Recognize invoices / receipts from Google Drive and put them into Google Sheets
This workflow allows you to recognize a folder with receipts or invoices (make sure your files are in .pdf, .png, or .jpg format). The workflow can be triggered via the "Test workflow" button, and it also monitors the folder for new files, automatically recognizing them. Video Demo https://youtu.be/mGPt7fqGQD8 n8n import glitch After import, the trigger node "When clicking 'Test workflow'" might be disconnected. You need to connect it via 2 arrows to "Google Sheets1" and "Google Drive" nodes. So, the workflow has 2 triggers - via button, and via Google Sheets "new file" event - both of these triggers should be connected to 2 nodes. Here is how it should look like: https://ocr.oakpdf.com/n8n_fix.png Set up RapidAPI HTTP auth key Create new "HTTP header" n8n credential and paste your RapidAPI key from https://rapidapi.com/restyler/api/receipt-and-invoice-ocr-api into it. https://ocr.oakpdf.com/n8napikey.png Make sure "HTTP Request" node uses this credential. Set up your Google Auth You need a Google connection to work with your Google Sheets and Google Drive accounts: https://docs.n8n.io/integrations/builtin/credentials/google/oauth-generic/finish-your-n8n-credential Set up Google Sheets Copy this Google Sheets document: https://docs.google.com/spreadsheets/d/1G0w-OMdFRrtvzOLPpfFJpsBVNqJ9cfRLMKCVWfrTQBg/edit?usp=sharing Custom document formats and advanced usage Email: contact@scrapeninja.net Linkedin: https://www.linkedin.com/in/anthony-sidashin/
By AnthonyAutomate meeting summaries from Fireflies transcripts with Gemini & Gmail
🤝🖊️🤖 This workflow automates the process of retrieving meeting transcripts from Fireflies.ai, extracting and summarizing relevant content using Google Gemini, and sending or drafting well-formatted summaries and emails via Gmail. Fireflies is an AI-powered meeting assistant that automatically records, transcribes, and summarizes meetings. It integrates with popular video conferencing tools like Zoom, Google Meet, and Microsoft Teams, helping teams capture key insights and action items without manual note-taking. This workflow automates meeting recap generation, from email detection to AI-powered summarization and delivery. --- Key Benefits 💡 Automated Insight Extraction: Uses AI (OpenAI & Gemini) to extract and summarize key insights from meetings automatically. 📩 Instant Client Communication: Generates ready-to-send meeting summaries and drafts without human intervention. 📥 Email Monitoring: Listens to Gmail for specific meeting recap messages and reacts accordingly. 🔗 Seamless Fireflies Integration: Dynamically pulls transcript data 🧠 Dual AI Models: Combines the strengths of OpenAI and Gemini for rich, contextual summaries in multiple formats. 🛠 Modular Design: Easily customizable and extensible for adding more destinations (e.g., Slack, Notion, CRM). 🧑💼 Ideal for Teams & Consultants: Great for sales teams, project managers, or consultants who handle multiple client meetings daily. --- How It Works Trigger: The workflow starts with a Gmail Trigger node that monitors incoming emails with the subject "Your meeting recap". It checks for new emails every hour. Alternatively, it can be manually triggered using the "When clicking ‘Execute workflow’" node for testing. Alternatively, via Webhook. Email Processing: The "Get a message" node fetches the full email content. The "Set Meeting link" node extracts the meeting link from the email. The "Information Extractor" (powered by OpenAI) processes the email text to identify the meeting URL. Transcript Retrieval: A Code node parses the meeting ID from the URL. The "Get a transcript" node (Fireflies.ai integration) fetches the full meeting transcript using the extracted meeting ID. Transcript Processing: The "Set sentences" and "Set summary" nodes extract structured data (sentences, short summary, overview) from the transcript. The "Full transcript" node combines all transcript segments into a readable format. AI Summarization & Email Generation: Google Gemini models analyze and summarize the transcript in Italian ("Expert Meeting transcripts") and generate a client-friendly recap ("Meeting summary expert"). The "Email writer" node combines summaries into a cohesive email draft. The Markdown to HTML nodes format the content for email readability. Output: A "Draft email to client" node prepares the final recap. Two Gmail nodes ("Send Full meeting summary" and "Send a message1") dispatch the summaries to the specified recipient. --- Set Up Steps Configure Credentials: Ensure the following credentials are set up in n8n: Fireflies.ai API (for transcript retrieval). Gmail OAuth2 (for email triggering/sending). OpenAI API (for initial text extraction). Google Gemini (PaLM) (for summarization). Adjust Nodes: Update the "Gmail Trigger" node with the correct email filter (subject:Your meeting recap). Replace YOUR_EMAIL in the Gmail Send nodes with the recipient’s address. Verify the Code nodes (e.g., meeting ID extraction) match your URL structure. Deploy: Activate the workflow. Test using the Manual Trigger or wait for the Gmail trigger to execute automatically. Optional Customization: Modify the Google Gemini prompts for different summary styles. Adjust the email templates in the final Gmail nodes. ---- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By DavideSend automatic WhatsApp order confirmations from Shopify with Rapiwa API
Send Automatic WhatsApp Order Confirmations from Shopify with Rapiwa API Who’s it for This n8n workflow helps Shopify store owners and teams automatically confirm orders via WhatsApp. It checks if the customer's number is valid using Rapiwa API, sends a personalized message, and logs every attempt in Google Sheets—saving time and reducing manual work. Whether you're a solo entrepreneur or managing a small team, this solution gives you a low-cost alternative to the official WhatsApp Business API, without losing control or personalization. Features Receives new order details via webhook upon order creation or update. Iterates over incoming data in manageable batches for smoother processing. Extracts and formats customer and order details from the Shopify webhook payload. Strips non-numeric characters from WhatsApp numbers for consistent formatting. Uses Rapiwa API to check if the WhatsApp number is valid and active. Branches the workflow based on number validity — separates verified from unverified. Sends a custom WhatsApp confirmation message to verified customers using Rapiwa. Updates Google Sheet rows with status and validity How it Works / What It Does Triggered by a Shopify webhook or by reading rows from a Google Sheet. Normalizes and cleans the order payload. Extracts details like customer name, phone, items, shipping, and payment info. Cleans phone numbers (removes special characters). Verifies if the number is registered on WhatsApp via Rapiwa API. If valid: Sends a templated WhatsApp message. Updates Google Sheet with validity = verified and status = sent. If invalid: Skips sending. Updates sheet with validity = unverified and status = not sent. Adds wait/delay between sends to prevent rate limits. Keeps an audit trail in the connected Google Sheet. --- How to Set Up Set up a Shopify webhook for new orders (or connect a Google Sheet). Create a Google Sheet with columns: name, number, order id, item name, total price, validity, status Create and configure a Rapiwa Bearer token in n8n. Add Google Sheets OAuth2 credential in n8n. Import the workflow in n8n and configure these nodes: Webhook or Sheet Trigger Loop Over Items (SplitInBatches) Normalize Payload (Code) Clean WhatsApp Number (Code) Rapiwa WhatsApp Check (HTTP Request) Conditional Branch (If) Send WhatsApp Message (HTTP Request) Update Google Sheet (Google Sheets) Wait Node (delay per send) --- Requirements Shopify store with order webhook enabled (or order list in Google Sheet) A verified Rapiwa API token A working n8n instance with HTTP and Google Sheets nodes enabled A Google Sheet with required structure and valid OAuth credentials in n8n --- How to Customize the Workflow Modify the message template with your own brand tone or emojis. Add country-code logic in the Clean Number node if needed. Use a unique order id in your Google Sheet to prevent mismatches. Increase or decrease delay in the Wait node (e.g., 5–10 seconds). Use additional logic in Code nodes to handle discounts, promotions, or more line items. --- Workflow Highlights Triggered by Shopify webhook update. Receiving new order data form Shopify using webhook Cleans and extracts order data from raw payload. Normalizing and validating the customer’s WhatsApp number using the Rapiwa API Verifies WhatsApp number using Rapiwa's verify-whatsapp endpoint. Sends order confirmation via Rapiwa's send-message endpoint. Logs every result into Google Sheets (verified/unverified + sent/not sent). --- Setup in n8n Check WhatsApp Registration Use an HTTP Request node: URL: https://app.rapiwa.com/api/verify-whatsapp Method: POST Auth: httpBearerAuth using your Rapiwa token Body: { "number": "cleaned_number" } Branch Based on Validity Use an If node: Condition: {{ $json.data.exists }} == true (or "true" if string) Send Message via Rapiwa Endpoint: https://app.rapiwa.com/api/send-message Method: POST Body: Hi {{ $json.customer_full_name }}, Thank you for shopping with SpaGreen Creative! We're happy to confirm that your order has been successfully placed. 🧾 Order Details • Product: {{ $json.line_item.title }} • SKU: {{ $json.line_item.sku }} • Quantity: {{ $json.line_item.quantity }} • Vendor: {{ $json.line_item.vendor }} • Order ID: {{ $json.name }} • Product ID: {{ $json.lineitem.productid }} 📦 Shipping Information {{ $json.shippingaddress.address1 }} {{ $json.shippingaddress.address2 }} {{ $json.shippingaddress.city }}, {{ $json.shippingaddress.country }} - {{ $json.shipping_address.zip }} 💳 Payment Summary • Subtotal: {{ $json.subtotal_price }} BDT • Tax (VAT): {{ $json.totaltaxamount }} BDT • Shipping: {{ $json.totalshippingamount }} BDT • Discount: {{ $json.totaldiscountamount }} BDT • Total Paid: {{ $json.total_price }} BDT Order Date: {{ $json.created_date }} Warm wishes, Team SpaGreen Creative Sample Google Sheet Structure A Google Sheet formatted like this ➤ Sample | name | number | order id | item name | total price | validity | status | | ----------- | ------------- | ------------- | ------------------------------ | ----------- | -------- | ------ | | Abdul Mannan | 8801322827799| 8986469695806 | Iphone 10 | 1150 | verified | sent | | Abdul Mannan | 8801322827799| 8986469695806 | S25 UltraXXXXeen Android Phone | 23000 | verified | sent | --- Tips Always ensure phone numbers have a country code (e.g., 880 for BD). Clean numbers with regex: replace(/\D/g, '') Adjust Rapiwa API response parsing depending on actual structure (true vs "true"). Use row_number for sheet updates, or unique order id for better targeting. Use the Wait node to add 3–10 seconds between sends. --- Important Notes Avoid reordering sheet rows—updates rely on consistent row_number. shopify-app-auth is the credential name used in the export—make sure it's your Rapiwa token. Use a test sheet before going live. Rapiwa has request limits—avoid rapid sending. Add media/image logic later using message_type: media. --- Future Enhancements (Ideas) Add Telegram/Slack alert once the batch finishes. Include media (e.g., product image, invoice) in the message. Detect and resend failed messages. Integrate with Shopify’s GraphQL API for additional data. Auto-mark fulfillment status based on WhatsApp confirmation. --- Support & Community WhatsApp: 8801322827799 Discord: discord Facebook Group: facebook group Website: https://spagreen.net Envato/Codecanyon: codecanyon portfolio ---
By SpaGreen CreativeExtract & summarize Bing Copilot search results with Gemini AI and Bright Data
Who is this for? This workflow automates the process of querying Bing's Copilot Search, extracting structured data from the results, summarizing the information, and sending a notification via webhook. It leverages the Microsoft Copilot to retrieve search results and integrates AI-powered tools for data extraction and summarization. What problem is this workflow solving? Data Analysts and Researchers: Who need to gather and summarize information from Bing search results efficiently. Developers and Engineers: Looking to integrate Bing search data into applications or services. Digital Marketers and SEO Specialists: Interested in monitoring search engine results for specific keywords or topics. What this workflow does Manually extracting and summarizing information from search engine results can be time-consuming and error-prone. This workflow automates the process by: Performing Bing searches using Bright Data's Bing Search API. Extracting structured data from the search results. Summarizing the extracted information using AI tools. Sending the summarized data to a specified endpoint via webhook. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Perform a Bing Copilot Request node with the prompt you wish to perform the search. Update the Structured Data Webhook Notifier node with the Webhook endpoint of your choice. Update the Summary Webhook Notifier node with the Webhook endpoint of your choice. How to customize this workflow to your needs Modify Search Queries: Adjust the search terms to target different topics or keywords. Change Data Extraction Logic: Customize the extraction process to capture specific data points from the search results. Alter Summarization Techniques: Integrate different AI models or adjust parameters to change how summaries are generated. Update Webhook Endpoints: Direct the summarized data to different endpoints as required. Schedule Workflow Runs: Set up automated triggers to run the workflow at desired intervals.
By Ranjan DailataEmail management: Auto-delete marketing emails & generate AI replies with Gemini
Description This workflow intelligently scans your inbox, detects whether an email is marketing or genuine, and takes the right action automatically. Marketing Emails : Deleted instantly and logged in Google Sheets for tracking. Non-Marketing Emails : Receive a customized, polite reply crafted using AI. Tracking : Every action (delete/reply) is recorded for auditing and reference. Accounts & Tools n8n instance (self-hosted or cloud). Google account with: Gmail API access (for reading, deleting, and replying). Google Sheets API access (for logging deleted/replied emails). IMP/SMTP credentials (if using IMAP trigger instead of Gmail API). Google Gemini (PaLM) API key to classify emails and generate replies. Setup instructions Create a n8N account on cloud or install it locally. follow the quick start guide this Define your trigger point for your workflow as how or when this needs to run. Currently IMAP has been used to detect if any email is received and if so, trigger the workflow Now, we need to setup the google account which allows our workflow to read emails. Follow this guideline to setup gmail account Next step is to add an AI tool which is google gemini here. To set up and use, see this guideline Since AI response is in text, we need a parser tool to read a specific value from text Setup a categorization tool like this Next is to send or delete email and for this, an existing gmail setup is going to work In the last, we need to set a connection for sheet to keep the logs. Adding any sheet to workflow can be seen as google sheet integration How it work Once any emails is received, IMAP detects and starts the workflow. Now, email is passed to AI model to see if this email is a marketing email or not. Also, is its not a marketing email, it generates a tailored response. Currently, sender, subject and body of email is being scanned and marked as marketing based on model's feedback. Since AI response is in text format, using a formattor to parse it Next step is to read its category as if it is a marketing email Based on email type, there are 2 steps: delete email if it is a marketing email Read the response from previos node and send that as reply Last step is track this activity as which emails is deleted or replied. In terms of structure of sheet, it has 2 tabs deleted emails & replied emails and both have 2 columns Email ID subject Future Use it to categories emails for wider range like job applications, bills, customer supprt and tailor replies for each categories seperately Logging can done in wider sources like databases etc In case if we are logging on sheet, a further enhancements like follow up emails etc can be done
By Raghvendra dixitAutomate agile project setup with GPT-5 Mini, Jira & form interface
Who is this for? This workflow is perfect for: Agile development teams and project managers who need to quickly set up Jira projects Product managers who want to convert feature ideas into structured user stories and tasks Software development agencies that need to rapidly create detailed project structures for clients Scrum masters seeking to automate the initial project setup and backlog creation process What problem is this workflow solving? Creating comprehensive Jira projects with detailed user stories and sub-tasks is time-consuming and often inconsistent. This workflow solves those issues by: Automating project creation from basic feature descriptions to fully structured Jira projects Generating professional user stories following Agile best practices with proper "As a [user], I want to [goal], so that [benefit]" formatting Creating detailed sub-tasks covering design, development, testing, and documentation phases What this workflow does This workflow transforms raw project ideas into fully structured Jira projects with comprehensive user stories and sub-tasks using AI-powered analysis and automated Jira integration. Step by step: Form Trigger collects project name and feature descriptions through a web form Project Naming uses GPT-4.1 mini to clean and professionalize the project name while generating a unique project key Create Project establishes a new Jira project with proper software development template and configuration Get Status ID retrieves project details and available issue types for story creation Jira Story Generator analyzes project features using AI to create structured user stories with sub-tasks Create Story generates individual Jira stories with proper titles and descriptions Execute Sub-task Workflow automatically creates all associated sub-tasks for each story Gmail Notification sends completion confirmation with project details and direct links How to set up Connect your Jira account by adding your Jira Software Cloud API credentials to all Jira-related nodes Update Jira URL in the "Set Jira URL" node to match your Jira instance (e.g., https://yourcompany.atlassian.net) Add OpenAI API key to the OpenAI Chat Model node for AI-powered story generation Configure Gmail credentials for the notification node and update the recipient email address Update project lead in the Create Project node by replacing the leadAccountId with your user ID Test the workflow using the manual trigger with sample project data Customize story templates in the Structured Output Parser if you need different story formats Set up the sub-workflow by ensuring the Execute Workflow node points to the correct workflow ID How to customize this workflow to your needs Adjust story generation prompts: modify the AI prompts in the "Jira Story Generator" to match your team's specific story writing style or include additional fields Include estimation: add story point estimation logic or time tracking fields to generated stories Switch AI models: replace the OpenAI Chat Model node with other AI providers like Google Gemini, Claude, or local models by using the appropriate n8n AI nodes for different cost and performance requirements Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiArticle to LinkedIn post generator with Telegram, GPT-4 & Google Sheets
🚀 Automated LinkedIn Post Generator from Article Links (Telegram → AI → Google Sheets → LinkedIn) This workflow lets you collect article links through a Telegram bot, automatically analyze and summarize them with AI, store everything neatly in Google Sheets, and generate polished LinkedIn posts on demand whenever the user types “generate”. Perfect for creators, marketers, and founders who want to post consistently without spending hours analyzing articles or writing drafts. --- 🧠 How It Works 1️⃣ User Sends Articles via Telegram Your Telegram bot is the main input point. Whenever the user drops a link, the workflow: Detects the URL Fetches the content Sends it to AI for analysis This keeps the process simple. --- 2️⃣ AI Analyzes & Summarizes the Article The workflow uses your LLM (OpenAI, Anthropic, etc.) to: Summarize the article Extract key insights Identify main arguments Capture tone and context It produces a clean, structured dataset for each link. --- 3️⃣ Everything is Saved into Google Sheets Each article becomes a new row in your Google Sheet. The sheet serves as your content library with fields like: Date Title Link Summary Insights Commentary You can save dozens of articles and generate posts from any of them later. --- 4️⃣ User Requests a Post with “generate” When the user types “generate”, the workflow will: Pull the latest article(s) from Google Sheets (or any selection logic you choose) Build a LinkedIn-ready post using AI Apply the requested tone/style Format it as a clean, professional post The final post is sent right back to Telegram — ready to copy/paste into LinkedIn. --- 🛠️ Setup Steps 🔧 1. Create a Telegram Bot Go to @BotFather on Telegram Create a new bot Copy the API token Paste the token into the Telegram Trigger node in n8n --- 🔧 2. Add Your AI Credentials Go to Credentials → OpenAI (or your provider) Add your API key Select this credential in all AI nodes You can switch to GPT-4o, GPT-4o-mini, or any model you prefer. --- 🔧 3. Connect Google Sheets Go to Credentials → Google Authenticate with your Google account Make sure the sheet contains the required columns: Date Title Link Summary Insights Commentary You can customize or add additional columns as needed. --- 🔧 4. Adjust Workflow Logic (Optional) You can modify: How the AI summarizes The LinkedIn post style How posts are selected (latest, random, specific tone, etc.) Whether you store more metadata Multi-language support Everything is modular. --- 🔧 5. Test the Flow Send yourself a link via the Telegram bot Check that it appears in Google Sheets Type “generate” Receive your LinkedIn post instantly --- 🎉 You’re Ready! This workflow helps you build a personal content pipeline that: Collects links Saves ideas Summarizes insights Generates LinkedIn posts on demand All directly from your phone, inside Telegram. If you remix or extend this template, I’d love to see what you build!
By Shachar ShamirGenerate AI sales proposals from transcripts using Azure OpenAI, PandaDoc & Slack approval
AI Proposal Workflow Overview This workflow turns your sales calls + intake form into a polished, send-ready proposal. It pulls the latest call transcript from Fireflies, generates structured proposal content with Azure OpenAI, builds a proposal in PandaDoc, routes it for Slack approval, and then handles sending, CRM stage updates (Airtable/HubSpot), and automated follow-ups using the PandaDoc audit trail. This workflow is modular. You can replace each major tool: Fireflies → Gong, Fathom, Wingman, Avoma (any transcript provider) PandaDoc → DocuSign, Qwilr, Proposify, Google Docs API Slack Approval → Gmail Approval, MS Teams Approval, Notion DB Approvals Airtable CRM → HubSpot, Pipedrive, Salesforce, Zoho, Monday Sales CRM Intake Form → Typeform, Tally, Jotform, HubSpot forms Azure OpenAI → OpenAI, Anthropic Claude, Mistral, or any LLM connected through an API The core logic stays the same — you only swap the nodes. --- Who It’s For Agencies & consultants who send similar proposals after every call B2B SaaS / tech teams that want proposals going out within hours Solo operators who want AI to handle most of the draft but keep final control Teams already working out of Slack, wanting approval flows there --- How It Works Form Trigger (Client Proposal Intake) Client fills a form with: Name, email, website Industry / business context Problem, solution idea, scope Budget, timeline, deliverables Sales Call Intelligence (Fireflies or Gong) Workflow searches transcripts using the client email Fetches the relevant transcript + summary AI Proposal Generator (Azure OpenAI or any LLM) Sets initial variables (draftText, lastFeedback) Sends transcript + form data into LLM Returns structured JSON: introduction client_problem proposed_solution scopeofwork deliverables timeline_breakdown investment next_steps Proposal Creation (PandaDoc, DocuSign, etc.) Creates the proposal document from a template Fills tokens with AI-generated content Inserts pricing table using Budget Slack Approval Loop Slack message is sent to reviewer with: Approve button Request Changes button Optional comment thread for feedback If Approved: Proposal is sent automatically via PandaDoc/DocuSign Slack message to notify proposal has been sent If Changes Requested: Feedback + draft are stored Passed back into the LLM to regenerate New document is created and the Slack approval request is sent again This loop continues until approval happens CRM Update (Airtable / HubSpot) After proposal is sent, Stage → Proposal Sent Follow-Up System (PandaDoc Audit Trail) After a 48-hour wait: Audit trail is fetched If document is not yet signed: Reminder is sent Stage → Reminder Sent Slack message to notify a reminder has been sent If signed: Stage → Document Signed --- Ideal use cases Sales teams creating tailored proposals at scale Agencies responding quickly to inbound RFPs Freelancers producing polished proposals in minutes RevOps teams standardizing proposal formats SaaS companies automating repetitive proposal creation --- Requirements n8n (self-hosted or cloud) Transcript provider (Fireflies, Gong, Fathom, etc.) LLM API (Azure OpenAI, OpenAI, Claude, etc.) Proposal tool (PandaDoc, DocuSign, Qwilr) Slack API app for approval flow CRM (Airtable, HubSpot, Pipedrive) Intake form --- You can now integrate this into your lead workflow and let AI + automation handle proposal drafting, Slack approvals, sending, CRM updates, and follow-ups.
By Sparsh From Automation JinnAutomated receipt processing for cashback with Jotform, Gemini 2.5 & Notion
📈 Automated Customer Rewards Platform: Jotform Integration This blueprint details a highly efficient, AI-powered workflow designed to automate customer reward fulfillment. Leveraging the accessible interface of Jotform, this system delivers superior reliability and exceptional processing speed. 📊 Reliability, Productivity, and Performance This workflow is engineered to maximize operational efficiency and maintain data integrity: Instant Fulfillment: Automation handles receipt scanning (OCR), AI calculation, logging, and notification in seconds, eliminating manual delays. Seamless Data Capture: Leverages the user-friendly Jotform interface for fast, reliable customer submission and file uploads. 🛠️ Quick Configuration Guide Jotform Webhook: In your JotForm settings, paste the n8n Jotform Trigger URL into the Webhook Integration. Done. API Access: Generate a "Full Access" JotForm API key and insert it into the required n8n nodes (Jotform Trigger and Fetch All Receipts). Credential Setup: Plug in your necessary API keys (Gemini, OCR.Space) and update the Notion Database ID and internal email recipient. 🚀 How It Works (Practical Flow) Submission: Customer submits their request via Jotform. Processing: System extracts text from the receipt (OCR), the AI calculates the reward, and the If node verifies the total. Fulfillment: Transaction logged, confirmation emails sent to both the customer and the internal team. If you need any help Get in Touch
By Abdullah Alshiekh