Workflow Templates

Automate Google Classroom: Topics, Assignments & Student Tracking Automate Google Classroom via the Google Classroom API to efficiently manage courses, topics, teachers, students, announcements, and coursework. Use Cases Educational Institution Management Sync rosters, post weekly announcements, and generate submission reports automatically. Remote Learning Coordination Batch-create assignments, track engagement, and auto-notify teachers on new submissions. Training Program Automation Automate training modules, manage enrollments, and generate completion/compliance reports. Prerequisites n8n (cloud or self-hosted) Google Cloud Console access for OAuth setup Google Classroom API enabled Google Gemini API key** (free) for the agent brain — or swap in any other LLM if preferred Setup Instructions Step 1: Google Cloud Project Create a new project in Google Cloud Console. Enable Google Classroom API. Create OAuth 2.0 Client ID credentials. Add your n8n OAuth callback URL as a redirect URI. Note down the Client ID and Client Secret. Step 2: OAuth Setup in n8n In n8n, open HTTP Request Node → Authentication → Predefined Credential Type. Select Google OAuth2 API. Enter your Client ID and Client Secret. Click Connect my account to complete authorization. Test the connection. Step 3: Import & Configure Workflow Import this workflow template into n8n. Link all Google Classroom nodes to your OAuth credential. Configure the webhook if using external triggers. Test each agent for API connectivity. Step 4: Customization You can customize each agent’s prompt to your liking for optimal results, or copy and modify node code to expand functionality. All operations use HTTP Request nodes, so you can integrate more tools via the Google Classroom API documentation. This workflow provides a strong starting point for deeper automation and integration. Features Course Topics List, create, update, or delete topics within a course. Teacher & Student Management List, retrieve, and manage teachers and students programmatically. Course Posts List posts, retrieve details and attachments, and access submission data. Announcements List, create, update, or delete announcements across courses. Courses List all courses, get detailed information, and view grading periods. Coursework List, retrieve, or analyze coursework within any course. Notes Once OAuth and the LLM connection are configured, this workflow automates all Google Classroom operations. Its modular structure lets you activate only what you need—saving API quota and improving performance.

Bulk WhatsApp Campaign Automation with Rapiwa API (Unofficial Integration) Who’s it for This n8n workflow lets you send bulk WhatsApp messages using your own number through Rapiwa API, avoiding the high cost and limitations of the official WhatsApp API. It integrates seamlessly with Google Sheets, where you can manage your contacts and messages with ease. Ideal for easy-to-maintain bulk messaging solution using their own personal or business WhatsApp number. This solution is perfect for small businesses, marketers, or teams looking for a cost-effective way to manage WhatsApp communication at scale. How it Works / What It Does Reads data from a Google Sheet where the Status column is marked as "pending". Cleans each phone number (removes special characters, spaces, etc.). Verifies if the number is a valid WhatsApp user using the Rapiwa API. If valid: Sends the message via Rapiwa. Updates Status = sent and Verification = verified. If invalid: Skips message sending. Updates Status = not sent and Verification = unverified. Waits for a few seconds (rate-limiting). Loops through the next item. The entire process is triggered automatically every 5 minutes. How to Set Up Duplicate the Sample Sheet: Use this format. Fill Contacts: Add columns like WhatsApp No, Name, Message, Image URL, and set Status = pending. Connect Google Sheets: Authenticate and link Google Sheets node inside n8n. Subscribe to Rapiwa: Go to Rapiwa.com and get your API key. Paste API Key: Use the HTTP Bearer token credential in n8n. Activate the Workflow: Let n8n take care of the automation. Requirements Google Sheets API credentials Configured Google Sheet (template linked above) WhatsApp (Personal or Business) n8n instance with credentials setup How to Customize the Workflow Add delay between messages**: Use the Wait node to introduce pauses (e.g., 5–10 seconds). Change message format**: Modify the HTTP Request node to send media or templates. Personalize content**: Include dynamic fields like Name, Image URL, etc. Error handling**: Add IF or SET nodes to capture failed attempts, retry, or log errors. Workflow Highlights Triggered every 5 minutes** using the Schedule Trigger node. Filters messages** with Status = pending. Cleans numbers* and *verifies WhatsApp existence** before sending. Sends WhatsApp messages** via Rapiwa (Unofficial API). Updates Google Sheets** to mark Status = sent or not sent and Verification = verified/unverified. Wait node** prevents rapid-fire sending that could lead to being flagged by WhatsApp. Setup in n8n 1. Connect Google Sheets Add a Google Sheets node Authenticate using your Google account Select the document and worksheet Use filter: Status = pending 2. Loop Through Rows Use SplitInBatches or a Code node to process rows in small chunks (e.g., 5 rows) Add a Wait node to delay 5 seconds between messages 3. Send Message via HTTP Node How the "Send Message Using Rapiwa" Node Sends Messages This node makes an HTTP POST request to the Rapiwa API endpoint: https://app.rapiwa.com/api/send-message It uses Bearer Token Authentication with your Rapiwa API key. When this node runs, it sends a WhatsApp message to the specified number with the given text and optional image. The Rapiwa API handles message delivery using your own WhatsApp number connected to their service. JSON Body**: { "number": "{{ $json['WhatsApp No'] }}", "message": "{{ $json['Message'] }}" } Sample Google Sheet Structure A Google Sheet formatted like this sample | SL | WhatsApp No | Name | Message | Image URL | Verification | Status | |----|----------------|------------------------|----------------------|---------------------------------------------------------------------------|--------------|---------| | 1 | 8801322827799 | SpaGreen Creative | This is Test Message | https://spagreen.sgp1.cdn.digitaloceanspaces.com/... | verified | sent | | 2 | 8801725402187 | Abdul Mannan Zinnat | This is Test Message | https://spagreen.sgp1.cdn.digitaloceanspaces.com/... | verified | sent | Tips Modify the Limit node to increase/decrease messages per cycle. Adjust the Wait node to control how fast messages are sent (e.g., 5–10s delay). Make sure WhatsApp numbers are properly formatted (e.g., 8801XXXXXXXXX, no +, no spaces). Store your Rapiwa API key securely using n8n credentials. Use publicly accessible image URLs if sending images. Always mark processed messages as "sent" to avoid duplicates. Use the Error workflow in n8n to catch failed sends for retry. Test with a small batch before going full-scale. Schedule the Trigger node for every 5 minutes to keep automation running. Useful Links Dashboard:** https://app.rapiwa.com Official Website:** https://rapiwa.com Documentation:** https://docs.rapiwa.com Support & Community Need help setting up or customizing the workflow? Reach out here: WhatsApp: Chat with Support Discord: Join SpaGreen Server Facebook Group: SpaGreen Community Website: SpaGreen Creative Envato: SpaGreen Portfolio

This n8n workflow template creates an efficient data analysis system that uses Google Gemini AI to interpret user questions about spreadsheet data and processes them through a specialized sub-workflow for optimized token usage and faster responses. What This Workflow Does Smart Query Parsing**: Uses Gemini AI to understand natural language questions about your data Efficient Processing**: Routes calculations through a dedicated sub-workflow to minimize token consumption Structured Output**: Automatically identifies the column, aggregation type, and grouping levels from user queries Multiple Aggregation Types**: Supports sum, average, count, count distinct, min, and max operations Flexible Grouping**: Can aggregate data by single or multiple dimensions Token Optimization**: Processes large datasets without overwhelming AI context limits Tools Used Google Gemini Chat Model** - Natural language query understanding and response formatting Google Sheets Tool** - Data access and column metadata extraction Execute Workflow** - Sub-workflow processing for data calculations Structured Output Parser** - Converts AI responses to actionable parameters Memory Buffer Window** - Basic conversation context management Switch Node** - Routes to appropriate aggregation method Summarize Nodes** - Performs various data aggregations 📋 MAIN WORKFLOW - Query Parser What This Workflow Does The main workflow receives natural language questions from users and converts them into structured parameters that the sub-workflow can process. It uses Google Gemini AI to understand the intent and extract the necessary information. Prerequisites for Main Workflow Google Cloud Platform account with Gemini API access Google account with access to Google Sheets n8n instance (cloud or self-hosted) Main Workflow Setup Instructions 1. Import the Main Workflow Copy the main workflow JSON provided In your n8n instance, go to Workflows → Import from JSON Paste the JSON and click Import Save with name: "Gemini Data Query Parser" 2. Set Up Google Gemini Connection Go to Google AI Studio Sign in with your Google account Go to Get API Key section Create a new API key or use an existing one Copy the API key Configure in n8n: Click on Google Gemini Chat Model node Click Create New Credential Select Google PaLM API Paste your API key Save the credential 3. Set Up Google Sheets Connection for Main Workflow Go to Google Cloud Console Create a new project or select existing one Enable the Google Sheets API Create OAuth 2.0 Client ID credentials In n8n, click on Get Column Info node Create Google Sheets OAuth2 API credential Complete OAuth flow 4. Configure Your Data Source Option A: Use Sample Data The workflow is pre-configured for: Sample Marketing Data Make a copy to your Google Drive Option B: Use Your Own Sheet Update Get Column Info node with your Sheet ID Ensure you have a "Columns" sheet for metadata Update sheet references as needed 5. Set Up Workflow Trigger Configure how you want to trigger this workflow (webhook, manual, etc.) The workflow will output structured JSON for the sub-workflow ⚙️ SUB-WORKFLOW - Data Processor What This Workflow Does The sub-workflow receives structured parameters from the main workflow and performs the actual data calculations. It handles fetching data, routing to appropriate aggregation methods, and formatting results. Sub-Workflow Setup Instructions 1. Import the Sub-Workflow Create a new workflow in n8n Copy the sub-workflow JSON (embedded in the Execute Workflow node) Import as a separate workflow Save with name: "Data Processing Sub-Workflow" 2. Configure Google Sheets Connection for Sub-Workflow Apply the same Google Sheets OAuth2 credential you created for the main workflow Update the Get Data node with your Sheet ID Ensure it points to your data sheet (e.g., "Data" sheet) 3. Configure Google Gemini for Output Formatting Apply the same Gemini API credential to the Google Gemini Chat Model1 node This handles final result formatting 4. Link Workflows Together In the main workflow, find the Execute Workflow - Summarize Data node Update the workflow reference to point to your sub-workflow Ensure the sub-workflow is set to accept execution from other workflows Sub-Workflow Components When Executed by Another Workflow**: Trigger that receives parameters Get Data**: Fetches all data from Google Sheets Type of Aggregation**: Switch node that routes based on aggregation type Multiple Summarize Nodes**: Handle different aggregation types (sum, avg, count, etc.) Bring All Data Together**: Combines results from different aggregation paths Write into Table Output**: Formats final results using Gemini AI Example Usage Once both workflows are set up, you can ask questions like: Overall Metrics: "Show total Spend ($)" "Show total Clicks" "Show average Conversions" Single Dimension: "Show total Spend ($) by Channel" "Show total Clicks by Campaign" Two Dimensions: "Show total Spend ($) by Channel and Campaign" "Show average Clicks by Channel and Campaign" Data Flow Between Workflows Main Workflow: User question → Gemini AI → Structured JSON output Sub-Workflow: Receives JSON → Fetches data → Performs calculations → Returns formatted table Contact Information For support, customization, or questions about this template: Email**: robert@ynteractive.com LinkedIn**: Robert Breen Need help implementing these workflows, want to remove limitations, or require custom modifications? Reach out for professional n8n automation services and AI integration support.

This n8n workflow template creates an intelligent data analysis system that converts natural language questions into Google Sheets SQL queries using OpenAI's GPT-4o model. The system generates proper Google Sheets query URLs and executes them via HTTP requests for efficient data retrieval. What This Workflow Does Natural Language to SQL**: Converts user questions into Google Sheets SQL syntax Direct HTTP Queries**: Bypasses API limits by using Google Sheets' built-in query functionality Column Letter Mapping**: Automatically maps column names to their corresponding letters (A, B, C, etc.) Structured Query Generation**: Outputs properly formatted Google Sheets query URLs Real-time Data Access**: Retrieves live data directly from Google Sheets Memory Management**: Maintains conversation context for follow-up questions Tools Used OpenAI Chat Model (GPT-4o)** - SQL query generation and natural language understanding OpenAI Chat Model (GPT-4.1 Mini)** - Result formatting and table output Google Sheets Tool** - Column metadata extraction and schema understanding HTTP Request Node** - Direct data retrieval via Google Sheets query API Structured Output Parser** - Formats AI responses into executable queries Memory Buffer Window** - Conversation history management Chat Trigger** - Webhook-based conversation interface Step-by-Step Setup Instructions 1. Prerequisites Before starting, ensure you have: An n8n instance (cloud or self-hosted) An OpenAI account with API access and billing setup A Google account with access to Google Sheets The target Google Sheet must be publicly accessible or shareable via link 2. Import the Workflow Copy the workflow JSON provided In your n8n instance, go to Workflows → Import from JSON Paste the JSON and click Import Save with a descriptive name like "Google Sheets SQL Query Generator" 3. Set Up OpenAI Connections Get API Key: Go to OpenAI Platform Sign in or create an account Navigate to API Keys section Click Create new secret key Copy the generated API key Important: Add billing information and credits to your OpenAI account Configure Both OpenAI Nodes: OpenAI Chat Model1 (GPT-4o): Click on the node Click Create New Credential Select OpenAI API Paste your API key Save the credential OpenAI Chat Model2 (GPT-4.1 Mini): Apply the same OpenAI API credential This handles result formatting 4. Set Up Google Sheets Connection Create OAuth2 Credentials: Go to Google Cloud Console Create a new project or select existing one Enable the Google Sheets API Go to Credentials → Create Credentials → OAuth 2.0 Client IDs Set application type to Web Application Add authorized redirect URIs (get this from n8n credentials setup) Copy the Client ID and Client Secret Configure in n8n: Click on the Get Column Info2 node Click Create New Credential Select Google Sheets OAuth2 API Enter your Client ID and Client Secret Complete the OAuth flow by clicking Connect my account Authorize the required permissions 5. Prepare Your Google Sheet Option A: Use the Sample Data Sheet Access the pre-configured sheet: Sample Marketing Data Make a copy to your Google Drive Important**: Set sharing to "Anyone with the link can view" Critical: Set sharing to "Anyone with the link can view" for HTTP access Copy the Sheet ID from the URL Update the Get Column Info2 node with your Sheet ID and column metadata sheet 6. Configure Sheet References Get Column Info2 Node: Set Document ID to your Google Sheet ID Set Sheet Name to your columns metadata sheet (e.g., "Columns") This provides the AI with column letter mappings HTTP Request Node: No configuration needed - it uses dynamic URLs from the AI agent Ensure your sheet has proper sharing permissions 7. Update System Prompt (If Using Custom Sheet) If using your own Google Sheet, update the system prompt in the AI Agent3 node: Replace the URL in the system message with your Google Sheet URL Update the GID (sheet ID) to match your data sheet Keep the same query structure format Contact Information Robert Ynteractive For support, customization, or questions about this template: Email**: robert@ynteractive.com LinkedIn**: Robert Breen Need help implementing this workflow, want to add security features, or require custom modifications? Reach out for professional n8n automation services and AI integration support.

Feedback Sentiment Workflow (Typeform → GCP → Notion/Slack/Trello) This template ingests feedback from Typeform, runs Google Cloud Natural Language sentiment analysis, routes based on sentiment, and then creates a Notion database page and posts a Slack notification for positive items, or creates a Trello card for negative items. The flow is designed for quick setup and safe sharing using placeholders for IDs and credentials. How it Works Typeform Trigger Captures each new submission and exposes answers like Name and the long-text Feedback field. Google Cloud Natural Language Analyzes the feedback text and returns a sentiment score in: documentSentiment.score Check Sentiment Score (IF) True branch: Score > 0 → Positive False branch: Score ≤ 0 → Non-positive Add Feedback to Notion (True branch) Creates a new page in a Notion database with mapped properties. Notify Slack (after Notion) Posts the feedback, author, and score to a Slack channel for visibility. Create Trello Card (False branch) Logs non-positive items to a Trello list for follow-up. Required Accounts Google Cloud Natural Language API** enabled (OAuth2 or service credentials). Notion integration** with database access to create pages. Slack app/bot token** with permission to post to the target channel. Typeform account** with a form including: Long Text feedback question Name field Notion Database Columns Name (title):** Person name or responder label Feedback (rich_text):** Full feedback text Sentiment Score (number):** Numeric score from GCP ∈ [-1, 1] Source (select/text):** "Typeform" for provenance Submitted At (date):** Timestamp from the trigger Customization Options Sentiment Threshold:** Adjust IF condition (e.g., ≥ 0.25) for stricter positivity. Slack Routing:** Change channel, add blocks/attachments for richer summaries. Trello Path:** Point to a triage list and include labels for priority. Field Mapping:** Update the expression for feedback question to match Typeform label. Database Schema:** Add tags, product area, or customer tier for reporting. Setup Steps Connect credentials: Typeform, GCP Natural Language, Notion, Slack, Trello. Replace placeholders in workflow JSON: Form ID Database ID Slack Channel Trello List ID Map fields: Set Feedback + Name expressions from Typeform Trigger output into Notion and Slack. Adjust IF threshold for your definition of "positive". Test with a sample response and confirm: Notion page creation Slack notification Trello card logging

Short Description (for listing) Import products from Google Sheets to Shopify with automatic handling of single products and multi-variant products (sizes, colors, etc.). Includes SKU management, inventory tracking, and image uploads via GraphQL API. Category E-commerce Productivity Data Import/Export Full Description Overview This workflow automates the process of importing products from a Google Sheet into your Shopify store. It intelligently detects and handles both simple products and products with multiple variants (like different sizes or colors), creating them with proper SKU management, pricing, inventory levels, and images. Key Features ✅ Dual Product Support: Handles single products and multi-variant products automatically ✅ Smart SKU Parsing: Automatically groups variants by parsing SKU format (e.g., 12345-SM, 12345-MD) ✅ Inventory Management: Sets stock levels for each variant at your default location ✅ Image Upload: Attaches product images from URLs ✅ GraphQL API: Uses Shopify's modern GraphQL API for reliable product creation ✅ Batch Processing: Process multiple products in one workflow run Use Cases Initial store setup with bulk product import Regular inventory updates from spreadsheet Migrating products from another platform Managing seasonal product catalogs Synchronizing products with external systems Requirements Shopify store with Admin API access Google Sheets API credentials n8n version 1.0+ Basic understanding of GraphQL (helpful but not required) What You'll Need to Configure Shopify Admin API token Your Shopify store URL (in 'set store url' node) Google Sheets connection (Optional) Vendor name and product type defaults Input Format Your Google Sheet should contain columns: Product Name SKU (format: BASESKU-VARIANT for variants) Size (or other variant option) Price On hand Inventory Product Image (URL) Products with the same name are automatically grouped as variants. How It Works Reads product data from your Google Sheet Groups products by name and detects if they have variants Switches to appropriate creation path (single or variant) Creates product in Shopify with options and variants Updates each variant with SKU and pricing Sets inventory levels at your location Uploads product images Technical Details Uses Shopify GraphQL Admin API (2025-04) Handles up to 100 variants per product Processes variants individually for accurate data mapping Includes error handling for missing data Supports one inventory location per run Common Modifications Change vendor name and product type Add more variant options (color, material, etc.) Customize product status (draft vs active) Modify inventory location selection Add product descriptions Perfect For Shopify store owners managing large catalogs E-commerce managers doing bulk imports Agencies setting up client stores Developers building automated product workflows Difficulty: Intermediate Estimated Setup Time: 15-30 minutes Nodes Used: 16 External Services: Shopify, Google Sheets

Who it's for This workflow is perfect for space enthusiasts, community managers, and content creators who want to automatically share stunning, curated space imagery with their Slack communities. It's ideal for teams that enjoy a daily dose of scientific inspiration and visually engaging content without any manual effort. What it does This workflow automates the creation and posting of a daily space image gallery to Slack. Every day at a scheduled time, it fetches three distinct images from NASA's public APIs: one from the Mars Rover, one from the EPIC satellite observing Earth, and one from the extensive Image Library. For each image, the workflow uses an AI model to generate a unique and poetic caption, transforming a simple image post into a more engaging piece of content. Finally, it combines these three images and their AI-generated captions into a single, beautifully formatted message and posts it to your designated Slack channel. As a bonus, it also saves a copy of the message to a Google Drive folder for archival purposes. How to set up Configure Variables: In the Workflow Configuration node, enter your NASA API Key in the nasaApiKey field and specify your target Slack channel name in the slackChannel field (e.g., general). Connect Credentials: You will need to add your credentials for the OpenAI Chat Model, Post to Slack, and Google Drive nodes. Activate Workflow: Once your credentials and variables are set, simply save and activate the workflow. Requirements A NASA API Key (free to generate). An OpenAI account and API key. A Slack workspace with permissions to post messages. A Google Drive account. How to customize the workflow Adjust the Schedule: Change the trigger time or frequency in the Daily 10:00 - Start Poll node. Change AI Tone: Modify the system message in the AI Agent node to alter the style, tone, or language of the generated captions. Swap Image Sources: Update the URLs in the Fetch nodes to pull images from different NASA APIs or use different search queries. Add More Channels: Duplicate the Post to Slack node and modify it to send notifications to other services like Discord or Telegram.

⭐ Google Review Sentiment Analysis & Slack Notification Workflow This workflow automates the process of collecting Google Business Profile reviews 🏪, analyzing customer sentiment with Google Gemini 🤖✨, and sending structured reports to Slack 💬. 🔑 Key Advantages 📥 Fetches Google Business Profile reviews for a given business and time period 🧠 Runs sentiment analysis using Gemini AI 📊 Consolidates comments, ratings, and trends into a JSON-based summary 🧩 Restructures results into Slack Block Kit format for easy readability 🚀 Sends automated sentiment reports directly to a Slack channel ⚙️ Set Up Essentials You’ll Need 🔑 Google Business Profile API access with project approval ✅ Enabled Google Business Profile API service 🔐 Gemini API credentials 💬 Slack workspace & channel for receiving reports 🚀 How to Get Started 🔧 Configure your Google Business Profile API and enable access 👤 Set the owner name and 📍 location to fetch reviews ⏳ Define the review time period using the Set Time Period node 🔗 Connect your Slack account and select a channel for notifications 🕒 Deploy and let the workflow run on schedule for automated insights

Automated Multi-Bank Balance Sync to BigQuery This workflow automatically fetches balances from multiple financial institutions (RBC, Amex, Wise, PayPal) using Plaid, maps them to QuickBooks account names, and loads structured records into Google BigQuery for analytics. Who’s it for? Finance teams, accountants, and data engineers managing consolidated bank reporting in Google BigQuery. How it works The Schedule Trigger runs weekly. Four Plaid API calls fetch balances from RBC, Amex, Wise, and PayPal. Each response splits out individual accounts and maps them to QuickBooks names. All accounts are merged into one dataset. The workflow structures the account data, generates UUIDs, and formats SQL inserts. BigQuery node uploads the finalized records. How to set up Add Plaid and Google BigQuery credentials, replace client IDs and secrets with variables, test each connection, and schedule the trigger for your reporting cadence.

Who's it for This template is for teams that want to stay updated on industry trends, tech news, or competitor mentions without manually browsing news sites. It's ideal for marketing, development, and research teams who use Slack as their central hub for automated, timely information. What it does / How it works This workflow runs on a daily schedule (default 9 AM), fetches the top articles from Hacker News for a specific keyword you define (e.g., 'AI'), and uses an AI agent with OpenRouter to generate a concise, 3-bullet point summary in Japanese for each article. The final formatted summary, including the article title, is then posted to a designated Slack channel. The entire process is guided by descriptive sticky notes on the canvas, explaining each configuration step. How to set up In the Configure Your Settings node, change the default keyword AI to your topic of interest and update the slack_channel to your target channel name. Click the OpenRouter Chat Model node and select your OpenRouter API key from the Credentials dropdown. If you haven't connected it yet, you will need to create a new credential. Click the Send Summary to Slack node and connect your Slack account using OAuth2 credentials. (Optional) Adjust the schedule in the Trigger Daily at 9 AM node to change how often the workflow runs. Activate the workflow. Requirements An n8n instance (Cloud or self-hosted). A Slack account and workspace. An OpenRouter API key stored in your n8n credentials. If self-hosting, ensure the LangChain nodes are enabled. How to customize the workflow Change the News Source:* Replace the *Hacker News* node with an *RSS Feed Read** node or another news integration to pull articles from different sources. Modify the AI Prompt:* In the *Summarize Article with AI** node, you can edit the system message to change the summary language, length, or tone. Use a Different AI Model:* Swap the *OpenRouter* node for an *OpenAI, **Anthropic, or any other supported chat model. Track Multiple Keywords:* Modify the workflow to loop through a list of keywords in the *Configure Your Settings** node to monitor several topics at once.

Complete incident workflow from detection through resolution to post-mortem, with full organizational context from Port's catalog. This template handles both incident triggered and resolved events from PagerDuty, automatically creating Jira tickets with context, notifying teams via Slack, calculating MTTR, and using Port AI Agents to schedule post-mortem meetings and create documentation. How it works The n8n workflow orchestrates the following steps: On Incident Triggered: PagerDuty webhook — Receives incident events from PagerDuty via POST request. Event routing — Routes to triggered or resolved flow based on event type. Port context enrichment — Uses Port's n8n node to query your software catalog for service context, on-call engineers, recent deployments, runbooks, and past incidents. AI severity assessment — OpenAI assesses severity based on Port context and recommends investigation actions. Escalation routing — Critical incidents automatically escalate to leadership Slack channel. Jira ticket creation — Creates incident ticket with full context, investigation checklist, and recommended actions. Team notification — Notifies the team's Slack channel with incident details and resources. On Incident Resolved: Port context extraction — Gets post-incident context from Port including stakeholders and documentation spaces. MTTR calculation — Calculates mean time to resolution from incident timestamps. Post-mortem generation — AI generates a structured post-mortem template with timeline. Port AI Agent scheduling — Triggers Port AI Agent to schedule post-mortem meeting, invite stakeholders, and create documentation. Resolution notification — Notifies team with MTTR, post-mortem document link, and meeting details. Metrics logging — Logs MTTR metrics back to Port for service reliability tracking. Setup [ ] Register for free on Port.io [ ] Configure Port with services, on-call schedules, and deployment history [ ] Set up Port AI agents for post-mortem scheduling [ ] Connect PagerDuty webhook for incident events [ ] Configure Jira project for incident tickets (use project key 'INC' or customize) [ ] Set up Slack channels for alerts (#incidents and #leadership-alerts) [ ] Add OpenAI credentials for severity assessment [ ] Test with a sample incident event [ ] You should be good to go! Prerequisites You have a Port account and have completed the onboarding process. Port's integrations are configured (GitHub, Jira, PagerDuty if available). You have a working n8n instance (Cloud or self-hosted) with Port's n8n custom node installed. PagerDuty account with webhook capabilities. Jira Cloud account with appropriate project permissions. Slack workspace with bot permissions to post messages. OpenAI API key for severity assessment and post-mortem generation. ⚠️ This template is intended for Self-Hosted instances only.

This n8n template from Intuz provides a complete solution to automate the syncing of new subscribers from Google Sheets to MailerLite. It intelligently identifies and adds only new contacts, preventing duplicates and ensuring your email lists are clean and accurate. Who's this workflow for? Marketing Teams Email Marketers Small Business Owners Community Managers How it works 1. Read from Google Sheets: The workflow begins by reading all contact rows from your designated Google Sheet. 2. Check for Existing Subscribers: For each contact, it performs a search in MailerLite to check if a subscriber with that email address already exists. 3. Handle Duplicates: If the subscriber is found in MailerLite, the workflow stops processing that specific contact, preventing any duplicates from being created. 4. Create New Subscribers: If the contact is not found, the workflow proceeds to create a new subscriber in MailerLite, using all the details from the Google Sheet (like name, company, and country) and assigns them to the specified group. Setup Instructions 1. Google Sheets Setup: Connect your Google Sheets account to n8n. Create a sheet with the required columns: Email, first_name, last_name, Company, Country, and group_id. In the Get row(s) in sheet node, select your credentials and specify the Document ID and Sheet Name. 2. MailerLite Setup: Connect your MailerLite account to n8n using your API key. In both the Get a subscriber and Create subscriber... nodes, select your MailerLite credentials. Make sure the group_id values in your Google Sheet correspond to valid Group IDs in your MailerLite account. 3. Activate Workflow: Save the workflow and click "Execute workflow" to run the sync whenever you need to update your subscriber list. Connect with us 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