Workflow Templates

This automation syncs your Invoice PDFs from Stripe to a (AWS) S3 Bucket each month, in a folder of your choice, with the following subPath: yourFolder/invoiceYear/invoiceMonth/fileName Fill in your Credentials and Settings in the Nodes marked with "*". You can adjust this Workflow to your needs. You can also override the yearand month in the ENV* Node for manual syncs. It will sync every Invoice PDF which created-date is greater then the provided year and month. It will automatically set the day to the first day of the desired month. Enjoy the Workflow! ❤️ https://let-the-work-flow.com Workflow Automation & Development

Remember when you were doing some large research and wanted to quickly bookmark a page and save it, only to find premium options? Worry not; n8n got you covered. You can now create a simple bookmarking app straight to your browser using simple scrips on your browser called bookmarklets. A bookmarklet is a bookmark stored in a web browser that contains JavaScript commands that add new features to the browser. To create one, we need to add a short script to the bookmark tab of our browser like below A simple hack is to open a new tab and click on the star that appears on the right side Now that we have our bookmark, it's time for the fun part. Right-click on the bookmark we just created and select the edit option. This will allow you to set the name you want for your bookmark and the destination URL. The URL used here will be the script that shall "capture" the page we want to bookmark. The code below has been used and tested to work for this example javascript:(() => { var currentUrl = window.location.href; var webhookUrl = 'https://$yourN8nInstanceUrl/webhook/1rxsxc04b027-39d2-491a-a9c6-194289fe400c'; var xhr = new XMLHttpRequest(); xhr.open('POST', webhookUrl, true); xhr.setRequestHeader('Content-Type', 'application/json'); var data = JSON.stringify({ url: currentUrl }); xhr.send(data); })(); Your Bookmark should look like something like this Now that we have this setup, we are now going to n8n to receive the data sent by this script. Create a new webhook node that receives the POST request as in the workflow and replace $yourN8nInstanceUrl with your actual n8n instance. This workflow can then be configured to send this data to a notion database. Make sure the notion database has all the required permissions before executing the workflow. Otherwise the URLs will not be saved

This workflow shows how you can get your OpenAI assistant to call an n8n workflow as a tool. Since you can put almost any functionality in an n8n workflow, this means you can give your assistant access to almost any data source. Note that to use this template, you need to be on n8n version 1.19.4 or later.

Have you ever wanted to throttle Plex when connecting remotely to your server? Well here is the script for you! The instructions to deploy are below: You will need: A plex server with Plex Pass (for webhooks) n8n running locally (either in docker on via the desktop app) Qbittorent with WebUI enabled Begin by installing n8n by visiting n8n.io. You can install the desktop version or the docker version, whichever works best for your but I'm doing this on my desktop version of n8n. Copy the code from this page into your n8n install canvas. You should see the script appear before your eyes. From there, you Double click on the Webhook node at the beginning of the script. Copy both the Test and Production URLs that appear there. Now make your way to Plex and visit your settings. On the left, you should see the webhooks option if you have Plex Pass. This will setup your triggers. Next visit your qBitTorrent instance and enable WebUI. Notate your Username, Password, and Port. You will also need to know the IP of the machine that qbittorent is running on. If you have an iPhone you can connect to the same wireless network as your computer and use the Fing app to scan the network for the IP. Open up the script and edit the Global Variables to reflect the values you copied. Hit save at the top right, and then activate the script. Enjoy!!

CallForge - AI-Powered Product Insights Processor from Sales Calls Automate product feedback extraction from AI-analyzed sales calls and store structured insights in Notion for data-driven product decisions. 🎯 Who is This For? This workflow is designed for: ✅ Product managers tracking customer feedback and feature requests. ✅ Engineering teams identifying usability issues and AI/ML-related mentions. ✅ Customer success teams monitoring product pain points from real sales conversations. It streamlines product intelligence gathering, ensuring customer insights are structured, categorized, and easily accessible in Notion for better decision-making. 🔍 What Problem Does This Workflow Solve? Product teams often struggle to capture, categorize, and act on valuable feedback from sales calls. With CallForge, you can: ✔ Automatically extract and categorize product feedback from AI-analyzed sales calls. ✔ Track AI/ML-related mentions to gauge customer demand for AI-driven features. ✔ Identify feature requests and pain points for product development prioritization. ✔ Store structured feedback in Notion, reducing manual tracking and increasing visibility across teams. This workflow eliminates manual feedback tracking, allowing product teams to focus on innovation and customer needs. 📌 Key Features & Workflow Steps 🎙️ AI-Powered Product Feedback Processing This workflow processes AI-generated sales call insights and organizes them in Notion databases: Triggers when AI sales call data is received. Detects product-related feedback (feature requests, bug reports, usability issues). Extracts key product insights, categorizing feedback based on customer needs. Identifies AI/ML-related mentions, tracking customer interest in AI-driven solutions. Aggregates feedback and categorizes it by sentiment (positive, neutral, negative). Logs insights in Notion, making them accessible for product planning discussions. 📊 Notion Database Integration Product Feedback** → Logs feature requests, usability issues, and bug reports. AI Use Cases** → Tracks AI-related discussions and customer interest in machine learning solutions. 🛠 How to Set Up This Workflow 1. Prepare Your AI Call Analysis Data Ensure AI-generated sales call insights are available. Compatible with Gong, Fireflies.ai, Otter.ai, and other AI transcription tools. 2. Connect Your Notion Database Set up Notion databases for: 🔹 Product Feedback (logs feature requests and bug reports). 🔹 AI Use Cases (tracks AI/ML mentions and customer demand). 3. Configure n8n API Integrations Connect your Notion API key** in n8n under “Notion API Credentials.” Set up webhook triggers** to receive AI-generated sales insights. Test the workflow** using a sample AI sales call analysis. 🔧 How to Customize This Workflow 💡 Modify Notion Data Structure – Adjust fields to align with your product team's workflow. 💡 Refine AI Data Processing Rules – Customize how feature requests and pain points are categorized. 💡 Integrate with Slack or Email – Notify teams when recurring product issues emerge. 💡 Expand with Project Management Tools – Sync insights with Jira, Trello, or Asana to create product tickets automatically. ⚙️ Key Nodes Used in This Workflow 🔹 If Nodes – Detect if product feedback, AI mentions, or feature requests exist in AI data. 🔹 Notion Nodes – Create and update structured feedback entries in Notion. 🔹 Split Out & Aggregate Nodes – Process multiple insights and consolidate AI-generated data. 🔹 Wait Nodes – Ensure smooth sequencing of API calls and database updates. 🚀 Why Use This Workflow? ✔ Eliminates manual sales call review for product teams. ✔ Provides structured, AI-driven insights for feature planning and prioritization. ✔ Tracks AI/ML mentions to assess demand for AI-powered solutions. ✔ Improves product development strategies by leveraging real customer insights. ✔ Scalable for teams using n8n Cloud or self-hosted deployments. This workflow empowers product teams by transforming sales call data into actionable intelligence, optimizing feature planning, bug tracking, and AI/ML strategy. 🚀

📜 AI-Powered Contract Management Pipeline (Google Drive + VLM Run + Sheets + Calendar + Slack) ⚙️ What This Workflow Does This workflow automatically extracts, organizes, and tracks legal contract details from documents uploaded to Google Drive. Using VLM Run’s Execute Agent, it parses key metadata such as contract ID, parties, dates, and terms — then stores, alerts, and schedules reminders through Google Sheets, Calendar, and Slack. 🧩 Requirements Google Drive OAuth2** for monitoring and downloads VLM Run API credentials** with Execute Agent access Google Sheets OAuth2** for structured record storage Google Calendar OAuth2** for key date reminders Slack API credentials** for team notifications A reachable Webhook URL (for receiving parsed contract data) ⚡Quick Setup Configure Google Drive OAuth2 and create upload folder and folder for saving extracted images. Install the verified VLM Run node by searching for VLM Run in the node list, then click Install. Once installed, you can start using it in your workflows. Add VLM Run API credentials for document parsing. Configure Google Sheet and Calendar. For Google Sheet, from the document list, pick your Google Sheet (e.g., test). Then select the sheet inside it (e.g., Sheet1). Set the operation to Append Row — this will add new contract details as new rows. Turn on Map Each Column Manually. Match each contract field (like Contract ID, Title, Parties, Effective Date, Termination Date) to its corresponding column in your Google Sheet. Configure Slack for notifications. ⚙️ How It Works Monitor Contract Uploads – Watches a target Google Drive folder for new file uploads (PDFs, images, or scans). Download Contract File – Automatically downloads new contracts for AI analysis. VLM Run ContractParser – Sends the file to the VLM Run Execute Agent, which extracts structured contract data, including: Contract ID Title Parties (with roles) Property address Effective date Termination date Rent, deposit, payment terms, and governing law Receive Contract Data – The webhook endpoint receives the structured JSON response. Format Contract Data – Normalizes fields, formats dates, and prepares for storage. Save to Expense Database (Google Sheets) – Appends extracted data to a master Google Sheet for centralized contract tracking. Notify via Slack – Posts a concise summary to a Slack channel, showing key contract details for visibility. Create Calendar Events – Automatically schedules Google Calendar events for: Effective Date Termination Date Renewal Reminder (60 days before termination) 💡 Why Use This Workflow Manual contract management is error-prone and time-consuming key details like renewal dates, payment terms, or termination clauses often get lost in email threads or folders. This workflow ensures: Zero missed deadlines** automatic Google Calendar reminders keep your team on track. Instant team visibility** - Slack notifications keep legal, finance, and operations aligned. End-to-end automation** no need for manual parsing, data entry, or follow-ups. 🧠 Perfect For Legal teams automating contract intake and tracking Real estate or lease management workflows Finance or procurement teams needing expiration alerts Organizations centralizing contract metadata in Sheets 🛠️ How to Customize Modify Extraction Fields Edit the VLM Run Execute Agent schema to add fields like contract value, payment schedule, department, or contact email. Change Storage Swap Google Sheets for Airtable, Notion, or BigQuery if you manage large datasets or need relational tracking. Customize Notifications Send Slack alerts only for high-value or expiring contracts, and tag relevant teams (e.g., @legal, @finance). Add Calendar Events Auto-create events for reviews or payment milestones using extra date fields. Add Approvals or Signatures Insert a Google Form or Slack approval step, or trigger DocuSign for e-signature automation. ⚠️ Community Node Disclaimer This workflow uses community nodes (VLM Run) that may need additional permissions and custom setup.

Automate Report Generation with n8n & Qualys Introducing the Save Qualys Reports to TheHive Workflow—a robust solution designed to automate the retrieval and storage of Qualys reports in TheHive. This workflow fetches reports from Qualys, filters out already processed reports, and creates cases in TheHive for the new reports. It runs every hour to ensure continuous monitoring and up-to-date vulnerability management, making it ideal for Security Operations Centers (SOCs). How It Works: Set Global Variables:** Initializes necessary global variables like base_url and newtimestamp. This step ensures that the workflow operates with the correct configuration and up-to-date timestamps. Ensure to change the Global Variables to match your environment. Fetch Reports from Qualys:** Sends a GET request to the Qualys API to retrieve finished reports. Automating this step ensures timely updates and consistent data retrieval. Convert XML to JSON:** Converts the XML response to JSON format for easier data manipulation. This transformation simplifies further processing and integration into TheHive. Filter Reports:** Checks if the reports have already been processed using their creation timestamps. This filtering ensures that only new reports are handled, avoiding duplicates. Process Each Report:** Loops through the list of new reports, ensuring each is processed individually. This step-by-step handling prevents issues related to bulk processing and improves reliability. Create Case in TheHive:** Generates a new case in TheHive for each report, serving as a container for the report data. Automating case creation improves efficiency and ensures that all relevant data is captured. Download and Attach Report:** Downloads the report from Qualys and attaches it to the respective case in TheHive. This automation ensures that all data is properly archived and easily accessible for review. Get Started: Ensure your Qualys and TheHive integrations are properly set up. Customize the workflow to fit your specific vulnerability management needs. Need Help? Join the discussion on our Forum or check out resources on Discord! Deploy this workflow to streamline your vulnerability management process, improve response times, and enhance the efficiency of your security operations.

Task: Control your data flow with rate limits and external cues Main use cases: Control the rate of items flow into one or more services in your workflow Wait for external events to occur before continuing with the rest of the workflow

This workflow uses a Hubspot Trigger to check for new contacts. It then validates the contacts' email using OneSimpleAPI. If there are any a message will be sent to Slack. To configure this workflow you will need to set the credentials for the Hubspot, OneSimpleAPI and Slack Nodes. You will also need to select the Slack channel to use for sending the message.

This workflow handles the incoming issues and issues comments for your open-source project. If a contributor is interested, the workflow will assign them the issue. Note: For organizations, you will have to use the Webhook node to trigger the workflow. You will also have to use the HTTP Request node instead of the regular GitHub node. You can learn more about this workflow by reading the blog on https://n8n.io/blog.

📊 Description Automatically track SDK releases from GitHub, compare documentation freshness in Notion, and send Slack alerts when docs lag behind. This workflow ensures documentation stays in sync with releases, improves visibility, and reduces version drift across teams. 🚀📚💬 What This Template Does Step 1: Listens to GitHub repository events to detect new SDK releases. 🧩 Step 2: Fetches release metadata including version, tag, and publish date. 📦 Step 3: Logs release data into Google Sheets for record-keeping and analysis. 📊 Step 4: Retrieves FAQ or documentation data from Notion. 📚 Step 5: Merges GitHub and Notion data to calculate documentation drift. 🔍 Step 6: Flags SDKs whose documentation is over 30 days out of date. ⚠️ Step 7: Sends detailed Slack alerts to notify responsible teams. 🔔 Key Benefits ✅ Keeps SDK documentation aligned with product releases ✅ Prevents outdated information from reaching users ✅ Provides centralized release tracking in Google Sheets ✅ Sends real-time Slack alerts for overdue updates ✅ Strengthens DevRel and developer experience operations Features GitHub release trigger for real-time monitoring Google Sheets logging for tracking and auditing Notion database integration for documentation comparison Automated drift calculation (days since last update) Slack notifications for overdue documentation Requirements GitHub OAuth2 credentials Notion API credentials Google Sheets OAuth2 credentials Slack Bot token with chat:write permissions Target Audience Developer Relations (DevRel) and SDK engineering teams Product documentation and technical writing teams Project managers tracking SDK and doc release parity Step-by-Step Setup Instructions Connect your GitHub account and select your SDK repository. Replace YOUR_GOOGLE_SHEET_ID and YOUR_SHEET_GID with your tracking spreadsheet. Add your Notion FAQ database ID. Configure your Slack channel ID for alerts. Run once manually to validate setup, then enable automation.

This template integrates OpenAI's image generation and editing endpoints via the GPT-Image-1 model to visually create and manipulate images based on prompts. It features base64 conversion, binary handling, and prompt chaining. Perfect for marketing, design, product visuals and creative workflows. 🛠️ Requirements OpenAI account with access to gpt-image-1(probably you need organizations verifications for access to that model) OpenAI API credentials configured in n8n A self-hosted or cloud n8n instance Basic familiarity with the n8n UI (no programming required) 🔧 Step-by-step Instructions Step 1: Manual Trigger Starts the workflow on click. Ideal for testing the generation and edit logic. Step 2: Generate Image The Create image call node sends a prompt to OpenAI and returns a base64 image. Example prompt: A cyberpunk city at night with flying cars and neon lights Step 3: Convert to Binary The base64 image is converted into a usable binary PNG file with the Convert json binary to File node. Step 4: Edit the Image The binary file is passed to OpenAI’s /images/edits endpoint. A new prompt applies changes to the image. Example: Add a glowing robot in the foreground with a neon sword ✅ Supports model: gpt-image-1 ⚠️ Requires binary file (not base64) Step 5: Final Conversion Converts the final edited image from base64 to file so it can be downloaded or used in other nodes. 🎯 Real-World Use Cases 🎨 Artists & Creators: concept art and illustration variations 🛍️ E-commerce: auto-generate product mockups 📰 Marketing: create eye-catching blog or social visuals 💡 Bonus Ideas Add a Telegram or Slack node to generate or edit images via chat Use a Webhook to feed prompts from a form or frontend Add a mask to restrict edits to specific areas (e.g., background only)