Workflow Templates

Client Onboarding Email Automation with Google Sheets + Gemini + Gmail When a new client fills out your onboarding form, this workflow automatically creates a personalized welcome email and sends it — using the details they submitted. Benefits Triggers automatically on every new Google Sheets form response Uses Google Gemini to generate a friendly, structured welcome email Includes a checklist of next steps for the client Sends email directly via Gmail Handles errors safely so the workflow never stops How It Works Google Sheets trigger fires when a new row is added Workflow extracts client name, email, company, and service needs Loads a standard onboarding checklist Gemini model writes a custom email using client info + checklist Gmail node sends the email with a welcome subject line Marks workflow as completed or logs failure if there is an error Who Is This For Agencies onboarding new clients Coaches and consultants welcoming new members SaaS or service businesses sending structured welcome steps Setup Connect Google Sheets (use the onboarding form sheet) Add Gemini (Google AI) API key Add Gmail OAuth2 credentials Customize the checklist items if needed Test with a sample form submission before going live ROI & Monetization Save 1–2 hours per new client on manual welcome emails Give clients a smooth and consistent onboarding experience Turn onboarding into a branded, automated touchpoint Strategy Insights In the full walkthrough, I show how to: Build a clean onboarding checklist step by step Use Gemini prompts to keep emails short and professional Add error handling and logging for reliability Extend workflow to create tasks or Slack notifications for your team Check Out My Channel For more AI automation systems that save time and improve client experience, check out my YouTube channel where I share the exact strategies I use to automate onboarding, scale client systems, and grow to $20k+ monthly revenue.

🧾 Attendance Extraction & Notification Pipeline (Google Drive + VLM Run + Google Sheets + Gmail) ⚙️ What This Workflow Does This workflow automates daily attendance tracking by analyzing uploaded attendance images, extracting participant names via VLM Run’s Execute Agent, appending the structured data into Google Sheets, and emailing a formatted attendance summary through Gmail. 🧩 Requirements A Google Drive account with a designated folder for attendance image uploads. A VLM Run API account and your Execute Agent URL or API credentials. A Gmail account connected to n8n for sending notification emails. An n8n instance with the following credentials configured: Google Drive, Google Sheets, Gmail, VLM Run (HTTP API Credential) ⚡Quick Setup Install the verified VLM Run node by searching for VLM Run in the node list, then click Install. Once installed, you can start using it in your workflows. Add VLM Run API credentials for image parsing. Link your Google Drive, Google Sheets and Gmail accounts in the credentials section. In the “Google Drive Trigger” node, select the folder where attendance images will be uploaded. In the “Append Row” node, connect your Google Sheet and map columns manually (e.g., Date, Total, Names…). Add VLM Run execute agent endpoint. Upload an image (whiteboard attendance photo or scanned sheet) to your Drive folder. Wait for the automation to process and check your Google Sheet for results. After each extraction and logging step, the Gmail Node sends an automated summary email. Email includes: 📅 Date of attendance 👥 Total participants detected 🧍 List of extracted names ⚙️ How It Works Monitor List Uploads – Watches a Google Drive folder for new attendance images (e.g., whiteboard snapshots, scanned sheets). Download List – Downloads each new image automatically for AI processing. VLM Run for Extraction sends the image to VLM Run Execute Agent, which uses an AI model to detect and extract attendee names from the image. Receive Attendance Data – The Webhook node (check-attendance) receives structured JSON data from VLM Run in the format: { "majorDimension": "ROWS", "values": [ ["2025-10-03", "6", "Camila Torres Rivera", "Mellissa Richmond", "Captioner Javier", "Siobhan", "Catherine Soler", "Anisah Anif"] ] } The Google Sheets Node appends the structured attendance data to the selected sheet, maintaining a daily log for future reference. The Gmail Node sends an automatic email summarizing attendance. 💡Why Use This Workflow 🔄 Fully Automated: No manual data entry required. 🧠 AI-Powered Extraction: Uses VLM Run to read and parse images with handwritten or typed text. 📊 Centralized Logging: Attendance data neatly organized in Google Sheets for future analysis. 📬 Instant Notification: Keeps stakeholders informed automatically after each session. ⚡ Scalable: Works with multiple folders, daily batches, or parallel sessions. 🛠️ How to Customize You can tailor this workflow to match your organization’s needs: | Area | Customization Options | | ------------------------ | ---------------------------------------------------------------------------------------------------------- | | Drive Folder | Point to a different upload folder for each department or class. | | Google Sheet Mapping | Add more columns (e.g., “Class Name,” “Supervisor”) and map them in the Append Row node. | | Email Template | Modify the Gmail node’s subject and body to include custom formatting or logos. | | Trigger Schedule | Replace Google Drive Trigger with a Cron Node if you prefer scheduled checks instead of live watching. | | Data Validation | Add a Function Node to filter duplicates or incorrect entries before appending to Sheets. | | Notification Options | Send alerts via Slack, Telegram, or Microsoft Teams instead of Gmail if desired. | ⚠️ Community Node Disclaimer This workflow uses community nodes (VLM Run) that may need additional permissions and custom setup.

Stripe Invoice Reminder Workflow Who’s this for Businesses using Stripe subscriptions or one-time payments who want to automatically follow up with customers after a failed payment. What this workflow does Detects expired or failed charges in Stripe Drafts AI-generated payment reminders for customers Creates a new Stripe invoice for the failed payment Optionally sends reminders via Email or Slack How it works Stripe trigger listens for expired charges Set node normalizes customer and payment information OpenAI node drafts a friendly payment reminder Stripe node creates a new invoice Optional Email/Slack node sends the reminder How to set up Connect Stripe account and enable 'charge.expired' events Connect OpenAI API credentials Configure Email or Slack notifications if desired Optional: Customize AI prompt for company tone Requirements n8n account with Stripe integration OpenAI API key Optional Email/Slack integration How to customize Change AI prompt to fit brand voice Include dynamic invoice details or subscription links Add internal alerts for accounting teams Modify email templates or Slack messages

How it works This workflow automatically identifies users who started but did not complete the signup process. It runs on a fixed schedule, checks your database for inactive and incomplete users, and validates the results before proceeding. Each user is then processed individually to send a personalized recovery email and enroll them in a follow-up sequence. Finally, the workflow updates the database to avoid duplicate outreach and notifies the sales team in Slack. Step-by-step Step 1: Run scheduled check and identify abandoned users** Schedule Trigger – Executes the workflow automatically every 24 hours. Find Abandoned Users – Queries Postgres for users marked as incomplete and inactive for over 24 hours. If – Confirms that valid user records exist before continuing. Step 2: Process users and send recovery emails** Loop Over Items – Processes users one at a time to avoid rate limits and execution errors. PrepareEmail email – Generates a personalized recovery email using a predefined template. Send a message – Sends the recovery email through Gmail. Get a message – Retrieves the sent email details for tracking and thread reference. StartSequence email – Adds the email to a follow-up sequence for engagement tracking. Step 3: Update records and notify the team** Update rows in a table – Marks the user as contacted to prevent duplicate recovery emails. Alert Sales Team – Sends a Slack notification with user details and recovery status. Why use this? Recover users who abandon onboarding without manual follow-ups Ensure each user receives only one recovery email Keep your Postgres user data accurate and up to date Provide sales teams with real-time visibility via Slack alerts Improve signup completion and activation rates automatically

How It Works This workflow automates intelligent content moderation and governance enforcement through multi-model AI validation. Designed for social media platforms, online communities, and user-generated content platforms, it solves the critical challenge of scaling content review while maintaining consistent policy enforcement and human oversight for edge cases. The system receives content submissions via webhook, processing them through a dual-agent AI framework for content validation and governance orchestration. It employs specialized AI models for policy violation detection, moderation API enforcement checks, and governance decision-making. The workflow intelligently routes content based on severity classification, escalating high-risk submissions for human moderator review while auto-processing clear-cut decisions. By merging parallel validation paths and maintaining comprehensive audit logs, it ensures consistent policy application across all content while preserving human judgment for nuanced cases requiring contextual understanding. Setup Steps Configure Content Submission Webhook trigger endpoint Connect Workflow Configuration node with content policy parameters Set up Content Validation Agent with Claude/OpenAI API credentials Configure parallel AI processing nodes Connect Governance Orchestration Agent with AI API credentials Set up multi-model validation Configure Route by Severity node with classification thresholds Prerequisites Claude/OpenAI API credentials for content validation, moderation API access for policy enforcement Use Cases Social media platforms moderating user posts and comments, online marketplaces reviewing product listings Customization Adjust severity thresholds for platform-specific risk tolerance Benefits Reduces content review time by 85%, ensures consistent policy enforcement across all submissions

What this template does Instantly reach new leads on WhatsApp when they submit a form (Typeform, JotForm, Google Forms, or any webhook-enabled form) using MoltFlow (https://molt.waiflow.app). Leads are also logged to Google Sheets for CRM tracking. How it works A form submission triggers this webhook Contact info is extracted (name, phone, interest) A personalized WhatsApp message is sent via MoltFlow The lead is logged to Google Sheets for follow-up tracking Set up steps Create a MoltFlow account (https://molt.waiflow.app) and connect your WhatsApp number Generate an API key in MoltFlow (Sessions page, API Keys tab) Activate this workflow in n8n and copy the webhook URL Configure your form tool to POST submissions to this webhook URL Map your form field names in the Parse Form Data code node (name, phone, email, interest) Set YOUR_SESSION_ID in the Parse Form Data code node Add your MoltFlow API key as an HTTP Header Auth credential (Header Name: X-API-Key) Optional: Connect Google Sheets to log leads automatically Prerequisites MoltFlow account with an active WhatsApp session Any form tool that supports webhooks (Typeform, JotForm, Google Forms, Tally, etc.) Optional: Google Sheets for lead tracking

How It Works This workflow automates the complex process of managing lawsuit responses through intelligent task validation and multi-authority coordination. Designed for legal departments, compliance teams, and government agencies handling litigation matters, it solves the critical challenge of ensuring timely, accurate responses while maintaining proper oversight across multiple organizational levels. The system receives lawsuit notifications, validates critical information, and intelligently routes tasks based on authority levels. It orchestrates human oversight at strategic checkpoints, merges authority paths for comprehensive review, and generates detailed orchestration reports. By automating document preparation and multi-trail logging, it ensures accountability while reducing manual coordination overhead. The workflow seamlessly integrates validation results, manages execution plans, and prepares final responses through systematic processes, ultimately delivering compliant lawsuit responses through secure multi-trail communication channels. Setup Steps Configure Workflow Execution Webhook trigger endpoint Connect Workflow Configuration node with workflow parameters Set up Prepare Request Data node with lawsuit data structure mapping Configure Fetch Authority Rules node with OpenAI/Nvidia API credentials Connect Check Validation Result node with boundary enforcement parameters Configure Human Checkpoint nodes (High/Medium Authority) with approval routing Set up Merge Authority Paths node for consolidation logic Configure Orchestration Export node with Google Sheets credentials Prerequisites OpenAI or Nvidia API credentials for validation processing, Google Sheets access for orchestration logging Use Cases Government litigation departments managing multi-level approval workflows Customization Modify authority routing logic for organizational hierarchies Benefits Reduces response coordination time by 70%, eliminates manual routing errors

How It Works This workflow automates clinical trial signal validation and regulatory governance through intelligent AI-driven oversight. Designed for clinical research organizations, pharmaceutical companies, and regulatory affairs teams, it solves the critical challenge of ensuring trial compliance while managing post-market surveillance obligations across multiple regulatory frameworks.The system operates on scheduled intervals, fetching data from clinical trial databases and laboratory production signals, then merging these sources for comprehensive analysis. It employs dual AI agents for clinical signal validation and governance assessment, detecting protocol deviations, safety signals, and compliance violations. The workflow intelligently routes findings based on governance action requirements, orchestrating parallel processes for regulatory reporting, batch result documentation, and post-market surveillance logging. By maintaining synchronized audit trails across regulatory reports, batch records, post-market surveillance, and comprehensive action logs, it ensures complete traceability while automating escalation to quality teams when intervention is required. Setup Steps Configure Schedule Trigger with monitoring frequency for trial oversight Connect Workflow Configuration node with trial parameters and compliance rules Set up Fetch Clinical Trial Data and Fetch Lab & Production Signals nodes Configure Merge Signal Sources node for data consolidation logic Connect Clinical Signal Validation Agent with OpenAI/Nvidia API credentials Set up parallel AI processing Configure Regulatory Governance Agent with AI API credentials for compliance assessment Connect Route by Governance Action node with classification logic Prerequisites OpenAI or Nvidia API credentials for AI validation agents, clinical trial database API access Use Cases Pharmaceutical companies managing Phase III trial monitoring, CROs overseeing multi-site clinical studies Customization Adjust signal validation criteria for therapeutic area-specific protocols Benefits Reduces regulatory review cycles by 70%, eliminates manual signal triage

Who it is for This workflow is designed for developers, content managers, and website administrators managing multilingual WordPress sites. It is highly beneficial for websites built with complex Advanced Custom Fields (ACF) or custom Gutenberg layouts that standard translation plugins often struggle to process efficiently. How it works When a post is created or updated, WordPress triggers a webhook to start the workflow. The workflow fetches the raw post JSON directly from the WordPress REST API. An OpenAI node analyzes a text snippet to detect the exact source language, ensuring it only routes and translates into missing target languages to prevent duplication. A code node then recursively extracts text from both standard fields and specific ACF fields into a single array. These strings are translated in bulk via DeepL, maintaining HTML formatting. Finally, the workflow rebuilds the original JSON structure with the translated text and pushes it back to WordPress as a newly linked translation draft. Requirements WordPress Application Password (for HTTP Basic Auth) OpenAI API Key DeepL API Key A WordPress plugin capable of firing webhooks on post updates (e.g., WP Webhooks) How to set up Configure the Webhook node and point your WordPress webhook plugin to the provided test/production URL. Add your HTTP Basic Auth credentials (WP Admin Username and App Password) to the WordPress request nodes. Add your OpenAI API key and DeepL API key to their respective nodes. Update the base URL in the HTTP nodes to point to your actual WordPress domain. How to customize Open the "Smart Router & Targets" node and update the target languages array to match your website's supported languages. Most importantly, open the "Extract Content" code node and modify the text keys array to perfectly match the field names used in your site's unique ACF configuration.

🎯 What This Does This workflow automatically monitors a specific Google Drive folder for new images. When you drop a file in, it uses Google's Gemini AI to analyze the image, generate an creative title, and write a high-engagement description. It then posts the image and text to a Discord channel and organizes your Google Drive by renaming the file and moving it to a "Processed" folder. 🔄 How It Works Watch:** The workflow detects when a new image file is uploaded to a specific Google Drive folder. Analyze:** It downloads the image and sends it to a Google Gemini AI Agent to identify the "hook" and generate technical/marketing copy. Format:** The AI returns a structured title, description, and a new optimized filename. Publish:** The workflow posts the image and the AI-generated caption directly to your Discord channel as a new thread. Organize:** Finally, it renames the original file in Google Drive and moves it to a separate "Processed" folder to keep your workspace clean. 🚀 Setup Requirements n8n Version:** Latest stable release recommended. Google Cloud Console Project:* With *Google Drive API** enabled. Google Gemini API Key:** For the AI generation. Discord Application:** A Bot Token with permissions to send messages/create threads in your server. Estimated Setup Time:** ~15 minutes. Set up steps Configure Google Drive Credentials: Set up a project in Google Cloud Console. Enable the Google Drive API. Create OAuth 2.0 credentials and add them to the Google Drive Trigger and Google Drive nodes in n8n. Prepare Drive Folders: Create a folder in Google Drive for Input (where you drop files). Copy the Folder ID from the URL. Create a folder for Processed files. Copy this Folder ID as well. Paste the Input Folder ID into the Google Drive Trigger node. Update the processed_folder_id value in the "Get File & Set Channel" (Set) node. Configure AI Agent: Get your API Key from Google AI Studio. Add a new credential for Google PaLM API in the Chat Model node. Setup Discord Bot: Go to the Discord Developer Portal and create a new Application/Bot. Copy the Bot Token. Invite the bot to your server. Enable Developer Mode in your Discord User Settings to right-click a channel and "Copy Channel ID". Update the channel_id in the "Get File & Set Channel" node. Open the "Post To Discord Channel" (HTTP Request) node. Under Authentication, select "Predefined Credential Type" -> "Discord Bot API" and paste your token. Test the Workflow: Click "Test Workflow" in n8n. Upload an image to your Google Drive Input folder. Watch the execution! Check Discord for the new post and Drive to see the file move. Nodes Used Google Drive Trigger:** Watches for new content. Google Drive:** Downloads, Updates (Renames), and Moves files. AI Agent (LangChain):** Orchestrates the analysis. Google Gemini Chat Model:** Generates the creative text. Structured Output Parser:** Ensures the AI replies in usable JSON. HTTP Request:** custom API call to Discord for advanced thread creation. Set:** Manages variables and folder IDs. Customization Guide Change the Persona:* Edit the "System Message" in the *AI Agent** node to change the tone. Want a pirate narrator? Or a strictly professional corporate tone? Change it there! 🙏 Thank You for Trying This Workflow! Your time and trust mean a lot! I truly appreciate you using this template. Your feedback shapes future updates: 💡 Suggestions for improvement 🆕 Ideas for new features 📝 Requests for other automation workflows Please share your thoughts! Every idea helps shape the next update. 🙋‍♂️ Join & Follow For More Free Templates! Discord Community: We Work Together Get help, share builds, collaborate! Daily tips, tutorials, and updates Thank you again for being part of this journey! 🚀 Together, we automate better! 🤖✨

🚀 ExamForge AI Automated PDF to Structured Exam Generator (MCQ + Essay + Answer Key) Generate structured exams automatically from text-based PDF materials using AI. ExamForge AI is a production-ready n8n workflow that transforms educational content into multiple-choice and essay questions with customizable difficulty and automatic answer key generation. ✨ Features 📄 Upload PDF via Webhook ✅ File size validation (default: max 5MB) 🧹 Automatic text cleaning 📏 Token length estimation & safety control 🎯 Customizable MCQ & Essay count 🧠 Difficulty selection (easy / medium / hard) 🌍 Language selection 📦 Structured JSON AI output 📝 Separate Exam PDF & Answer Key PDF 📲 Telegram delivery support (optional) 🔒 Parameter validation with structured error responses 🧠 What This Workflow Does Accepts PDF upload via Webhook Validates file size Extracts and cleans text content Estimates text length to prevent token overflow Validates required parameters: mcq_count essay_count difficulty language Sends structured prompt to OpenAI Parses JSON response Formats exam and answer key separately Converts both into PDF Sends results via Telegram or Webhook response ⚙️ Requirements Accounts Required OpenAI account (API key required) Telegram Bot (optional) PDF Munk (API key required) Environment n8n (self-hosted or cloud) Node version compatible with your n8n installation 🔑 Credentials Setup 1️⃣ OpenAI Add OpenAI credentials inside n8n Insert your API key Select preferred model (e.g., GPT-4o / GPT-4) 2️⃣ Telegram (Optional) Create a Telegram Bot via BotFather Insert Bot Token into Telegram node Add your Chat ID 🛠 Webhook Configuration Method: POST Content-Type: multipart/form-data Required Parameters | Parameter | Type | Required | Description | |--------------|--------|----------|-------------| | file | File | Yes | PDF document | | mcq_count | Number | Yes | Number of multiple-choice questions | | essay_count | Number | Yes | Number of essay questions | | difficulty | String | Yes | easy / medium / hard | | language | String | Yes | Output language | 📥 Example Request curl -X POST https://your-n8n-domain/webhook/examforge \ -F "file=@document.pdf" \ -F "mcq_count=20" \ -F "essay_count=5" \ -F "difficulty=medium" \ -F "language=Indonesian"

N8N AI LLM Unstructured Invoice data PDF OCR recognition to JSON output API What this workflow does Accepts a PDF or image upload via Webhook as binary property "data" Runs OCR with the Mistral OCR node Normalizes OCR text Sends OCR text to an LLM to extract structured JSON Cleans and normalizes the JSON Returns either: status: ok status: review_needed Setup Import the workflow JSON into n8n Create/attach Mistral AI credentials on the "Mistral OCR" node Create/attach your choice LLM AI credentials on the OCR text to JSON converson node Activate the workflow POST a file to: /webhook/ocr-to-json Notes This starter is tuned for invoices/documents but can be adapted for receipts, purchase orders, or forms. Depending on your installed n8n version, the Mistral node parameter names may need minor adjustment after import. The workflow returns review_needed when confidence is below 0.5.