Workflow Templates

Automated QuickBooks Invoice to Custom PDF & Email This n8n workflow automates the entire QuickBooks invoicing process — from creation to delivery. When a new invoice is generated in QuickBooks Online, it automatically fetches the data, applies your company branding, converts it into a professional multi-page PDF via Gotenberg, and emails it directly to your client. Key Features: ⚡ Fully Automated: Triggers instantly on new QuickBooks invoices. 🧾 Custom Branding: Adds your logo and signature from public URLs. 🎨 Modern PDF Design: Clean, professional multi-page layout with smart totals and “Page X of Y” footers. 📧 Automatic Emailing: Sends the final PDF in a formatted email to your customer. Requirements: QuickBooks Online, n8n instance, Gotenberg (HTML→PDF converter), and public URLs for logo/signature.

Automatically Assign Jira Service Management Reporter from Forwarded Emails This workflow solves a common problem in Jira Service Management: when an email is forwarded to create a ticket, Jira often sets the forwarding system (e.g., support@yourcompany.com) as the reporter, not the original customer. This template automates the process of parsing the original sender's details from the email body and correctly assigning them as the ticket's reporter. If the customer doesn't exist in Jira, a new customer profile is created automatically before the ticket is assigned. What it Does Triggers on New Issue: The workflow starts when a new issue is created in a specified Jira project. Filters Forwarded Emails: An If node checks if the issue was created by one of your internal forwarding email addresses. The workflow only proceeds for these specific issues. Parses Details: A Code node uses regular expressions to parse the issue description (the forwarded email's body) and extract the original sender's name and email address. Searches for Existing Customer: An HTTP Request node checks if a customer with the extracted email already exists in your Jira Service Desk. Creates New Customer: If the customer is not found, another HTTP Request node creates a new customer profile in Jira Service Management. Assigns Reporter: Finally, a Jira node updates the issue's "Reporter" field to the existing or newly created customer, ensuring the ticket is correctly associated with the original sender. Use Cases Shared Support Inboxes**: Automatically process emails sent to a general support inbox (e.g., support@company.com) that are then forwarded to Jira. Departmental Forwarding**: Handle tickets forwarded from specific departments (e.g., sales@company.com or billing@company.com) and assign the original sender correctly. Personal Email Forwarding**: Useful when a team member forwards a customer email from their personal inbox to the Jira Service Management-connected address. Customization The Parse Details From Description node uses a regular expression (regex) to find the sender's email. The default regex is designed for standard forwarded emails that look like this: From: John Doe <john.doe@example.com> If your email client forwards emails in a different format, you may need to adjust the regex in the Code node. For example, if your format is From: [john.doe@example.com], you would need to update the regex pattern to match this structure. Troubleshooting Reporter Not Being Updated**: Verify that the forwarding email addresses in the Filter Forwarding Emails node are correct. Check the body of the Jira ticket's description to ensure the forwarded email content is present and in a format the regex can parse. Customer Not Found/Created**: Ensure your Jira API credentials have the necessary permissions to search for and create customers in Jira Service Management. Workflow Not Triggering**: Confirm that the Jira Trigger is correctly configured for the right project and that the webhook is active in your Jira instance. Requirements An n8n instance (self-hosted or cloud). Jira Software Cloud API credentials with Service Management permissions. How to Set Up Connect Credentials: In the Jira Trigger, Jira, and HTTP Request nodes, select your Jira Software Cloud API credentials. Configure Trigger: In the Jira Trigger node, select the Jira project you want this workflow to monitor. Set Filter Emails: In the Filter Forwarding Emails (If) node, replace the placeholder email addresses with the internal email addresses that forward mail to Jira. Update Jira Domain: In both HTTP Request nodes (Search for Existing Customer and Create Customer), replace the YOUR_JIRA_DOMAIN placeholder with your actual Atlassian domain (e.g., my-company.atlassian.net). Activate Workflow: Save and activate the workflow.

Generate Invoices and Send Reminders for Customers with Jotform and QuickBooks This workflow automates the entire process of receiving a product/service order, checking or creating a customer in QuickBooks Online (QBO), generating an invoice, emailing it — all triggered by a form submission (via Jotform), and sending invoice reminders. How It Works Receive Submission Triggered when a user submits a form. Collects data like customer details, selected product/service, etc. Check If Customer Exists Searches QBO to determine if the customer already exists. If Customer Exists:* *Update** customer details (e.g., billing address). If Customer Doesn’t Exist:* *Create** a new customer in QBO. Get The Item Retrieves the selected product or service from QBO. Create The Invoice Generates a new invoice for the customer using the item selected. Send The Invoice Automatically sends the invoice via email to the customer. Store The Invoice In DB Stores the needed invoice details in the DB. Send Reminders Every day at 8 AM, the automation checks each invoice to decide whether to: send a reminder email, skip and send it later, or delete the invoice from the DB (if it's paid or all reminders have been sent). Who Can Benefit from This Workflow? Freelancers** Service Providers** Consultants & Coaches** Small Businesses** E-commerce or Custom Product Sellers** Requirements Jotform webhook setup, more info here QuickBooks Online credentials, more info here Email setup, update email nodes (Send reminder email & Send reminders sent summary) Create data table with the following columns: invoiceId (string) remainingAmount (number) currency (string) remindersSent (number) lastSentAt (date time) Update Add reminders config node so update the data table id and intervals in days (default is after 2 days, then after 3 days and finally after 5 days ) LLM model credentials

⚡Auto Rename n8n Workflow Nodes with AI✨ This workflow uses AI to automatically generate clear and descriptive names for every node in your n8n workflows. It analyzes each node's type, parameters, and connections to create meaningful names, making your workflows instantly readable. Who is it for? This workflow is for n8n users who manage complex workflows with dozens of nodes. If you've ever: Built workflows full of generic names like HTTP Request 2 or Edit Fields 1 Struggled to understand your own work after a few weeks Copied workflows from others with unclear node names Spent hours manually renaming nodes one by one ...then this workflow will save you significant time and effort. Requirements n8n API Credentials**: Must be configured to allow listing and updating workflows AI Provider Credentials**: An API key for your preferred AI provider (OpenRouter is used currently) How it works Trigger: Launch via form (select from dropdown) or manual trigger (quick testing with pre-selected workflow) Fetch: Retrieve the target workflow's JSON and extract nodes and connections Generate: Send the workflow JSON to the AI, which creates a unique, descriptive name for every node Validate: Verify the AI mapping covers all original node names Apply: If valid, update all node names, parameter references, and connections throughout the workflow Save: Save/Update the workflow with renamed nodes and provide links to both new and previous versions If validation fails (e.g., AI missed nodes), the workflow stops with an error. You can modify the error handling to retry or loop back to the AI node. Setup Connect n8n API credentials Open any n8n node in the workflow and make sure your n8n API credentials is connected Configure AI provider credentials Open the "OpenRouter" node (or replace with your preferred AI) Add your API credentials Adjust the model if needed (current: openai/gpt-5.1-codex-mini) Test the workflow Use Manual Trigger for quick testing with a pre-selected workflow Use Form Trigger for a user-friendly interface with workflow selection Important notice If you're renaming a currently opened workflow, you must reload the page after execution to see the latest version, n8n doesn't automatically refresh the canvas when workflow versions are updated via API. Need help? If you're facing any issues using this workflow, join the community discussion on the n8n forum.

Description: Stay ahead of payment disputes with this automated n8n workflow that integrates Stripe, Slack, and ClickUp. Perfect for finance teams, payment ops specialists, and SaaS businesses, this template fetches disputes directly from Stripe, analyzes urgency, and instantly notifies your team with rich, formatted alerts. High-priority disputes are flagged, pushed into Slack for immediate visibility, and tracked in ClickUp with due dates aligned to Stripe evidence deadlines—ensuring no dispute ever slips through the cracks. For lower-priority or resolved cases, the workflow provides concise updates and maintains an audit trail. No more manual Stripe checks, late responses, or missed deadlines—this workflow turns dispute management into a proactive, structured process. What This Template Does (Step-by-Step): 🟢 Trigger: Manual or Scheduled Execution Run the workflow on demand or schedule it (e.g., every 4 hours). 📥 Fetch Stripe Disputes Calls the Stripe API to retrieve all active disputes in your account. 📊 Validate & Format Data Ensures disputes exist, then enriches data with formatted amounts, deadlines, and customer info. ⚖️ Priority Logic Determines urgency based on dispute status, evidence deadlines, and transaction amount. 🚨 High Priority Path • Sends urgent Slack alert with full dispute details • Creates a high-priority ClickUp task with due dates • Flags immediate action required 📋 Standard Path • Sends standard Slack alert for non-urgent cases • Creates a ClickUp task with appropriate priority levels ℹ️ No Disputes Path Sends a Slack summary confirming no new disputes, maintaining a clear audit trail. ✅ Workflow Completion Confirms all disputes are processed, logged, and assigned—ready for your team to take action. Required Integrations: ✅ Stripe API (for dispute data) ✅ Slack API (for team alerts) ✅ ClickUp API (for task management) Perfect For: 💳 FinOps and payment operations teams monitoring transactions 🏢 SaaS platforms or e-commerce handling large payment volumes 🛡️ Risk and compliance teams tracking disputes and deadlines 📈 Businesses scaling customer payment handling and case management Why Use This Template? ✔️ Never miss a dispute deadline ✔️ Automated priority assessment saves hours of manual checks ✔️ Seamlessly integrates alerts + task tracking ✔️ Provides full visibility and accountability for dispute resolution

This workflow automates the generation of a daily stock market report, identifying the top gainers and losers among the top 100 stocks. It fetches real-time stock data, processes it to highlight significant price movements, and delivers formatted alerts via WhatsApp and email. Quick Notes Ensure the Twelve Data API key and stock symbols are correctly configured. Verify recipient lists for WhatsApp and email alerts are up-to-date. Confirm the workflow triggers at 5:00 PM (IST) from Monday to Friday. Process Flow Trigger the workflow daily at 5:00 PM (IST) with the Daily Market Change Trigger node. Configure API key, stock symbols, and alert recipients using the Configuration Variables node. Fetch stock data from Twelve Data API with the Fetch Stock Data from Twelve Data node. Process stock data to identify top gainers and losers with the Process Stock Movements node. Format WhatsApp messages with the Format WhatsApp Message node. Send WhatsApp alerts with the Send WhatsApp Alert node. Format email content with the Format Email Content node. Send email alerts with the Send Email Alert node. Output Getting Started Import the workflow into n8n and configure Twelve Data API credentials. Set up WhatsApp and email service integrations. Run a test execution to ensure data fetching and alert delivery work as expected. Tailored Adjustments Adjust the Process Stock Movements node to change the number of top gainers/losers. Modify the Configuration Variables node to include additional stock symbols or recipient lists.

This workflow automates the generation of a daily crypto market report, identifying the top 24-hour gainers and losers among the top 100 cryptocurrencies. It fetches real-time data, processes it to highlight significant price movements, and delivers formatted alerts via WhatsApp and email. Quick Notes Ensure the CoinGecko API key is correctly configured. Verify phone numbers and email addresses for alert recipients. Confirm the workflow triggers at 00:00 UTC daily. Process Flow Trigger the workflow daily at 00:00 UTC with the Daily Crypto Trigger node. Configure phone numbers, email addresses, and API key with the Set Configuration Variables node. Fetch crypto data from CoinGecko API with the Fetch Crypto Data from CoinGecko node. Process crypto data to rank top 24-hour movements with the Process Crypto Movements node. Format WhatsApp messages with the Format WhatsApp Message node. Send WhatsApp alerts with the Send WhatsApp Alert node. Format email content with the Format Email Content node. Send email alerts with the Send Email Alert node. Output Getting Started Import the workflow into n8n and set up CoinGecko API credentials. Configure WhatsApp and email service integrations. Run a test execution to verify data fetching and alert delivery. Tailored Adjustments Adjust the Process Crypto Movements node to change the number of top gainers/losers. Modify the Set Configuration Variables node to include additional recipient contacts or API parameters.

This n8n workflow pulls campaign data from Google Sheets, summarizes it using OpenAI, and sends a performance recap via Outlook email. ✅ Step 1: Connect Google Sheets In n8n, go to Credentials → click New Credential Select Google Sheets OAuth2 API Log in with your Google account and authorize Use a spreadsheet with: Column names in the first row Data in rows 2–100 Example format: 📄 Sample Marketing Sheet ✅ Step 2: Connect OpenAI Go to OpenAI API Keys Make sure you have a payment method set under Billing In n8n, create a new OpenAI API credential Paste your API key and save 📬 Need Help? Feel free to contact me if you run into issues: 📧 robert@ynteractive.com 🔗 LinkedIn

🎙️ Audio-to-Insights Workflow (Form Upload + Google Drive Link) Description This workflow enables seamless speech-to-text transcription, AI-powered summarization, sentiment analysis, and automated email delivery. It supports two different input modes: Form Upload (Local File)** Form Submission (Google Drive Link)** How it Works Input Form 1: Upload an audio file (e.g., .mp3,.wav,.mp4) Form 2: Submit a Google Drive link File Handling Local uploads go directly to AssemblyAI. Drive links are parsed → File ID extracted → File fetched → Sent to AssemblyAI. Transcription AssemblyAI generates transcript text with punctuation and highlights. Workflow loops with Wait + If until transcript status = completed. AI Analysis Transcript is passed to OpenAI. Generates a structured output including: Executive summary Sentiment label & score Key points Action items Notable quotes Topics Email Delivery A formatted email is sent via Gmail with the summary and insights. Features Dual input support: Google Drive OR direct upload Handles long-running jobs with Wait + If polling AI-powered transcript analysis with structured JSON Automated sentiment scoring and summary generation Professional HTML email reports Requirements AssemblyAI API Key – transcription Google Drive OAuth2 – file fetch OpenAI API Key – summarization & sentiment analysis Gmail OAuth2 – email delivery How to Use Import this workflow into your n8n instance. Add and configure the required credentials. Update placeholders for: AssemblyAI API Key Google Drive Link Gmail ID Trigger via either form (local file or Google Drive link). 5.For long recordings, split before uploading (10–20 min per chunk, 2–5s overlap).Keep audio consistent (e.g., WAV/MP3, 16 kHz mono if possible).Process chunks sequentially and combine summaries/action items at the end. Customising this Workflow Adjust the OpenAI prompt to fit your reporting style (executive summary, bullet points, etc.). Extend email formatting with logos or branding. Add Slack, CRM, or Notion integrations for distribution. Use Cases Meeting or lecture transcription with summaries Podcast analysis with highlights and quotes Business call reviews with action item extraction Academic seminar notes emailed automatically

Template presentation This template generates a sales follow-up presentation in Google Slides after a sales call recorded in Claap. The workflow is simplified to showcase the main use case. You can customize and enrich this workflow by connecting to the CRM, researching data online or adding more files in the presentation. The presentation template used in this workflow is available here. Workflow configuration Create a webhook in Claap, by following this article. Edit the labels that trigger the workflow and route on the relevant presentation. Fill your Open AI credentials by creating an API Key in OpenAI Platform Edit the presentation personalization details (user set as editor, content, title) Fill your Slack credentials by following steps in this video.

Build a powerful AI chatbot that provides precise answers from your own company's knowledge base. This template provides a smart AI agent that connects to Lookio, a platform where you can easily upload your documents (from Notion, Jira, Slack, etc.) to create a dedicated knowledge source. What makes this agent "smart" is its efficiency. It's configured to handle simple greetings and small talk on its own, only using its powerful (and paid) knowledge retrieval tool when a user asks a genuine question. This cost-saving logic makes it perfect for building production-ready internal helpdesks, customer support bots, or any application where you need accurate, source-based answers. Who is this for? Customer support teams:** Build internal bots that help agents find answers instantly from your support documentation and knowledge bases. Product & engineering teams:** Create a chatbot that can answer technical questions based on your product documentation or internal wikis. HR departments:** Deploy an internal assistant that can answer employee questions based on company handbooks, policies, and procedures. Any business with a knowledge base:** Provide an interactive, conversational way for employees or customers to access information locked away in your documents. What problem does this solve? Provides accurate, grounded answers:** Ensures the AI agent's responses are based on your trusted, private documents, not the open internet, which prevents factual errors and "hallucinations." Makes your knowledge accessible:** Transforms your static documents and knowledge bases into an interactive, 24/7 conversational resource. Optimizes for cost and efficiency:** The agent is intelligent enough to handle simple small talk without making unnecessary API calls to your knowledge base, saving you credits and money. Simplifies RAG setup:** Provides a ready-to-use template for a common RAG (Retrieval-Augmented Generation) pattern, with the complexities of document management and retrieval handled by the Lookio platform. How it works First, build your knowledge base in Lookio: The process starts on the Lookio platform. You upload your documents (from Notion, Jira, PDFs, etc.) and create an "assistant" which becomes your secure, queryable knowledge base. A user asks a question: The n8n workflow begins when a user sends a message via the Chat Trigger. The agent makes a decision: The AI Knowledge Agent, guided by its system prompt, analyzes the user's message. If it's a simple greeting like "hi," it will respond directly. If it's a substantive question that requires specific knowledge, it decides to use its "Query knowledge base" tool. Query the Lookio knowledge base: The agent passes the user's question to the HTTP Request Tool. This tool securely calls the Lookio API with your specific Assistant ID and API key. Deliver the fact-based answer: Lookio searches your documents, synthesizes a precise answer, and sends it back to the workflow. The n8n agent then presents this answer to the user in the chat interface. Architectural Approaches to RAG in n8n with Lookio From a workflow perspective, integrating RAG natively in n8n involves orchestrating multiple nodes for data handling, embedding, and vector searches. This method provides high visibility and control over each step. An alternative architectural pattern is to use an external RAG service like Lookio, which consolidates these steps into a single HTTP Request node. This simplifies the workflow's structure by abstracting the multi-stage RAG process into one API endpoint. Setup Set up your Lookio assistant (Prerequisite): First, go to Lookio, sign up (you get 50 free credits), create an assistant with your documents, and from your settings, copy your API Key and Assistant ID. Configure the Lookio tool: In the Query knowledge base (HTTP Request Tool) node: Replace the <your-assistant-id> placeholder with your actual Assistant ID. Replace the <your-lookio-api-key> placeholder with your actual API Key. Connect your AI model: In the OpenAI Chat Model node, connect your AI provider credentials. Activate the workflow. Your smart knowledge base agent is now live and ready to chat! Taking it further Adjust retrieval quality:* In the *Query knowledge base** node, you can change the query_mode from flash (fastest) to deep for higher quality but slightly slower answers, depending on your needs. Add more tools:** Enhance your agent by giving it other tools, like a web search for when the internal knowledge base doesn't have an answer, or a calculator for performing computations. Deploy it anywhere:* Swap the *Chat Trigger* for a *Slack* or *Discord** trigger to deploy your agent right where your team works.

Overview Create hyper-personalized cold outreach messages at scale by combining Google Sheets, web scraping, and AI. This workflow is perfect for sales teams, SDRs, and agency owners looking to boost reply rates with icebreakers that actually feel personal. It takes lead info from a Google Sheet—including name, email, company, and website—then visits each site, pulls meaningful text, and crafts a tailored message using AI. The personalized message is then written back into your lead sheet, ready for use in cold email, LinkedIn DMs, or CRM enrichment. Who’s it for Cold email outreach specialists B2B sales and SDR teams Lead generation agencies Founders doing outbound manually How it works Pull lead data from Google Sheets Loop through each lead and scrape their website using an HTTP node Clean and format the website content Use OpenAI to generate a custom-written icebreaker for each lead Write the final icebreaker back into the spreadsheet How to set up Connect your Google Sheets account Replace the spreadsheet ID and column names with your own Set up your OpenAI credentials (or whichever LLM you prefer) Tweak the prompt for tone or style Hit "Execute Workflow" and watch the sheet populate Requirements Google Sheets credentials OpenAI (or any compatible LLM node) The websites listed must be publicly accessible and static How to customize Modify the scraping logic to focus on specific sections (e.g. About page, Case Studies) Adjust the AI prompt to match your brand’s tone Add filtering logic to skip low-value leads Integrate with your CRM to send the data downstream