Gmail Integration – Directly interacts with Gmail threads and drafts via OAuth. How it Works This workflow automates the process of analyzing incoming emails and generating context-aware draft replies by examining the entire email thread. Trigger & Initial Filtering: The workflow is automatically triggered every minute by the Gmail Trigger node, which detects new emails. For each new email, it immediately performs a crucial first step: it uses an AI Email Classifier to analyze the email snippet. The AI determines if the email is a legitimate message that warrants a reply (categorized as "ok") or if it's spam, a newsletter, or an advertisement. This prevents the system from generating replies for unwanted emails. Context Aggregation: If an email is classified as "ok," the workflow fetches the entire conversation thread from Gmail using the threadId. A Code Node then processes all the messages in the thread, structuring them into a consistent format that the AI can easily understand. AI-Powered Draft Generation: The structured conversation history is passed to the Replying email Agent with Sonnet 4.5. This agent, powered by a language model, analyzes the entire thread to understand the context and the latest inquiry. It then drafts a relevant and coherent HTML email reply. The system prompt instructs the AI not to invent information and to use placeholders for any missing details. Draft Creation: The final step takes the AI-generated reply and the original email's metadata (subject, recipient, threadId) and uses them to create a new draft email in Gmail. This draft is automatically placed in the correct email thread, ready for the user to review and send. Set up Steps To implement this automated email reply system, you need to configure the following: Configure Gmail & OpenAI Credentials: Ensure the following credentials are set up in your n8n instance: Gmail OAuth2 Credentials: The workflow uses the same Gmail account for the trigger, fetching threads, and creating drafts. Configure this in the "Gmail Trigger," "Get a thread," and "Create a draft" nodes. OpenAI API Credentials: Required for both the "Email Classifier". Provide your API key in the respective OpenAI Chat Model nodes. Anthropic API Credentials: Required for the main "Replying email Agent." Provide your API key in the respective Antrhopic Chat Model nodes. Review AI Classification & Prompting: Email Filtering: Check the categories in the Email Classifier node. The current setup marks only non-advertising, non-newsletter emails as "ok." You can modify these categories to fit your specific needs and reduce false positives. Reply Agent Instructions: Review the system message in the Replying email Agent. You can customize the AI's persona, tone, and instructions (e.g., making it more formal, or instructing it to sign with a specific name) to better align with your communication style. Need help customizing? Contact me for consulting and support or add me on Linkedin.
by WeblineIndia
Send daily applicant digest by role from Gmail to hiring managers with Google Gemini This workflow automatically collects all new job application emails from your Gmail labeled as applicants in the last 24 hours. Every day at 6:00 PM (Asia/Kolkata), it extracts structured details (name, email, phone, role, experience, skills, location, notice, summary) from each applicant (using Gemini AI or OpenAI). It then groups applicants by role and manager, compiles a neat HTML table digest for each manager and emails them a single summary — so hiring managers get everything they need, at a glance, in one place. Who’s It For Recruiters and hiring managers tired of digging through multiple application threads. Small HR teams / agencies not yet on a full applicant tracking system. Anyone wanting a consolidated, role-targeted applicant update each day. Teams that want to automate candidate triage using Google Workspace and AI. How It Works Schedule Trigger (6PM IST): Runs automatically at 18:00 India time. Fetch Applicant Emails: Reads Gmail for emails labeled 'applicants' from the past 24 hours. Prepare Email Text: Converts email content to plain text for reliable AI extraction. Extract Applicant Details: Gemini/OpenAI extracts applicant’s info in structured JSON. Assign Manager Emails: Routes each applicant to the correct manager via role→email mapping or fallback. Group & Build HTML Tables: Organizes applicants by manager and role, builds summary tables. Send Digest to Managers: Sends each manager one HTML summary email for their new applicants. How to Set Up Create/verify Gmail label applicants and set up filters to route job emails there. Import the workflow: Use your Google/Gmail and Gemini/OpenAI accounts as credentials. Configure connections: Gmail with OAuth2 (IMAP not required, uses Gmail API) Gemini or OpenAI API key for extraction Set role→manager mapping in the “Assign Manager Emails” node (just edit the map!). Adjust time / defaults: Edit schedule and fallback email if you wish. Test it: Send yourself a test application, label it, check workflow logs. Requirements Gmail account (with OAuth2 enabled and 'applicants' label set up) Gemini or OpenAI API key for structured AI extraction n8n instance (self-hosted or cloud) SMTP credentials (if using direct email instead of Gmail node) At least one valid hiring manager email mapped to a role How to Customize the Workflow Centralize config with a Set node (label name, fallback/manager email, model name, schedule). Add attachment-to-text conversion for applications with resume attachments. Normalize role names in the mapping code for more robust routing. Enable additional delivery: Slack, Teams, Google Sheets log, extra Cron for mid-day urgents. Refine AI extraction prompt for specific fields (add portfolio URL, etc.). Change schedule for daily, weekly or per-role timing. Add‑Ons / Extensions Resume Text Extraction:** Add PDF/DOCX to text parsing for attachment-only applications. ChatOps:** Send the summary to Slack or Teams channels along with/instead of email. Applicant Logging:** Auto-log every applicant/action into Google Sheets, Notion or Airtable. Multi-timezone:** Duplicate/modify the Cron trigger for different manager regions or urgency levels. Use Case Examples Tech Hiring:** Java, Python, Frontend candidates are automatically routed to their respective leads. Small Agency:** All applications summarized for reviewers, with per-role breakdowns. HR Operations:** Daily rollups sent before hiring sync, facilitating fast decision-making. Common Troubleshooting | Issue | Possible Cause | Solution | |-----------------------------------------|----------------------------------------------------------|-------------------------------------------------------------| | No emails processed | No 'applicants' label or wrong time window | Check Gmail filters and adjust search query in fetch node | | All digests go to fallback manager | Incorrect or missing role → manager mapping | Normalize role text in assignment node, expand map | | AI Extraction returns bad/missing JSON | Wrong prompt, high temperature or missing field names | Tighten prompt, lower temperature, check example response | | Duplicate/Old Emails appear | Date filter not correct | Use 'newer_than:1d' and keep 'mark as read' in email node | | SMTP/Gmail Send errors | Auth problem, quota or app password missing | Use OAuth2, check daily send caps and app password settings | | Blank or partially filled summary table | AI unable to parse poorly formatted/empty email | Improve sender email consistency, add fallback handling | | Attachments not processed | No attachment extraction node | Add attachment-to-text parsing before AI node | Need Help? If you get stuck, need help customizing a mapping or adding nodes or want to integrate extra steps (e.g., resume text, Slack), just ask! We're happy to guide you step by step, review your workflow, or help you troubleshoot any errors. Contact WeblineIndia — Your n8n Automation partner!
by Ryo Sayama
Who is this for This workflow is designed for sales professionals, account managers, and small business owners in Japan who frequently exchange business cards. Instead of manually entering contact details, you can instantly capture and store them by sending a photo to LINE. What this workflow does When a user sends a business card photo via LINE, the workflow uses Google Gemini Vision to extract key contact details — name, company, title, email, phone, and address — and saves them as a new row in Google Sheets. The team is notified in Slack, and a thank-you email is automatically sent to the new contact via Gmail. Finally, a confirmation message is sent back to the user on LINE. How to set up Connect your LINE Messaging API credentials in n8n Set your LINE channel webhook URL in the LINE Developer Console Add your Google Gemini API key (free tier available) Share your target Google Sheet with the service account email Connect your Slack workspace and set the target channel Connect your Gmail account Requirements LINE Messaging API account (free) Google Gemini API key (free tier) Google Sheets (any Google account) Slack workspace Gmail account How to customize Change the Gemini prompt in the "Extract card data" node to capture additional fields. Modify the Slack message format or Gmail template to match your team's tone.
by Rahul Joshi
Description This workflow automates personalized candidate communication for both shortlisted and rejected applicants. It fetches candidate details, processes resumes, checks for errors, and uses GPT-4o to generate professional HTML emails. Shortlisted candidates receive congratulatory onboarding plans, while rejected candidates receive polite rejections with learning resources. What This Template Does (Step-by-Step) ⚡ Manual Trigger – Starts the workflow execution. 📑 Candidate Data Fetch (Google Sheets) – Pulls structured candidate data (name, email, resume link, skills, job info, status). 📥 Resume Downloader (Google Drive) – Downloads candidate resumes from sheet links. ✅ Resume File Check (If Condition) – Ensures the resume file is valid before proceeding. ⚠️ Error Logging (Google Sheets) – Records failed or missing resumes in a dedicated sheet for audit. 📄 PDF → Text Extractor – Extracts raw resume text for deeper AI analysis. 🧩 Candidate Data Builder (Code Node) – Combines Google Sheets data with extracted resume text into a single enriched JSON object. 🎯 Shortlisted vs Rejected (If Condition) – Splits candidates into two flows based on their status field. Shortlisted Path 🎉 Congrats + Onboarding Plan (LLM Chain) – GPT-4o generates a congratulatory HTML email including: Identified skill gaps Recommended online courses (Coursera/Udemy/LinkedIn Learning) Next onboarding steps 📧 Candidate Mailer – Shortlisted (Gmail) – Sends the onboarding email directly to the candidate. Rejected Path 🙏 Polite Rejection + Learning Plan (LLM Chain) – GPT-4o generates a professional rejection email including: Empathetic rejection message Constructive feedback on skill gaps Learning resources to improve for future opportunities 📧 Candidate Mailer – Rejected (Gmail) – Sends the polite rejection + learning plan to the candidate. Prerequisites Google Sheets (candidate database + error log) Google Drive (resume storage) Gmail API (for sending candidate emails) Azure OpenAI (GPT-4o-mini model access) Key Benefits ✅ Automates candidate communication (both shortlisted & rejected) ✅ Delivers professional, HTML-ready emails ✅ Enhances candidate experience with personalized learning plans ✅ Prevents silent rejections by providing constructive resources ✅ Improves employer branding with empathetic communication ✅ Error resilience via logging and validation steps Perfect For Recruitment teams managing high candidate volume Companies looking to humanize rejections HR departments that want automated but personalized communication Organizations investing in candidate experience & employer brand
by Apurva Mishra
AI Email Manager: Auto Summary, Labeling, and CRM Logging via n8n + Gemini Overview This workflow turns your Gmail inbox into a fully autonomous AI Email Agent that reads, summarizes, categorizes, and organizes emails in real-time. Built with n8n, Google Gemini, Notion, and Google Sheets, it’s perfect for founders, freelancers, and agencies who receive a ton of emails daily and want to automate the triage process without losing control. How It Works Gmail Trigger — Detects new incoming emails. Process Email Data — Extracts sender info, subject, and content in a clean structured format. AI Email Analyzer — Uses Gemini AI to summarize the email and decide the most relevant label (e.g., Project Updates, Client Requests, Invoices, etc.). Create Gmail Label (if not exists) — Dynamically creates a new label if the AI recommends one that doesn’t exist. AI Agent + Add Label to Email — Applies the correct Gmail label automatically using the message ID. Logs in Notion & Google Sheets — Every processed email (summary, sender, date, label) is logged for tracking and analytics. Who It’s For Entrepreneurs & Founders — Manage investor, client, and product update emails automatically. Agencies & Teams — Classify and track client emails effortlessly across projects. Freelancers & Consultants — Get AI summaries and organize leads without manually labeling emails. Tech Builders — Anyone building AI automation tools and SaaS products around inbox management.
by Jitesh Dugar
Intelligent Financial Invoice Hub: AI Parsing, 3-Way Matching & Multi-Channel Alerting 🎯 Description This is an enterprise-grade solution designed for complex finance departments. It automates the entire accounts payable lifecycle by combining secure document handling, intelligent vendor mapping, 3-way reconciliation, and a sophisticated multi-channel notification engine. ✨ What This Workflow Does Multi-Channel Ingestion - Consolidates invoices arriving via Gmail, legacy IMAP servers, and direct vendor portal webhooks into a single processing stream. Advanced Security Layer - Automatically retrieves rotating encryption keys from a secure database and uses the HTML to PDF (Unlock) node to decrypt protected vendor statements. Fuzzy Vendor Identification - Uses intelligent string analysis to identify vendors despite name variations (e.g., "Amazon" vs. "AWS"), ensuring data consistency. Automated 3-Way Matching - Fetches the associated Purchase Order (PO) and Delivery Receipt, then uses the HTML to PDF (Merge) engine to create a verified "Audit Bundle" for compliance. AI-Driven Data Extraction - Parses line-item details, converts international currencies using live exchange rates, and detects early payment discounts to optimize cash flow. Enterprise Notification Engine - Slack: Instant escalation for high-value outliers (e.g., >$10k) or urgent invoices. Microsoft Teams: Direct alerts to Department Heads when items impact their specific budgets. Gmail: Delivers a daily processing success digest to the Finance Lead. 💡 Key Features 3-Way Reconciliation:** Prevents fraud and overpayment by validating quantities and prices across three distinct documents before ERP synchronization. Encrypted Document Handling:** Seamlessly manages password-protected PDFs without manual intervention. Currency Intelligence:** Automatically handles international vendor payments with real-time conversion and tax mapping. Budget Allocation:** Smartly assigns costs to specific department codes and project tags in your accounting software. 🔧 Technical Highlights Binary Buffer Management:** High-performance handling of multiple large PDF streams during the merge process. Fuzzy Matching Logic:** Robust vendor recognition that handles typos and naming variations. Hybrid Trigger Support:** Reliable execution via polling (Email) and real-time events (Webhooks). Modular Architecture:** Easy to adapt for Xero, QuickBooks, or custom SQL databases. 📦 What You'll Need HTML to PDF Node - Essential for the Unlock and Merge operations. Google Sheets - To serve as the Vendor Vault (decryption keys) and Master Audit Log. ERP Credentials - Access to Xero, QuickBooks, or Sage for bill creation. Communication Tools - Slack, Microsoft Teams, and a Gmail account. 🚀 Benefits ✅ Zero Manual Data Entry - Complete "Email-to-ERP" automation saves hours of administrative work. ✅ Eliminate Overpayments - 3-way matching ensures you only pay for exactly what was ordered and received. ✅ Real-Time Financial Visibility - Department heads are notified the moment their budget is impacted. ✅ Audit Readiness - Automatically maintains a complete digital paper trail for every single invoice. 🎨 Customization Options Thresholds:** Adjust the "High Value" IF-node to match your internal approval policies. Channels:** Easily swap Slack for Discord or Teams for SMS alerts (via Twilio). Currency:** Add or remove currency pairs in the Intelligence Engine code node. Tags: #finance #accounting #xero #3-way-match #pdf-automation #slack #enterprise #security Category: Finance & Accounting Difficulty: Advanced
by Gilbert Onyebuchi
A complete email campaign automation system featuring dual-mode access control (Demo/Pro), usage tracking, and professional email delivery. Perfect for SaaS products, marketing agencies, or anyone building newsletter tools with freemium models. WHAT IT DOES This workflow manages email newsletter campaigns with built-in rate limiting for free users and unlimited access for premium users. It automatically tracks daily usage, manages user data in Google Sheets, delivers emails via SendGrid, and sends real-time notifications through Telegram. KEY FEATURES Dual-Mode System: Demo mode (5 emails/day) and Pro mode (unlimited) Smart Rate Limiting: Automatic daily counter reset User Management: Automatic new user registration and tracking Google Sheets Integration: Stores user data, send counts, and usage history Professional Email Delivery: SendGrid integration for reliable sending Real-Time Monitoring: Telegram notifications for every send Ready-to-Use Templates: 4 professional email designs included (Modern, Professional, Promotional, Newsletter) Live Preview: See exactly how emails look before sending HTML Export: Copy email HTML for use in any platform HOW IT WORKS User accesses the Email Newsletter Builder web form Designs email using one of 4 professional templates Chooses Demo or Pro mode Webhook receives the email data and configuration Workflow checks mode (Demo/Pro) For Demo mode: Queries Google Sheets for user email Checks if user exists and validates daily limit (<5 sends) If new user: Creates database entry If existing user + under limit: Increments counter If limit reached: Returns error message For Pro mode: Sends immediately without limits SendGrid delivers the email Google Sheets updates with new send count and timestamp Telegram notification sent to admin Success/error response returned to user SETUP REQUIREMENTS Google Sheets account (free) SendGrid account (free tier: 100 emails/day) Telegram account + bot (free) n8n instance (self-hosted or cloud) SUPPORT & FEEDBACK Questions or issues? Connect with me on LinkedIn Want to see it in action? Try the live demo: Click here ⭐ If you find this workflow helpful, please give it a rating and share your feedback!
by NodeAlchemy
🧾 Short Description An AI-powered customer support workflow that automatically triages, summarizes, classifies, and routes tickets to the right Slack and CRM queues. It sends personalized auto-replies, logs results to Google Sheets, and uses a DLQ for failed cases. ⚙️ How It Works Trigger: Captures messages from email or form submissions. AI Triage: Summarizes and classifies issues, scores urgency, and suggests next steps. Routing: Directs to Slack or CRM queue based on type and priority. Logging: Records summaries, urgency, and responses in Google Sheets. Auto-Reply: Sends an acknowledgment email with ticket ID and SLA timeframe. Error Handling: Failed triage or delivery attempts are logged in a DLQ. 🧩 How to Use Configure triggers (email or webhook) and connect credentials for OpenAI, Slack, Gmail, and Google Sheets. In Workflow Configuration, set: Slack Channel IDs CRM Type (HubSpot, Salesforce, or custom) Google Sheet URL SLA thresholds (e.g., 2h, 6h, 24h) Test with a sample ticket and verify routing and summaries in Slack and Sheets. 🔑 Requirements OpenAI API key (GPT-4o-mini or newer) Slack OAuth credentials Google Sheets API access Gmail/SMTP credentials CRM API (HubSpot, Salesforce, or custom endpoint) 💡 Customization Ideas Add sentiment detection for customer tone. Localize responses for multilingual support. Extend DLQ logging to Notion or Airtable. Add escalation alerts for SLA breaches.
by Brandon Charleson
n8n Lead Qualification & Sales Intelligence Workflow (Top of Funnel) Overview / Purpose This workflow automatically processes new free-trial / lead sign-ups in real time: Catches a webhook from any source (Webflow form, Intercom, custom agent, etc.) Filters out personal / disposable / .edu emails → only business emails continue Validates the company website is live Scrapes the website with Firecrawl to find the official LinkedIn company page Enriches the company via AI Agent (Scrapin.io) → pulls name, follower count, headcount, HQ location, industry, and clean description Runs a multi-factor scoring engine (Location + Headcount + Industry) Sends a beautiful rich Slack notification to the sales team with score, rating, and quick-action buttons Segments the lead by score tier (Very High / High / Mid / Low) Checks if the lead already exists in Instantly Adds qualified leads to the correct Instantly campaign with first/last name extracted from email Core Flow (Step-by-Step) Webhook – Trigger (POST /new-lead) Extract Email Root Domain – Pulls @company.com part Blacklist Regex Domains – Blocks all personal, free, and .edu emails Check Email Not Null – Safety gate Check if Website Exists – HEAD request (continues only on 200-399) Firecrawl Scrape – Scrapes homepage looking for LinkedIn URL in footer/links Extract LinkedIn Url – Code node that finds and cleans /company/ URL Check LinkedIn Not Null + Is Company Page – Rejects personal profiles LinkedIn Agent (AI Agent) Uses Scrapin.io enrichment tool Structured output: company_name, followers, employee_count, headquarters_location, industry, description Audit LI Results – Ensures all key fields returned Sanitize Description – Cleans Unicode, newlines, caps length for Slack Normalize Country – GPT-4.1-nano turns "Sheridan, US" → "United States" Score Country – Code node (0–10 points based on market tier) Score Staff Count – Code node (0–10 points based on headcount buckets) Industry Scoring – Code node (normalizes raw industry + 0–10 points) Algo Score – Final score = weighted average → 0–100 + rating label ("Excellent Fit", "Good Fit", etc.) Send to Slack – Rich blocks with: Email, Company Name, Location (+score), Staff Count (+score), Followers, Industry (+score) Clean description Final Score + Rating Buttons: Visit LinkedIn + Visit Website Score-Based Routing Very High (90–100) High (70–89) Mid (50–69) Low (0–49) Instantly Checks – For each tier: search if lead already exists Extract Name From Email (GPT) – Turns john.smith@company.com → First/Last Name (or "there") Wait nodes (optional delay before adding) Add Lead to Campaign – Pushes to Instantly with website custom field Scoring Logic (Fully Configurable in Code Nodes) Based on your ICP, narrow down your scoring based on how you want to segment. What Makes This Workflow Powerful Zero manual work after webhook Rich, actionable Slack alerts (sales team loves it) Smart scoring that matches real ICP Built-in deduplication with Instantly Fully modular code nodes (easy to tweak scoring without breaking anything) Heavy error handling and safety gates This is a complete, production-ready, public template. You can import the JSON and it will run immediately after you connect your own: Webhook source Firecrawl API Scrapin.io (or alternative) OpenAI Slack Instantly Any questions/comments/concerns, please email brandon@topoffunnel.com Built by Brandon Charleson https://www.youtube.com/@brandoncharleson https://www.linkedin.com/in/brandon-charleson https://x.com/brandon_ai
by Rahul Joshi
📘 Description This workflow automates the full lifecycle of a data-consent complaint: receiving the complaint, validating the payload, normalizing the data into a clean ticket format, storing it in a compliance sheet, generating a formal acknowledgement email for the user, and sending an internal Slack alert for the compliance team. Everything moves from intake → classification → communication → escalation with zero manual handling. AI-generated messages follow DPDP-compliant tone and structure. ⚙️ What This Workflow Does (Step-by-Step) ▶️ Receive Consent Complaint (Webhook) Accepts a POST request containing complaint details: name, email, issue type, description, and metadata. 🔍 Check Required Fields (IF) Validates that the complaint includes a non-empty description. Valid → processed Invalid → logged to a separate sheet. 🧹 Clean & Normalize Complaint Data (Code) Constructs a unified ticket object with: auto-generated ticketId normalized fields (action, email, issueType, description) priority scoring timestamp source metadata Sets default status to Open. 📄 Log Invalid Complaint Records (Google Sheets) Stores incomplete submissions for later review. 📥 Store Complaint Ticket in Consent Dispute Sheet (Google Sheets) Appends the cleaned ticket into the Consent Dispute sheet including all metadata for traceability. 🧠 Generate Acknowledgement Email (AI) Creates a DPDP-compliant support email: mentions user name references ticket ID summarizes issue sets response window (48–72 hours) avoids legal or internal disclosures uses formal, respectful tone ⚙️ Configure GPT-4o – Email Generator Supplies the AI model for email generation. 📝 Extract Email Subject + Body (Code) Splits the AI-generated email into structured fields: subject and message. 📧 Send Acknowledgement Email to User (Gmail) Delivers the formatted acknowledgement directly to the user who filed the complaint. ⚙️ Configure GPT-4o – Slack Summary Model Supplies the AI model for internal Slack summary generation. 🔔 Generate Slack Incident Summary (AI) Produces an internal, action-focused Slack message containing: ticket ID user details issue type description timestamp priority recommended next step No greetings, no email formatting. 📡 Slack – Notify Compliance Team Sends the incident summary to the assigned Slack user or channel for quick action by compliance. 🧩 Prerequisites Live webhook endpoint Google Sheets OAuth (Techdome) Gmail OAuth Slack API credentials Azure OpenAI GPT-4o enabled 💡 Key Benefits ✅ Zero-touch intake → acknowledgement → escalation ✅ DPDP-compliant communication with users ✅ Structured ticket normalization and prioritization ✅ Instant Slack alerts for compliance action ✅ Full audit trail in Google Sheets 👥 Perfect For Data privacy teams Compliance & grievance redressal units SaaS platforms handling consent disputes Organizations needing DPDP-aligned automated workflows
by Asuka
Who Is This For? This workflow is designed for space enthusiasts, science educators, journalists, fact-checkers, and researchers who want to stay informed about near-Earth asteroid threats while filtering out media sensationalism. It's also valuable for anyone studying how different regions cover space-related news. What It Does This workflow creates an automated planetary defense monitoring system that: Scans NASA's Near Earth Object database for potentially hazardous asteroids over a 7-day window Searches news coverage across three regions (US, Japan, EU) to compare media reporting Uses AI (GPT-4o-mini) to fact-check news claims against official NASA data Detects misinformation and measures media sensationalism levels Generates visual charts comparing actual threat levels vs media panic Sends alerts through multiple channels (Slack, Discord, Email) Logs all alerts to Google Sheets for historical analysis How It Works Trigger: Runs daily at 9 AM or on-demand via webhook NASA Data Fetch: Retrieves 7-day asteroid forecast from NASA NeoWs API Threat Analysis: Identifies potentially hazardous asteroids and assigns alert levels (LOW/MEDIUM/HIGH) News Search: Searches news in US, Japan, and EU using Apify's Google Search Scraper AI Fact-Check: GPT-4o-mini compares news claims against NASA data, detecting misinformation Visualization: Generates gauge charts for threat level and media panic, plus regional comparison bar chart Multi-Channel Alerts: Sends formatted reports to Slack, Discord, Email, and logs to Google Sheets Set Up Steps Estimated time: 15-20 minutes NASA API (Required): Get your free API key at api.nasa.gov Apify (Required): Create account and connect via OAuth OpenAI (Required): Add your API key from platform.openai.com Notification Channels (Choose at least one): Slack: Create OAuth app and connect Discord: Create webhook URL Email: Configure SMTP settings Google Sheets (Optional): Create a sheet for logging with columns: Date, Alert Level, Hazardous Count, Threat Score, Media Panic Score, Misinformation Detected, Top Asteroid, Most Accurate Region Requirements NASA API key (free) Apify account (free tier available) OpenAI API key (paid) At least one notification channel configured n8n version 1.0+ How to Customize Change scan frequency**: Modify the Schedule Trigger node Add more regions**: Edit the "Configure Regional Search" code node Adjust alert thresholds**: Modify lunar distance threshold (currently 10) in "Analyze Asteroid Threats" Disable channels**: Simply remove connections to notification nodes you don't need Customize messages**: Edit the "Format Multi-Channel Messages" node