Workflow Templates

Who is this for? This workflow is for online store owners, support teams, and marketing staff who want to automatically verify WhatsApp numbers and send order invoice links or personalized order updates to customers. It’s built against WooCommerce order webhooks but can be adapted to Shopify or other e-commerce platforms that provide billing and line_items. What this Workflow Does Receives order events (Webhook / WooCommerce order.updated). Normalizes the payload into a compact object: { data: { customer, products, invoice_link } } via a Code node. Iterates items in batches (SplitInBatches) to control throughput. Cleans phone numbers (removes non-digits) and verifies WhatsApp registration using Rapiwa (/api/verify-whatsapp). Sends templated WhatsApp messages through Rapiwa (/api/send-message) for verified numbers. Logs every attempt into Google Sheets: one sheet for verified & sent rows, another for unverified & not sent rows. Uses a Wait node to throttle and loop back into the batch processor. Key Features Trigger-based automation (Webhook or WooCommerce trigger). Payload normalization and mapping via JavaScript Code nodes. Controlled batching (SplitInBatches) to avoid rate limits. Pre-send verification of WhatsApp numbers using Rapiwa. Conditional branching with the IF node to separate verified vs unverified flows. Personalized message templates that pull customer and product fields from the mapped data. Logging and audit trail stored in Google Sheets (two separate append flows). How to Use — Step-by-step Setup Add credentials in n8n Rapiwa: Create an HTTP Bearer credential and paste your Bearer token (example name used in the flow: Rapiwa Bearer Auth). Google Sheets: Create an OAuth2 credential (example: Google Sheets). WooCommerce: Add WooCommerce API credentials for the trigger (or configure Shopify credentials if adapting). Import / configure nodes in n8n Webhook (or WooCommerce Trigger): receive order payloads. Example Webhook path is present in the exported flow. Code node Format Webhook Response Data: map body.billing, body.line_items, body.payment_url into { data: { customer, products, invoice_link } }. Code node Clean WhatsApp Number: ensure the phone number is a string and strip non-digits: String(rawNumber).replace(/\D/g, ""). HTTP Request Check valid whatsapp number Using Rapiwa: POST to https://app.rapiwa.com/api/verify-whatsapp with { number }. Use the Rapiwa Bearer credential. IF If: check verification result. The flow compares {{$json.data.exists}} to "true" in the exported flow; normalize types if your API returns booleans. HTTP Request Rapiwa Sender: POST to https://app.rapiwa.com/api/send-message with number, message_type: 'text', and a templated message (see message template in the flow). Google Sheets Store State of Rows in Verified & Sent and Store State of Rows in Unverified & Not Sent Google Sheet Column Structure Create these columns exactly (the Google Sheets nodes in the flow expect these names): A Google Sheet formatted like this ➤ sample | Name | Number | Email | Address | Product Title | Product ID | Size | Quantity | Total Price | Product Image | Invoice Link | Product Status | Validity | Status | |-----------------|---------------|-------------------|--------------|------------------------------------------------|------------|------|----------|----------------|--------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|----------------|------------|----------| | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur dohs | Air Force 1 Reigning Champ Dark Grey 1:1 - 40 | 251 | 40 | 1 | BDT 5800.00 | | Invoice | on-hold | verified | sent | | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur dohs | Air Force 1 Reigning Champ Dark Grey 1:1 - 40 | 251 | 40 | 1 | BDT 5800.00 | | Invoice | on-hold | unverified | not sent | Customization Ideas Adapt the Code mapping node for Shopify payloads or other marketplaces. Iterate and include multiple products in the message instead of using products[0]. Add filters in the Code node (e.g., only process orders with total > 5000). Add fallback channels (SMS or email) for unverified numbers. Persist logs into a database for analytics and retention beyond Google Sheets. Add admin notifications (Slack, email) at the end of each run. Useful Links Dashboard:** https://app.rapiwa.com Official Website:** https://rapiwa.com Documentation:** https://docs.rapiwa.com Support & Help WhatsApp**: Chat on WhatsApp Discord**: SpaGreen Community Facebook Group**: SpaGreen Support Website**: https://spagreen.net Developer Portfolio**: Codecanyon SpaGreen

This automated workflow monitors your website's keyword rankings daily and sends instant alerts to your team when significant ranking drops occur. It fetches current ranking positions, compares them with historical data, and triggers notifications through Slack and email when keywords drop beyond your defined threshold. Good to know The workflow uses SERP API for accurate ranking data; API costs apply based on your usage volume Ranking checks are performed daily to avoid overwhelming search engines with requests The system tracks ranking changes over time and maintains historical data for trend analysis Slack integration requires workspace permissions and proper bot configuration False positives may occur due to personalized search results or data center variations How it works Daily SEO Check Trigger** initiates the workflow on a scheduled basis Get Keywords Database** retrieves your keyword list and current ranking data Filter Active Keywords Only** processes only keywords marked as active for monitoring Fetch Google Rankings via SERP API** gets current ranking positions for each keyword Wait For Response** Wait for gets current ranking positions Parse Rankings & Detect Changes** compares new rankings with historical data and identifies significant drops Filter Significant Ranking Drops** isolates keywords that dropped beyond your threshold (e.g., 5+ positions) Send Slack Ranking Alert** notifies your team channel about ranking drops Send Email Ranking Alert** sends detailed email reports to stakeholders Update Rankings in Google Sheet** saves new ranking data for historical tracking Generate SEO Monitoring Summary** creates a comprehensive report of all ranking changes How to use Import the workflow into n8n and configure your SERP API credentials Set up your Google Sheet with the required keyword database structure Configure Slack webhook URL and email SMTP settings Define your ranking drop threshold (recommended: 5+ position drops) Test the workflow with a small keyword set before full deployment Schedule the workflow to run daily during off-peak hours Requirements SERP API account** with sufficient credits for daily keyword checks Google Sheets access** for keyword database and ranking storage Slack workspace** with webhook permissions for team notifications Email service** (SMTP or API) for stakeholder alerts Keywords database** properly formatted in Google Sheets Database/Sheet Columns Required Google Sheet: "Keywords Database" Create a Google Sheet with the following columns: | Column Name | Description | Example | |-------------|-------------|---------| | keyword | Target keyword to monitor | "best seo tools" | | domain | Your website domain | "yourwebsite.com" | | current_rank | Latest ranking position | 5 | | previous_rank | Previous day's ranking | 3 | | status | Monitoring status | "active" | | target_url | Expected ranking URL | "/best-seo-tools-guide" | | search_volume | Monthly search volume | 1200 | | difficulty | Keyword difficulty score | 65 | | date_added | When keyword was added | "2025-01-15" | | last_checked | Last monitoring date | "2025-07-30" | | drop_threshold | Custom drop alert threshold | 5 | | category | Keyword grouping | "Product Pages" | Customising this workflow Modify ranking thresholds** in the "Filter Significant Ranking Drops" node to adjust sensitivity (e.g., 3+ positions vs 10+ positions) Add competitor monitoring** by duplicating the SERP API node and tracking competitor rankings for the same keywords Customize alert messages** in Slack and email nodes to include your brand voice and specific stakeholder information Extend to multiple search engines** by adding Bing or Yahoo ranking checks alongside Google Implement ranking improvement alerts** to celebrate when keywords move up significantly Add mobile vs desktop tracking** by configuring separate SERP API calls for different device types

🤯 Problem of Traditional Bookkeeping 🔀 Context switch kills the habit: Because bookkeeping lives outside the apps you use every day, you postpone it → forget to log. 🧱 High input friction: You’re forced to fill rigid fields (amount/category/date/notes…), which is slow and discouraging for quick capture. 🎙️💸 Weak or pricey natural-language options: A few tools support voice/chat, but they’re often expensive, and the experience is hit-or-miss. 🔒📦 Limited data ownership: Records live on third-party servers, so privacy and control are diluted. 📲 How This Workflow Fixes It 💬 Put the capture back where you already are: Log expenses directly inside Telegram (or other channels) in a familiar chat—no new app to learn. ⚡ Ultra-low-friction, unstructured input: Send text, a voice note, or a receipt photo—the flow extracts amount · item · date, supports multiple languages and relative dates, and can split multiple expenses from one message. 🗂️📝 Your data, your sheet: Final records are written to your own Google Sheet (columnar fields or a JSON column). You keep full control. 🔗 Demo Google Sheet: click me 👥 Who Is This For 😤 Anyone fed up with traditional bookkeeping but curious about an AI-assisted, chat-based way to log expenses. 🤖 People who tried AI bookkeeping apps but found them pricey, inflexible, or clunky. 💵 Bookkeeping beginners who want frictionless capture first, simple review and categorize later. 🧩 How It Works 💬 Captures expenses from Telegram (text, voice note, or receipt photo). 🔎 Normalizes inputs into raw text (uses Gemini to transcribe voice and extract text from images). 🧠 Parses amount · item · date with an LLM expense parser. 📊 Appends tidy rows to Google Sheets. 🔔 Sends a Telegram confirmation summarizing exactly what was recorded. 🛠️ How to Set Up 1) 🔑 Connect credentials (once) TELEGRAM_BOT_TOKEN LLM_API_KEY GOOGLE_SHEETS_OAUTH 2) 🚀 Quick Start Setup:* Create a Google Sheet to store *Log Expense** data and configure it in n8n. Telegram:* Fill in and verify the *Telegram chatId**. Remember enable the workflow!* 🧰 How to Customize the Workflow 📝 Other user interaction channels: Add Gmail, Slack, or a website Webhook to accept email/command/form submissions that map into the same parser. 🌍 Currency: Extract and store currency in its own column (e.g., MYR, USD); keep amount numeric only (no symbols). 🔎 Higher-accuracy OCR / STT to reduce errors 📩 Help Contact: owenlzyxg@gmail.com

Why Creating and sending invoices manually is a major administrative bottleneck. It's not only slow but also prone to human error, such as creating duplicate invoice numbers or sending sensitive financial data in an unsecured format. This workflow solves these problems by creating a robust, end-to-end automation. It ensures every invoice has a unique ID, is professionally generated, is password-protected, and is delivered to your customer automatically. What This workflow provides a complete, secure solution for automated invoicing. It is designed to be triggered by a Webhook (e.g., from your e-commerce store, CRM, or billing platform) that provides customer and order details. The workflow then executes the following steps: Generate & Verify ID: It first generates a new invoice ID. It then performs a critical check by reading your master Google Sheet to ensure this ID is unique, preventing duplicate invoices. Generate PDF: Once the ID is verified, it passes the data to the PDF Generator API. This service dynamically populates your custom invoice template. (PDF Generator API makes it incredibly easy to build and manage your document templates via their web-based editor). Encrypt Document: For enhanced security, the workflow uses a PDF Generator API operation to encrypt the newly generated invoice with a password, protecting your client's sensitive data. Store & Deliver: Finally, it uploads the secure PDF to a specified Google Drive folder for your records and then automatically sends it to the customer as an attachment using Gmail. How Prerequisites: You will need active accounts for: PDF Generator API (for both generation and encryption) Google Suite (for Sheets, Drive, and Gmail) PDF Generator API Setup: Log in to your PDF Generator API account and use their template builder to create your invoice design. Note your Template ID, API Key, and API Secret. In the n8n PDFGeneratorAPI node (Generate a PDF document), create new credentials using your Key and Secret. In the node's parameters, select your Template ID from the list. Google Sheets Setup: Create a Google Sheet to act as your master list of invoices. In the Check If ID Already Exists node, authenticate your Google Sheets account. Set the Spreadsheet ID and Sheet Name. In the "Columns to Return" field, enter the name of the column where you store your invoice IDs. Security & Delivery Setup: Encrypt Node: In the Encrypt PDF document node, authenticate your PDF Generator API credentials (the same ones from Step 2). You can set a static password, or for better security, use an expression to set a dynamic password from the webhook data (e.g., the customer's postal code or order ID). Google Drive Node: Authenticate the Upload file node and specify the Drive and Folder ID where invoices should be stored. Gmail Node: Authenticate the Send a message + file node. Use an expression to map the customer's email from the trigger data into the "To" field. Test & Activate: The Webhook node has pinned test data. You can click "Test workflow" to run the entire process with this sample data. Once you confirm the file is generated, encrypted, and sent, connect your live app (e.g., Shopify, Stripe, etc.) to the production Webhook URL. Activate the workflow.

Track your daily mood in one tap and receive automated AI summaries of your emotional trends every week and month. Perfect for self-reflection, wellness tracking, or personal analytics. This workflow logs moods sent through a webhook (/mood) into Data Tables, analyzes them weekly and monthly with OpenAI (GPT-4o), and emails you clear summaries and actionable recommendations via Gmail. ⚙️ How It Works Webhook – Mood → Collects new entries (🙂, 😐, or 😩) plus an optional note. Set Mood Data → Adds date, hour, and note fields automatically. Insert Mood Row → Stores each record in a Data Table. Weekly Schedule (Sunday 20:00) → Aggregates the last 7 days and sends a summarized report. Monthly Schedule (Day 1 at 08:00) → Aggregates the last 30 days for a deeper AI analysis. OpenAI Analysis → Generates insights, patterns, and 3 actionable recommendations. Gmail → Sends the full report (chart + AI text) to your inbox. 📊 Example Auto-Email Weekly Mood Summary (last 7 days) 🙂 5 ██████████ 😐 2 ████ 😩 0 Average: 1.7 (Positive 🙂) AI Insights: You’re trending upward this week — notes show that exercise days improved mood. Try keeping short walks mid-week to stabilize energy. 🧩 Requirements n8n Data Tables enabled OpenAI credential (GPT-4o or GPT-4 Turbo) Gmail OAuth2 credential to send summaries 🔧 Setup Instructions Connect your credentials: Add your own OpenAI and Gmail OAuth2 credentials. Set your Data Table ID: Open the Insert Mood Row node and enter your own Data Table ID. Without this, new moods won’t be stored. Replace the email placeholder: In the Gmail nodes, replace your.email@example.com with your actual address. Deploy and run: Send a test POST request to /mood (e.g. { "mood": "🙂", "note": "productive day" }) to log your first entry. ⚠️ Before activating the workflow, ensure you have configured the Data Table ID in the “Insert Mood Row” node. 🧠 AI Analysis Interprets mood patterns using GPT-4o. Highlights trends, potential triggers, and suggests 3 specific actions. Runs automatically every week and month. 🔒 Security No personal data is exposed outside your n8n instance. Always remove or anonymize credential references before sharing publicly. 💡 Ideal For Personal mood journaling and AI feedback Therapists tracking client progress Productivity or self-quantification projects 🗒️ Sticky Notes Guide 🟡 Mood Logging Webhook POST /mood receives mood + optional note. ⚠️ Configure your own Data Table ID in the “Insert Mood Row” node before running. 🟢 Weekly Summary Runs every Sunday 20:00 → aggregates last 7 days → generates AI insights + emails report. 🔵 Monthly Summary Runs on Day 1 at 08:00 → aggregates last 30 days → creates monthly reflection. 🟣 AI Analysis Uses OpenAI GPT-4o to interpret trends and recommend actions. 🟠 Email Delivery Sends formatted summaries to your inbox automatically.

Who’s it for Recruiting agencies, executive search firms, and in-house talent teams that want to automate candidate sourcing and prequalification. Instead of spending hours searching, scoring, and writing outreach, this workflow turns any job description into a ready-to-use shortlist with personalized messages. Youtube Walkthrough What it does (How it works) This workflow takes a job description (title, description, and location) and runs a complete recruiting automation pipeline: Normalize job titles** and generate variations to widen search coverage. Search candidates** in Apollo (or your CRM / database of choice). Remove duplicates** to keep clean lists. Score candidates** with AI (0–5) and provide concise reasoning across experience, industry, and seniority. Enrich LinkedIn profiles** (name, title, image, location, experience). Create structured candidate assessments** (summary, alignment, red flags, positives). Generate outreach messages** (email + LinkedIn DM) tailored to the candidate. Write to Airtable** for job/candidate tracking and downstream automation. Everything is plug-and-play, with no manual searching or copy-pasting required. Requirements n8n (Cloud or self-hosted) Airtable account + API access Apollo API or your preferred candidate source LLM provider: OpenAI or Anthropic LinkedIn enrichment API (RapidAPI, Apify, etc.) > ⚠️ Do not hardcode API keys in HTTP nodes. Always use Credentials in n8n. Airtable table specifications Create one base (e.g., Candidate Search – From Job Description) with two tables: Jobs Table Job Title (text) Job Description (long text) Job Location (text) Candidates (linked to Candidates table) Candidates Table Core fields: Name, LinkedIn URL, Job Title, Location, Image URL, Job Searches (linked) Assessment fields: Summary Fit Score, Executive Summary, Title Alignment, Skill Alignment, Industry Alignment, Seniority Alignment, Company Type Alignment, Educational Alignment, Potential Red Flags, Positive Signals, Final Recommendation, Next Steps Suggestion Outreach fields: Email Subject, Email Body, LinkedIn Message How to set up Connect credentials Add Airtable, Apollo/CRM, and OpenAI/Anthropic credentials under n8n Credentials. Create Airtable base/tables Follow the above spec for Jobs and Candidates. Match field names exactly to avoid mapping errors. Configure the trigger The workflow starts from a Form/Webhook node. It captures: Job Title (required) Job Description (required) Location (required) Target Companies (optional, comma-separated domains) Job title mutation The workflow uses an AI node to normalize the job title and generate up to 5 variations for broader candidate searches. Candidate search Apollo (or your CRM API) is queried with the generated titles and location filters. Results are deduped. AI scoring & structuring Candidates are scored 0–5 with clear reasoning (experience, industry, seniority, general fit). Profiles are formatted into structured JSON for Airtable. LinkedIn enrichment Enrichment API fetches missing data (geo, image, job history). Candidate assessment An AI model produces a full recruiter-ready evaluation (fit summary, strengths, red flags). Outreach generation The workflow drafts a concise cold email (<75 words) and LinkedIn DM (<60 words), consultative in tone. Write to Airtable All jobs and candidates (with assessments and outreach messages) are logged for review and integration. How to customize Swap Apollo with your CRM** (Greenhouse, Bullhorn, etc.). Adjust scoring prompts** to match your niche (sales, engineering, healthcare). Add custom filters** for target companies or industries. Change outreach tone** to align with your brand voice. Limit by score** (e.g., only push candidates with score ≥4). Security & best practices Store all keys in n8n Credentials (never in nodes). Use Set nodes to centralize editable variables (title, location, filters). Always add sticky notes in your workflow explaining steps. Rename nodes clearly for readability. Troubleshooting No candidates found?** Loosen title variations or broaden location. Low fit scores?** Refine keywords and required skills in scoring prompts. Airtable errors?** Double-check Base ID, Table ID, and field names. API rate limits?** Enable batching/pagination and increase intervals. SEO title: Build candidate shortlists from a job description to Airtable with Apollo, AI scoring, and personalized outreach Keywords: recruiting automation, Apollo people search, candidate enrichment, AI scoring, Airtable recruiting CRM, LinkedIn outreach, n8n workflow template

This workflow monitors product prices from BooksToScrape and sends alerts to a Discord channel via webhook when competitor's prices are lower than our prices. 🧩 Nodes Used Schedule (for daily or required schedule) If nodes (to check if checked or unchecked data exists) HTTP Request (for fetching product page ) Extract HTML (for extracting poduct price) Code(to clean and extract just the price number) Discord Webhook (send discord allerts) Sheets (extract and update) 🚀 How to Use Replace the Discord webhook URL with your own. Customize the scraping URL if you're monitoring a different site.(Sheet i used) Run the workflow manually or on a schedule. ⚠️ Important Do not use this for commercial scraping without permission. Ensure the site allows scraping (this example is for learning only).

How It Works The system collects real-time wearable health data, normalizes it, and uses AI to analyze trends and risk scores. It detects anomalies by comparing with historical patterns and automatically triggers alerts and follow-up actions when thresholds are exceeded. Setup Steps Configure Webhook Endpoint - Set up webhook to receive data from wearable devices Connect Database - Initialize storage for health metrics and historical data Set Normalization Rules - Define data standardization parameters for different devices Configure AI Model - Set up health score calculation and risk prediction algorithms Define Thresholds - Establish alert triggers for critical health metrics Connect Notification Channels - Configure email and Slack integrations Set Up Reporting - Create automated report templates and schedules Test Workflow - Run end-to-end tests with sample health data Workflow Template Webhook → Store Database → Normalize Data → Calculate Health Score → Analyze Metrics → Compare Previous → Check Threshold → Generate Reports/Alerts → Email/Slack → Schedule Follow-up Workflow Steps Ingest real-time wearable data via webhook, store and standardize it, and use GPT-4 for trend analysis and risk scoring. Monitor metrics against thresholds, trigger SMS, email, or Slack alerts, generate reports, and schedule follow-ups. Setup Instructions Configure webhook, database, GPT-4 API, notifications, calendar integration, and customize alert thresholds. Prerequisites Wearable API, patient database, GPT-4 key, email SMTP, optional Slack/Twilio, calendar integration. Use Cases Monitor glucose for diabetics, track elderly vitals/fall risk, assess corporate wellness, and post-surgery recovery alerts. Customization Adjust risk algorithms, add metrics, integrate telemedicine. Benefits Early intervention reduces readmissions and automates 80% of monitoring tasks.

Create GitHub issues from webhook input and send alerts to Telegram This workflow streamlines bug tracking by using a webhook to collect issue reports, automatically classifying and summarizing them with Gemini AI, then sending critical issues to GitHub and real-time notifications to Telegram. Optional manager approval is built in for low-priority reports. 🧑‍💻 Who’s it for This workflow is ideal for: Engineering teams needing automated issue tracking from multiple systems QA testers or customer support agents who log bugs via custom tools DevOps teams monitoring logs or error reports in real time Teams using GitHub for issue tracking and Telegram (or any messenger) for notifications ⚙️ How it works Webhook Trigger – Listens for incoming POST requests containing bug or task data. AI-Powered Classification – Uses the Gemini model to classify bugs as High or Low severity. Optional Approval – If severity is Low, it waits for a manager’s approval before proceeding. Bug Summary Generation – Passes through a filter and sends the input to Gemini to generate a clean summary. Create GitHub Issue – Submits the summarized issue to your GitHub repository. Telegram Notification – Sends a formatted message to a Telegram group or manager, depending on the path. 🛠️ How to set up Replace the GitHub node with your repo credentials and target repo. Set up the Telegram bot token and chat ID in the Telegram node. Customize the Gemini prompts for your preferred classification and summary logic. Define the conditions for “High” vs “Low” severity based on your data. 📋 Requirements A GitHub account with a personal access token (with repo access) A Telegram bot token and group chat ID Google Gemini API credentials (or your preferred AI model integration) 🔧 How to customize the workflow Swap Telegram with another messaging platform like Slack, Discord, or Microsoft Teams. Adjust classification rules to match your business logic. Change approval flow to notify a different person or add additional logic before sending to GitHub. Extend the webhook input format to support richer data, such as user info or system metadata.

How it works 🧠 AI-Powered News Update Bot for Zalo using Gemini and RSS Feeds This workflow allows you to build a smart Zalo chatbot that automatically summarizes and delivers the latest news using Google Gemini and RSS feeds. It’s perfect for keeping users informed with AI-curated updates directly inside Vietnam’s most popular messaging app. 🚀 What It Does Receives user messages via Zalo Bot webhook Fetches the latest articles from an RSS feed (e.g., AI news) Summarizes the content using Google Gemini Formats the response and sends it back to the user on Zalo 📱 What Is Zalo? Zalo is Vietnam’s leading instant messaging app, with over 78 million monthly active users—more than 85% of the country’s internet-connected population. It handles 2 billion messages per day and is deeply embedded in Vietnamese daily life, making it a powerful channel for communication and automation. 🔧 Setup Instructions 1. Create a Zalo Bot Open the Zalo app and search for "Zalo Bot Creator" Tap "Create Zalo Bot Account" Your bot name must start with "Bot" (e.g., Bot AI News) After creation, Zalo will send you a message containing your Bot Token 2. Configure the Webhook Replace [your-webhook URL] in Zalo Bot Creator with your n8n webhook URL Use the Webhook node in this workflow to receive incoming messages 3. Set Up Gemini Add your Gemini API key to the HTTP Request node labeled Summarize AI News Customize the prompt if you want a different tone or summary style 4. Customize RSS Feed Replace the default RSS URL with your preferred news source You can use any feed that provides timely updates (e.g., tech, finance, health) 🧪 Example Interaction User: "What's new today?" Bot: "🧠 AI Update: Google launches Gemini 2 with multimodal capabilities, revolutionizing how models understand text, image, and code..." ⚠️ Notes Zalo Bots currently do not support images, voice, or file attachments Make sure your Gemini API key has access to the model you're calling RSS feeds should be publicly accessible and well-formatted 🧩 Nodes Used Webhook HTTP Request (Gemini) RSS Feed Read Set & Format Zalo Message Sender (via API) 💡 Tips You can swap Gemini with GPT-4 or Claude by adjusting the API call Add filters to the RSS node to only include articles with specific keywords Use the Function node to personalize responses based on user history Built by Nguyen Thieu Toan (Nguyễn Thiệu Toàn) (https://nguyenthieutoan.com). Read more about this workflow by Vietnamese: https://nguyenthieutoan.com/share-workflow-n8n-zalo-bot-cap-nhat-tin-tuc/

This n8n template from Intuz provides a complete and automated solution for instant team-wide financial visibility. It actively monitors QuickBooks and, upon detecting a new invoice, immediately sends a detailed alert to your chosen Slack channel. For customized reporting, the workflow can pull specific keywords or data like the customer name, invoice amount, and due date directly into the Slack message, creating a complete, real-time feed of your company's sales activity. Use Cases Sales Team Visibility:** Instantly notify the sales channel when an invoice is generated for a deal they closed. Finance & Ops Sync:** Keep the finance team aware of all billing activities as they happen in a dedicated channel. Account Management:** Alert account managers when invoices are sent to their clients, allowing for proactive follow-up. Executive Dashboard:** Create a high-level #billing-feed channel for leadership to monitor revenue-generating activities in real time. How it Works 1. Instant Webhook Trigger: The workflow begins when an invoice is created or updated in QuickBooks. A configured webhook in your Intuit Developer Portal sends a real-time notification to n8n, instantly activating the flow. 2. Fetch Full Invoice Details: The initial webhook payload only contains a basic event notification. This node uses the invoice ID from that payload to query the QuickBooks API and retrieve the full invoice details, such as the customer's name, due date, and domain. 3. Format Key Data: A simple but essential Code node takes the raw data from QuickBooks and cleans it up. It extracts only the most important fields (ID, Domain, Customer Name, Due Date) and organizes them for the next step. 4. Send Slack Notification: The final node crafts a human-readable message and posts it to your chosen Slack channel. The message is dynamically populated with the invoice data, providing a clear and concise update for the whole team. For example: Invoice having ID: 160 having the Domain: QBO for the customer Rondonuwu Fruit and Vegi which is due on 2025-09-07 has been generated successfully. Setup Instructions To get this workflow running, follow these configuration steps: 1. Credentials: QuickBooks: Connect your QuickBooks account credentials to n8n. Slack: Connect your Slack account using OAuth2 credentials. 2. QuickBooks Webhook Configuration: First, activate this n8n workflow. This will make the webhook URL live. Copy the Production URL from the QuickBooks Webhook node. Log in to your Intuit Developer Portal, navigate to the webhooks section for your application, and paste the URL. Ensure you subscribe to Invoice events (e.g., Create, Update, etc.). 3. Node Configuration: Get an invoice: No configuration needed; it will automatically use your QuickBooks credentials. Send a message (Slack): In the parameters, select the Slack Channel where you want the notifications to be posted. Support If you need help setting up this workflow or require a custom version tailored to your specific use case, please feel free to reach out to the template author: Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

Who's it for Customer support teams, SaaS companies, and service businesses that need to quickly identify and respond to urgent customer issues. Perfect for organizations handling high ticket volumes where manual prioritization creates delays and missed critical issues. How it works This workflow automatically analyzes incoming Zendesk tickets using OpenAI's GPT-4 to determine urgency levels and routes high-priority issues to your team via Slack notifications. The system monitors new Zendesk tickets via webhook, extracts key information (subject, description, customer details), and sends this data to OpenAI for intelligent analysis. The AI considers factors like emotional language, business impact keywords, technical severity indicators, and customer context to assign an urgency score from 1-5. Based on the AI analysis, the workflow automatically updates the ticket priority in Zendesk, adds detailed reasoning as a private note, and sends formatted Slack notifications for high-priority issues (score 4+). The Slack alert includes ticket details, urgency reasoning, key indicators found, and direct links to the ticket for immediate action. How to set up Prerequisites: Zendesk account with API access OpenAI API key (GPT-4 access recommended) Slack workspace with webhook permissions n8n instance (cloud or self-hosted) Setup steps: Configure credentials in n8n: Add OpenAI API credential with your API key Add Zendesk API credential (email + API token) Add Slack API credential (bot token with chat:write permissions) Update Configuration Variables node: Set your Zendesk subdomain (e.g., "yourcompany" for yourcompany.zendesk.com) Configure Slack channel for urgent alerts (e.g., "#support-urgent") Adjust urgency threshold (1-5, default is 4) Set default assignee email for fallback scenarios Set up Zendesk webhook: Copy the webhook URL from the trigger node In Zendesk Admin, go to Settings > Extensions > Add target Create HTTP target with the copied URL and POST method Create a trigger for "Ticket is created" that sends to this target Test the workflow: Create a test ticket with urgent language ("system is down", "critical issue") Verify the AI analysis runs and priority is updated Check that Slack notifications appear for high-priority tickets Confirm ticket updates include AI reasoning in private notes Requirements Zendesk** account with API access and admin permissions for webhook setup OpenAI API key** with GPT-4 access (estimated cost: $0.01-0.05 per ticket analysis) Slack workspace** with bot creation permissions and access to notification channels n8n instance** (cloud subscription or self-hosted installation) How to customize the workflow Adjust AI analysis parameters: Modify the system prompt in the OpenAI node to focus on industry-specific urgency indicators Add custom keywords or phrases relevant to your business in the prompt Adjust the temperature setting (0.1-0.5) for more consistent vs creative analysis Configure priority mapping: Edit the Code node to change how urgency scores map to Zendesk priorities Add custom business logic based on customer tiers or product types Implement time-based urgency (e.g., higher priority during business hours) Enhance Slack notifications: Customize the Slack message blocks with additional fields (product, customer tier, SLA deadline) Add action buttons for common responses ("Acknowledge", "Escalate", "Assign to me") Route different urgency levels to different Slack channels Extend integrations: Add email notifications using the Email node for critical issues Integrate with PagerDuty or Opsgenie for after-hours escalation Connect to your CRM to enrich customer context before AI analysis Add Teams or Discord notifications as alternatives to Slack Advanced customizations: Implement machine learning feedback loops by tracking resolution times vs AI scores Add sentiment analysis as a separate factor in priority calculation Create daily/weekly summary reports of AI analysis accuracy Build approval workflows for certain priority changes before auto-updating