Workflow Templates

🔍 What This Workflow Does This RAG Pipeline in n8n automates document ingestion from Google Drive, vectorizes it using OpenAI embeddings, stores it in Pinecone, and enables chat-based retrieval using LangChain agents. Main Functions: 📂 Auto-detects new files uploaded to a specific Google Drive folder. 🧠 Converts the file into embeddings using OpenAI. 📦 Stores them in a Pinecone vector database. 💬 Allows a user to query the knowledge base through a chat interface. 🤖 Uses a GPT-4o-mini model with LangChain to generate intelligent responses using retrieved context. ⚙️ Setup Instructions Connect Accounts Ensure these services are connected in n8n: ✅ Google Drive (OAuth2) ✅ OpenAI ✅ Pinecone You can do this in n8n > Credentials > New and use the matching names from the file: Google Drive: "Google Drive account 2" OpenAI: "OpenAi success" Pinecone: "PineconeApi account 2" Folder Setup Upload your documents to this folder in Google Drive: 📁 Power Folder The workflow is triggered every minute when a new file is uploaded. Workflow Overview A. File Ingestion Path Google Drive Trigger — detects new file. Google Drive (Download) — downloads the new file. Recursive Text Splitter — splits text into chunks. Default Data Loader — loads content as LangChain documents. OpenAI Embeddings — converts text chunks into embeddings. Pinecone Vector Store — stores them in "ragfile" index. B. Chat Retrieval Path When chat message received — AI Agent — LangChain agent managing tools. OpenAI Chat Model (GPT-4o-mini) — generates replies. Pinecone Vector Store (retrieval) — retrieves matching content. Embeddings OpenAI1 — helps match queries to document chunks.

Using the knowledge graphs instead of RAG vector stores This workflow creates a Telegram chatbot agent that has access to several knowledge bases at the same time (used as "experts"). These knowledge bases are provided using the InfraNodus GraphRAG using the knowledge graphs and providing high-quality responses without the need to set up complex RAG vector store workflows. The advantages of using GraphRAG instead of the standard vector stores for knowledge are: Easy and quick to set up and update (no complex data import workflows or vector stores needed) A knowledge graph has a holistic view of your knowledge base and knows what it's about Better retrieval of relations between the document chunks = higher quality responses How it works This template uses the n8n AI agent node as an orchestrating agent that decides which tool (knowledge graph) to use based on the user's prompt. Here's a description step by step: The user submits a question using the Telegram bot, which is then received in the n8n workflow via the Telegram trigger node. The AI agent node checks a list of tools it has access to. Each tool has a description of the knowledge it has auto-generated by InfraNodus. The AI agent decides which tool should be used to generate a response. It may reformulate user's query to be more suitable for the expert. The query is then sent to the InfraNodus HTTP node endpoint, which will query the graph that corresponds to that expert. Each InfraNodus GraphRAG expert provides a rich response that takes the whole context into account and provides a response from each expert (graph) along with a list of relevant statements retrieved using a combination or RAG and GraphRAG. The n8n AI Agent node integrates the responses received from the experts to produce the final answer. The final answer is sent back to the Telegram bot who delivers it back to the private chat or a Telegram group. How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Create a separate knowledge graph for each expert (using PDF / content import options) in InfraNodus For each graph, go to the workflow, paste the name of the graph into the body name field. Keep other settings intact or learn more about them at the InfraNodus access points page. Once you add one or more graphs as experts to your flow, add the LLM key to the OpenAI node Create a Telegram bot (the instructions are in the workflow Post note) — it takes 30 seconds. Get its API key and create the Telegram credentials to use in the Telegram nodes in this workflow. Requirements An InfraNodus account and API key An OpenAI (or any other LLM) API key A Telegram account Customizing this workflow You can use this same workflow with a standard AI chatbot via a URL that can also be embedded to any website. You can also use it with ElevenLabs AI voice agent. There are many more customizations available. Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20174217658396-Using-InfraNodus-Knowledge-Graphs-as-Experts-for-AI-Chatbot-Agents-in-n8n Also check out the video tutorial with a demo: Support If you have any questions, contact us via the support portal at https://support.noduslabs.com or via our Discord channel. More n8n workflows are available on our support portal: n8n x InfraNodus AI automation workflows.

This workflow automates the process of removing backgrounds from WooCommerce product images using the BackgroundCut API, and then updates the product images in both WooCommerce and a Google Sheet. Once set up, the workflow processes product images in bulk, removing backgrounds and updating WooCommerce seamlessly. This workflow is perfect for online stores that sell: Clothing and fashion items Jewelry and accessories General consumer products Any product that benefits from clean, background-free images for a professional storefront presentation will see improved visual appeal and potentially higher conversions. Benefits ⏱ Time-saving:** Automates what would otherwise be a manual and repetitive task of editing images and updating product listings. 🔄 Fully Integrated:** Connects Google Sheets, BackgroundCut API, FTP server, and WooCommerce in a seamless loop. 📦 Scalable:** Supports batch processing, making it suitable for stores with hundreds of products. 📁 Organized Tracking:** Updates the Google Sheet with the new image and a “DONE” flag for easy monitoring. 🔧 Customizable:** You can change the image processing API, storage server, or eCommerce platform if needed. How It Works Data Retrieval: The workflow starts by fetching product data (ID and IMAGE URL) from a Google Sheets document. Only rows without a "DONE" marker are processed to avoid duplicates. Background Removal: Each product image URL is sent to the BackgroundCut API, which removes the background and returns the edited image. File Handling: The processed image is uploaded to an FTP server with the original filename preserved. A new URL for the edited image is generated and assigned to the product. WooCommerce Update: The product in WooCommerce is updated with the new image URL. Sheet Update: The Google Sheet is marked as "DONE" for the processed row, and the new image URL is recorded. Batch Processing: The workflow loops through all rows in the sheet until all products are processed. Set Up Steps Prepare the Google Sheet: Clone the provided Google Sheet template. Fill in the ID (product ID) and IMAGE (original image URL) columns. API & Credentials Setup: Get an API key from BackgroundCut.co. Configure the HTTP Request node ("Remove from Image URL") with: Header Auth: Authorization = API_KEY. Set up WooCommerce API credentials in the "Update product" node. FTP Configuration: Replace YOUR_FTP_URL in the "New Image Url" node with your FTP/CDN base URL. Ensure FTP credentials are correctly set in the FTP node. Execution: Run the workflow manually via "When clicking ‘Execute workflow’". The process automatically handles background removal, file upload, and WooCommerce updates. Need help customizing? Contact me for consulting and support or add me on Linkedin.

🎬 Google Veo 3 Prompt and Video Generator via Leonardo.ai + Claude 4 Transform text descriptions into cinematic videos using Google's Veo 3 model through Leonardo.ai's platform! 🚀 What This Workflow Does This advanced automation pipeline takes your creative ideas and turns them into professional-quality videos using Google's powerful Veo 3 model (accessed via Leonardo.ai), enhanced by Claude 4's sophisticated prompt engineering. ✨ Key Features 🤖 AI-Powered Prompt Enhancement**: Uses Claude 4 Sonnet with Wikipedia integration to craft optimal Google Veo 3 prompts 🎥 Professional Video Generation**: Leverages Google's Veo 3 model through Leonardo.ai for high-quality text-to-video conversion ☁️ Automatic Cloud Storage**: Videos are automatically saved to your Google Drive 📋 Structured Prompting**: Follows Google Veo3 best practices with 8 essential elements (Subject, Context, Action, Style, Camera Motion, Composition, Ambiance, Audio) ⚡ Hands-Off Processing**: Set it and forget it - the workflow handles the entire pipeline 🔧 How It Works Input Your Concept - Describe your video idea in the "Video Context" node AI Enhancement - Claude 4 transforms your description into a cinematic Google Veo 3 prompt using advanced techniques Video Generation - Google's Veo 3 model (via Leonardo.ai) creates your video (720p resolution, ~8 seconds) Smart Waiting - 4-minute processing buffer ensures completion Auto-Download - Retrieves the finished video from Leonardo's servers Cloud Storage - Uploads directly to your Google Drive folder 💡 Perfect For Content Creators** looking to automate video production Marketing Teams** needing quick promotional videos Educators** creating engaging visual content Social Media Managers** generating scroll-stopping content Creative Professionals** exploring AI-assisted filmmaking 📋 Requirements Leonardo AI account with API access Anthropic API key (Claude 4 Sonnet) Google Drive integration N8N instance (cloud or self-hosted) 👨‍💻 About the Creator Created by: AlexK1919 - AI-Native Workflow Automation Architect, n8n Ambassador and Verified Partner, Co-Founder @ WotAI If you'd like to review more Google Veo 3 Prompts organized by business category, check out over 9,000+ free, pre-made prompts at: Google Veo 3 Prompts 📄 License This workflow is available under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. You are free to use, adapt, and share this workflow for non-commercial purposes under the terms of this license. Full license details: https://creativecommons.org/licenses/by-nc-sa/4.0/ 🎯 Example Output Input: "Star Wars stormtrooper digging for uranium in desert, saying something funny" The AI generates a structured prompt with: Subject**: Detailed character description Context**: Desert environment specifics Action**: Dynamic digging movements Style**: Cinematic vlog aesthetic Camera**: Appropriate angles and movement Audio**: Dialogue, sound effects, and music ⚙️ Setup Notes Character Limit**: Prompts are optimized for Leonardo's 1,500 character API limit Processing Time**: Allow 4+ minutes for Google Veo3 video generation Quality**: 720p resolution with native audio generation Consistency**: Uses advanced Google Veo3 prompting for reliable results 🔄 Customization Options Modify the prompt engineering system message for different styles Adjust video resolution and model parameters Change storage destination (Google Drive folder) Add post-processing steps or notifications 📈 Why This Workflow Rocks Unlike simple text-to-video tools, this workflow: Intelligently enhances** your prompts using AI for Google Veo 3 Follows industry best practices** for Google Veo3 prompting Automates the entire pipeline** from idea to stored video Leverages multiple AI models** for superior results Handles technical details** like API limits and timing 🚨 Pro Tips Be specific in your initial context - detail creates better videos The workflow includes comprehensive Google Veo3 prompting guidelines Videos are typically 5-8 seconds - plan accordingly for longer content Experiment with different styles and camera movements optimized for Veo 3 The AI can access Wikipedia for factual enhancement Ready to revolutionize your video creation process? Import this workflow and start generating professional videos with just a text description! Perfect for anyone looking to harness the power of AI for content creation. Tags: #veo3 #GoogleVeo3 #AI #VideoGeneration #Leonardo #Claude #Automation #ContentCreation #GoogleAI

README Automating Video File Download from Sample.cat with Airtop.ai Use Case Automating file downloads from web pages is useful for scenarios like bulk media retrieval, dataset access, or recurring content backups. This workflow ensures a hands-free, consistent process for retrieving downloadable content. What This Automation Does This automation performs a reliable download of a video file from a specified webpage using the following steps: Initiates an Airtop browser session. Opens a specified URL containing downloadable media. Interacts with the page to click the download button. Waits for the file to be processed and made available. Retrieves metadata to confirm availability. Downloads the file. Terminates the browser session to clean up resources. How It Works Manual Trigger: Activated by user test. Session: Starts an Airtop browser session. Window: Navigates to https://sample.cat/en/webm. Interaction: Simulates a click on the download button for the video titled “SD 640x360 (Seawater, drone view video, 30 FPS)”. Wait: Pauses for 10 seconds to allow the file to be ready for download. Get File Data: Checks for downloadable files in the session. Download File: Retrieves the file using its ID. Terminate: Ends the browser session to free up resources. Setup Requirements Airtop API Key — required to authenticate API calls. Next Steps Enhance with Retry Logic**: Loop file availability check until status = available for more robust automation. Customize File Targets**: Dynamically pass URLs and button descriptors for multi-source downloads. Connect to Storage**: Pipe downloaded files to cloud storage or databases for archiving. Read more about automating file downloads from the web

This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. This workflow demonstrates how to build and expose a sophisticated n8n AI Agent as a single, callable tool using the Multi-Agent Collaboration Protocol (MCP). It allows external clients or other AI systems to easily query software library documentation via Context7, without needing to manage the underlying tool orchestration or complex conversational logic. Core Idea: Instead of building complex agentic loops on the client-side (e.g., in Python, a VS Code extension, or another AI development environment), this workflow offloads the entire agent's reasoning and tool-use process to n8n. The client simply sends a natural language query (like "How do I use Flexbox in Tailwind CSS?") to an SSE endpoint, and the n8n agent handles the rest. Key Features & How It Works: Public MCP Endpoint: The main workflow uses the Context7 MCP Server Trigger node to create an SSE endpoint. This makes the agent accessible to any MCP-compatible client. The path for the endpoint is kept long and random for basic 'security by obscurity'. Tool Workflow as an Interface: A Tool Workflow node (named call_context7_ai_agent in this example) is connected to the MCP Server Trigger. This node defines the single "tool" that external clients will see and call. Dedicated AI Agent Sub-Workflow: The call_context7_ai_agent tool invokes a separate sub-workflow which contains the actual AI logic. This sub-workflow starts with a Context7 Workflow Start node to receive the user's query. A Context7 AI Agent node (using Google Gemini in this example) is the brain, equipped with: A system prompt to guide its behavior. Simple Memory to retain context for each execution (using {{ $execution.id }} as the session key). Two specialized Context7 MCP client tools: context7-resolve-library-id: To convert library names (e.g., 'Next.js') into Context7-specific IDs. context7-get-library-docs: To fetch documentation using the resolved ID, with options for specific topics and token limits. Seamless Tool Use: The AI Agent autonomously decides when and how to use the resolve-library-id and get-library-docs tools based on the user's query, handling the multi-step process internally. Benefits of This Approach: Simplified Client Integration:** Clients interact with a single, powerful tool, sending a simple query. Reduced Client-Side Token Consumption:** The detailed prompts, tool descriptions, and conversational turns are managed server-side by n8n, saving tokens on the client (especially useful if the client is another LLM). Centralized Agent Management:** Update your agent's capabilities, tools, or LLM model within n8n without any changes needed on the client side. Modularity for Agentic Systems:** Perfect for building complex, multi-agent systems where this n8n workflow can act as a specialized "expert" agent callable by others (e.g., from environments like Smithery). Cost-Effective:** By using a potentially less expensive model (like Gemini Flash) for the agent's orchestration and leveraging the free tier or efficient pricing of services like Context7, you can build powerful solutions economically. Use Cases: Providing an intelligent documentation lookup service for coding assistants or IDE extensions. Creating specialized AI "micro-agents" that can be consumed by larger AI applications. Building internal knowledge base query systems accessible via a simple API-like interface. Setup: Ensure you have the necessary n8n credentials for Google Gemini (or your chosen LLM) and the Context7 MCP client tools. The Path in the Context7 MCP Server Trigger node should be unique and secure. Clients connect to the "Production URL" (SSE endpoint) provided by the trigger node. This workflow is a great example of how n8n can serve as a powerful backend for building and deploying modular AI agents. I've made a video to try and explain this a bit too https://www.youtube.com/watch?v=dudvmyp7Pyg

Advanced n8n Error Handling: Automated Email Alerts & Global Error Workflow Configuration In any automated environment, n8n workflows, while powerful, can sometimes encounter unexpected issues or fail during execution. Without a dedicated error handling strategy, these failures might go unnoticed, leading to incomplete processes, data inconsistencies, or critical operational disruptions. Manually monitoring every workflow execution or sifting through logs for error details is inefficient and can significantly delay crucial fixes. This is where a centralized, automated error management system becomes essential to maintain reliability and quickly address any problems. The "Advanced n8n Error Handling: Automated Email Alerts & Global Error Workflow Configuration" template provides a robust solution to proactively manage and respond to errors within your n8n instance. For more powerful n8n templates, visit our website or contact us at AI Automation Pro. We help your business build custom AI workflow automation and apps. Highlight features Automated Email Notifications:** Sends detailed HTML emails via Gmail for both execution and trigger failures, ensuring you're promptly informed. Centralized Error Management:** Acts as a single, dedicated workflow to catch and process errors from multiple other n8n workflows. Proactive Global Error Handler Configuration:** A scheduled task automatically scans and updates other active n8n workflows to use this workflow as their default error handler, ensuring consistent error management. Comprehensive Error Reporting:** Notification emails are rich with information, including error messages, stack traces, the last executed node, direct links to failed executions, and detailed trigger failure context. Dynamic Email Content:** The subject line and body of the notification email are dynamically adjusted based on whether the failure was an execution error or a trigger failure. Highly Customizable:** Offers flexibility to modify email content (HTML), change the notification channel (e.g., Slack, other email providers), and adjust the logic for updating other workflows' error handlers. Scheduled Operation:** The global configuration part runs on a user-definable schedule (e.g., daily, hourly) for proactive and automated error handling setup across your n8n instance. Who is this for? This workflow is designed for n8n users and administrators who want to: Establish a resilient and centralized error handling mechanism across their n8n instance. Receive immediate and detailed email notifications for any workflow failures. Automate the process of assigning a default error handling workflow to all their active n8n workflows. Save time on manually configuring error handlers for each individual workflow and ensure comprehensive error coverage. What problem is this workflow solving? / use case In an n8n environment with multiple workflows, errors can occur without immediate visibility. This can lead to: Unnoticed failures, potentially causing data loss or incomplete automated processes. Time-consuming diagnosis of issues due to a lack of readily available, detailed error information. Inefficiency and oversight from manually setting an error workflow for every new or existing workflow. This template tackles these issues by providing a proactive error management system. It not only alerts you to failures with comprehensive details but also ensures that your other workflows are automatically configured to use this centralized handler. What this workflow does This workflow operates in two distinct yet complementary parts: 1\. Scheduled Global Error Handler Configuration: Trigger:** Initiates based on a configurable schedule (e.g., daily, hourly). Identify Self:** Retrieves its own workflow ID to use as the designated error handler. Scan Workflows:** Fetches a list of all other workflows within your n8n instance. Conditional Update Logic:** For each active workflow found, it checks if: An error workflow (errorWorkflow setting) is not currently set, OR The currently set errorWorkflow is different from this central error handling workflow. The workflow is active. Apply Default Handler:** If the above conditions are met, it automatically updates the target workflow's settings. This sets the current workflow as its default error handler, ensuring that any future errors in those workflows are routed here. The callerPolicy setting is also removed during this update. 2\. Error Notification via Email: Trigger:** Activates whenever an error occurs in any n8n workflow that has this workflow designated as its errorWorkflow. Gather Error Context:** Collects vital information about the failure, such as: The base URL of your n8n instance. Specific details of the workflow that failed (name, ID). The nature of the error: whether it's an "execution error" (occurring mid-workflow) or a "trigger failure" (occurring at the start). Format Detailed Error Message:** Constructs a comprehensive HTML email tailored to the error type: For Execution Errors: The email includes a direct link to the failed execution's page, the timestamp of the error, the name of the last node that successfully executed, the error message, and the full error stack trace. For Trigger Failures: The email includes the timestamp, operational mode, error message, error name and description, relevant context data, details about the cause (message, name, code, status), and the stack trace. Send Email Notification:** Dispatches the formatted HTML email using Gmail to a predefined recipient. The email subject line dynamically indicates the name of the failing workflow and the type of error, providing a quick overview. Setup Import Workflow: Import the JSON file into your n8n instance. Configure Credentials: n8n API Access: Locate the nodes: "N8n Get Error Handler", "N8n Get All Workflows", and "N8n Update Workflow". For each, select or create new n8n API credentials. These credentials must have permissions to read all workflows (workflows.read) and update workflows (workflows.update). Gmail Access: Locate the "Gmail Send Notification" node. Select or create new Gmail OAuth2 credentials to authorize n8n to send emails on your behalf. Set Email Recipient and Sender Details: Navigate to the "Settings" node, which is connected directly after the "Error Trigger" node. Modify the value for the Email Receiver variable to the email address where error notifications should be sent. Optionally, update the Email Sender Name variable. Configure Schedule (Optional): Select the "Schedule Trigger" node. Adjust the "Trigger Interval" (e.g., Every Day, Every Hour) according to how frequently you want the workflow to scan and update the error handler settings for other workflows in your n8n instance. Activate Workflow: Ensure this workflow is toggled to "Active". Once active, its scheduled component will begin operating, and it will be ready to process and notify on errors from other linked workflows. Manual Configuration (Optional): While this workflow automates the assignment, you can also manually set this workflow as the errorWorkflow in the settings of any critical existing workflows for immediate protection. How to customize this workflow to your needs Email Content & Formatting:** Modify the HTML content within the "HTML For Execution Error" and "HTML For Trigger Error" nodes to alter the appearance, structure, or information included in the notification emails. Alternative Notification Channels:** Replace the "Gmail Send Notification" node with a different email service node (e.g., Microsoft Outlook, SendGrid) or integrate other notification platforms like Slack, Microsoft Teams, or Discord. Remember to adjust the input data mappings for the new node. Refine Global Update Logic:** Adjust the conditions within the "If No Default Error Handler Set" node if you need more granular control over which workflows are automatically updated (e.g., filter by workflow tags, names, or explicitly exclude certain workflows). Enrich Error Data:** Insert additional nodes after the "Error Trigger" but before the "Settings" node if you need to fetch more context about the error or the workflow that failed (e.g., look up related information from a database or API). Advanced Notification Routing:** Implement more complex logic prior to sending notifications. For example, you could use a Switch node to route error alerts to different email addresses or channels based on the name of the failing workflow or the severity of the error. Handling of callerPolicy:** The "Set Data" node is configured to remove the callerPolicy setting from workflows it updates. If your workflows rely on this setting, you may need to modify or remove this part of the "Set Data" node's code. Adjust Scheduled Task:** Change the frequency or timing of the "Schedule Trigger" to better suit your operational needs for the global error handler update.

This n8n workflow automates the discovery, enrichment, and comparative analysis of startups from the Crunchbase dataset via Bright Data, enhanced with AI, and exports structured results to Google Sheets. 🚀 What It Does Receives a keyword from the user that describes the area of interest — such as an industry, sector, technology, or trend (e.g., "AI in healthcare", "carbon capture", "edtech"). This keyword is used to filter relevant startups from the Crunchbase dataset via Bright Data. Fetches data from Bright Data's Crunchbase snapshot API. Extracts and cleans key fields from the JSON response. Sorts startups by most recent founding date. Selects the top 10 most recent companies. Sends these 10 companies to Google Gemini AI for comparative analysis. Embeds the AI-generated summary into the final export. Appends results to a Google Sheet for tracking and reporting. 🛠️ Step-by-Step Setup Get user keyword input from a form. Use 3 Bright Data requests: Start snapshot. Poll snapshot status until ready. Fetch snapshot data in JSON format. Use a Python Code node to: Parse and sort companies by founded_date. Clean and standardize data fields. Pass the top 10 companies into Gemini AI for comparative insight. Merge the AI output back with company data. Send everything to Google Sheets. 🧠 How It Works Snapshot Control: Polls every few seconds until the Bright Data snapshot is complete. Code Cleanup: Ensures consistent structure and formatting across all records. Comparative AI Analysis: Gemini compares all 10 companies at once and returns a unified analysis. Merging Output: AI analysis is merged into the first company’s record (to avoid duplication), while all 10 are exported. 📤 Google Sheet Output Each row includes: name, founded, about, num_employees, type, ipo_status, full_description, social_media_links, address, website, funding_total, num_investors, lead_investors, founders, products_and_services, monthly_visits, crunchbase_link, ai_analysis. AI comparative analysis summary (only once per batch – attached to the first company). All fields from above customizible through the python code (you can add additional ones from Bright Data output). 🔐 Required Credentials Bright Data* – Replace *YOUR_API_KEY** in 3 HTTP Request nodes. Google Gemini API** – For AI analysis. Google Sheets OAuth2** – For spreadsheet export. ⚠️ Notes AI output is shared once per batch of 10 companies, attached to the first company entry. You can configure the limit of batch size in the first "Code" node.

This n8n template allows you to perform real-time currency conversions by simply sending a webhook request. By integrating with the ExchangeRate.host API, you can get up-to-date exchange rates for over 170 world currencies, making it an incredibly useful tool for financial tracking, e-commerce, international business, and personal budgeting. 🔧 How it works Receive Conversion Request Webhook: This node acts as the entry point for the workflow, listening for incoming POST requests. It's configured to expect a JSON body containing: from: The 3-letter ISO 4217 currency code for the source currency (e.g., USD, PHP). to: The 3-letter ISO 4217 currency code for the target currency (e.g., EUR, JPY). amount: The numeric value you want to convert. Important: The ExchangeRate.host API access_key is handled securely by n8n's credential system and should not be included in the webhook body or headers. Convert Currency: This node makes an HTTP GET request to the ExchangeRate.host API (api.exchangerate.host). It dynamically constructs the URL using the from, to, and amount from the webhook body. Your API access key is securely retrieved from n8n's pre-configured credentials (HTTP Query Auth type) and automatically added as a query parameter (access_key). The API then performs the conversion and returns a JSON object with the conversion details. Respond with Converted Amount: This node sends the full currency conversion result received from ExchangeRate.host back to the service that initiated the webhook. 👤 Who is it for? This workflow is ideal for: E-commerce Platforms: Display prices in local currencies on the fly for international customers. Convert incoming international payments to your local currency for accounting. Calculate shipping costs in different currencies. Financial Tracking & Budgeting Apps: Update personal or business budgets with converted values. Track expenses incurred in foreign currencies. Automate portfolio value conversion for multi-currency investments. International Business & Freelancers: Generate invoices in a client's local currency based on your preferred currency. Quickly estimate project costs or earnings in different currencies. Automate reconciliation of international transactions. Travel Planning: Convert travel expenses from one currency to another while abroad. Build simple tools to estimate costs for trips in different countries. Data Analysis & Reporting: Standardize financial data from various sources into a single currency for unified reporting. Build dashboards that display converted financial metrics. Custom Integrations: Connect to CRMs, accounting software, or internal tools to automate currency-related tasks. Build chatbots that can answer currency conversion queries. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "from": "USD", "to": "PHP", "amount": 100 } The workflow will return a JSON response similar to this (results will vary based on currencies and amount): { "date": "2025-06-03", "historical": false, "info": { "rate": 58.749501, "timestamp": 1717398188 }, "query": { "amount": 100, "from": "USD", "to": "PHP" }, "result": 5874.9501, "success": true } ⚙️ Setup Instructions Get an ExchangeRate.host Access Key: Go to https://exchangerate.host/ and sign up for a free API key. Create an n8n Credential for ExchangeRate.host: In your n8n instance, go to Credentials. Click "New Credential" and search for "HTTP Query Auth". Set the Name (e.g., ExchangeRate.host API Key). Set API Key to your ExchangeRate.host access key. Set Parameter Name to access_key. Set Parameter Position to Query. Save the credential. Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure ExchangeRate.host API Node: Double-click the Convert Currency node. Under "Authentication", select "Generic Credential Type". Choose "HTTP Query Auth" as the Generic Auth Type. Select the credential you created (e.g., "ExchangeRate.host API Key") from the dropdown. Configure Webhook Path: Double-click the Receive Conversion Request Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /convert-currency). Activate Workflow: Save and activate the workflow. 📝 Tips This workflow is a powerful starting point. Here's how you can make it even more robust and integrated: Robust Error Handling: Add an IF node after Convert Currency to check {{ $json.success }}. If false, branch to an Error Trigger node or send an alert (e.g., Slack, Email) with {{ $json.error.info }} to notify you of API issues or invalid inputs. Include a Try/Catch block to gracefully handle network issues or malformed responses. Input Validation & Defaults: Add a Function node after the webhook to validate if from, to, and amount are present and in the correct format. If not, return a clear error message to the user. Set default from or to currencies if they are not provided in the webhook, making the API more flexible. Logging & Auditing: After a successful conversion, use a Google Sheets, Airtable, or database node (e.g., PostgreSQL, MongoDB) to log every conversion request, including the input currencies, amount, converted result, date, and possibly the calling IP (from the webhook headers). This is crucial for financial auditing and analysis. Rate Limits & Caching: If you anticipate many requests, be mindful of ExchangeRate.host's API rate limits. You can introduce a Cache node to store recent conversion results for a short period, reducing redundant API calls for common conversions. Alternatively, add a Delay node to space out requests if you're hitting limits. Format & Rounding: Use a Function node or Set node to format the result to a specific number of decimal places (e.g., {{ $json.result.toFixed(2) }}). Add currency symbols or full currency names to the output for better readability. Alerting on Significant Changes: Chain this workflow with a Cron or Schedule node to periodically fetch exchange rates for a pair you care about (e.g., USD to EUR). Use an IF node to compare the current rate with a previously stored rate. If the change exceeds a certain percentage, send an alert via Slack, Email, or Telegram to notify you of significant market shifts. Integration with Payment Gateways: For e-commerce, combine this with nodes for payment gateways (e.g., Stripe, PayPal) to automatically convert customer payments received in foreign currencies to your base currency before recording. Multi-currency Pricing for Products: Use this workflow in conjunction with your product database. When a user selects a different country/currency, trigger this webhook to dynamically convert product prices and display them instantly.

Automate expense reviews with AI-powered CFO-level analysis. This workflow monitors Airtable expense submissions, uses GPT-4 to analyze expenses like an experienced CFO, flags suspicious expenses with detailed reasoning, and maintains comprehensive audit trails in Pinecone vector database. 🚀 What It Does Smart Monitoring**: Watches Airtable for new expense submissions AI CFO Analysis**: GPT-4 applies financial expertise to review amounts, categories, and descriptions Intelligent Flagging**: Automatically identifies policy violations and suspicious patterns Audit Trail**: Stores all decisions in Pinecone for compliance and searchability Auto Updates**: Updates Airtable records with AI decisions and detailed reasoning 🎯 Perfect For Finance teams needing intelligent expense oversight CFOs wanting to automate expense policy enforcement Growing companies scaling expense management Businesses requiring compliance documentation ⚙️ Key Benefits ✅ 99% faster expense processing vs manual review ✅ CFO-level intelligence applied to every expense ✅ Complete audit trail for compliance ✅ Real-time fraud detection and policy enforcement ✅ Detailed explanations for every decision 🔧 What You Need Airtable base with expense data (template included) OpenAI API for GPT-4 analysis Pinecone account for audit trail storage Basic expense submission process 📊 Sample Results Input: $4,500 business class flight to Tokyo AI Decision: "Flagged - Amount exceeds typical travel thresholds. Requires verification against travel policies and client justification for premium travel." 🛠️ Setup & Support Quick Setup: Deploy in 60 minutes with included templates and documentation YouTube: https://www.youtube.com/@YaronBeen/videos 💼 Expert Support LinkedIn: https://www.linkedin.com/in/yaronbeen/ 📧 Direct Help Email: Yaron@nofluff.online Transform expense management from manual bottleneck to intelligent automation. Let AI handle policy compliance while your finance team focuses on strategy.

Analyze and Explore your ZenDesk Support Requests using AI-Powered Knowledge Graph This template helps you create an interactive InfraNodus knowledge graph for your ZenDesk tickets using any search criteria (e.g. after a certain date, specific status, sender, keyword) that will automatically be sent to a selected Slack channel. Here's an example of the InfraNodus graph that shows the main topics and gaps in ZenDesk support tickets: You can use the workflow to: Get an instant overview of the main topics your customers are talking about Generate business and product ideas based on the blind spots identified using the InfraNodus AI See which topics correlate to the negative / positive sentiment understanding the weak and strong sides of your product and support Receive daily notifications on the main topics your customers are talking about via Slack / Telegram / Email and other channels Perform detailed search using a password-protected web form for tickets filtered by a certain date, status, tag, sender, keyword. Use the interactive graph to explore specific topics and concepts your customers are talking about — a great way to engage with their concerns in a non-linear way, bypassing the boring tabular interface Use the graph to explore the support requests by specific segments — e.g. status, priority, sentiment, tags, urgency. Use the graph generated as an AI expert available to your AI agents in other n8n workflows via InfraNodus GraphRAG. For instance, you could connect your knowledge base to the support tickets graph and let the agent discover possible solutions to your customers' most typical problems. See an sample template here. How it works You can start this workflow manually, with a daily / weekly trigger, or via a password-protected web form, where you can provide search requests. Once started, it will perform a ZenDesk tickets search with the default or your custom criteria. Then it will use the search results to generate an InfraNodus graph (or add the new data to an existing one), and — finally — use the InfraNodus AI endpoints to generate a topical summary and a product business idea based on the blind spots identified. The results are delivered a channel of your choice. Here's a description step by step: Start the workflow (manually or on schedule) Assign values to variables (search criteria, graph name) Perform ZenDesk support tickets search Convert the data received and submit it to InfraNodus to generate a knowledge graph Generate topical summary with InfraNodus Generate a business idea with InfraNodus (you can also change the setting to generate a question instead) Send a notification via Slack / Telegram / Email or back to the webform How to use You need an InfraNodus API account and key to use this workflow. You also need a ZenDesk account. It takes about 5 minutes to set everything up. Create an InfraNodus account. Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Add the authorization key to all the InfraNodus HTTP nodes in the template (Steps 3, 5, and 6). Generate a ZenDesk authorization token following the instructions in n8n's ZenDesk node (Step 3). Optionally: connect your Slack or Telegram or Gmail account to receive automated notifications with the link to the graph, once the workflow is ready (it takes about 30 seconds to run). Run it with using the form to play around with the search criteria that works best for you (you can leave everything empty at first), then choose the parameters you like and activate the Daily Trigger node to receive executive summaries to a channel of your choice. Open the graph in InfraNodus and use our customer feedback analysis guide to explore the graph and generate new insights. Requirements An InfraNodus account and API key A ZenDesk API key (Optional) — a Slack / Telegram / Gmail connection for notifications FAQ 1. What are the best use cases to try? I love to set the graph to deliver me a daily visual briefing of what's happening in my support portal. It shows me the main topics and gaps and generates product ideas based on them. Great to keep the pulse on the business. I also really like generating a graph for the past week manually, using the form, and then exploring the graph in InfraNodus directly using the customer feedback analysis workflow to: discover main topics my customers are talking about? understand the topics that have the most negative connotation for them (using the sentiment filter)? discover some support tickets that need more attention or that talk about the topics I'm personally interested in and engage with the client identify the gaps in your customers' discourse based on the blind spots — useful for generating ideas, see the graph below with a demo of how it works: 2. Why use the graph and not just AI summary? AI summary will just give you generic results. You'll see what you already know. Using the graph helps you deconstruct the discourse and get a much more nuanced understanding of the main pain points and interests of your customers. The auto-generated InfraNodus summary and business ideas have a direct explainable connection to the discourse, so you can always see where they are coming from and maintain the focus on all the topics, rather than the most prominent ones. Additionally, having an interactive graph opens a possibility to explore your customers' concerns in a more engaging way, finding the topics and concepts that are relevant to your interests or to your agents' expertise, helping you find the conversations that you'd otherwise have missed. 3. Is my customers' data safe? Absolutely. InfraNodus' terms of use and privacy policy state that the customers' data and text graphs are not used in AI training and are not offered to any third parties. Its underlying API system uses the Open API which explicitly states that data is not used for training either. So all the customers' data are private and safe. As an extra precaution, you can always delete the graphs after you analyzed them, in which case there is no trace of this data left on the servers. Customizing this workflow Check out the complete setup guide for this workflow at https://support.noduslabs.com/hc/en-us/articles/20447530961308-Zendesk-Tickets-Summarization-Sentiment-Analysis-and-Slack-Integration-with-n8n-and-InfraNodus For support with this template, please, contact https://support.noduslabs.com For more InfraNodus n8n workflows, please, see our creators page: https://n8n.io/creators/infranodus/ To learn more about InfraNodus, GraphRAG, and knowledge graph analysis: https://infranodus.com

Video Introduction Want to automate your inbox or need a custom workflow? 📞 Book a Call | 💬 DM me on Linkedin Transform your messy inbox into a calm, organized command center - in minutes - using this ready-to-use n8n automation! Tired of your Gmail looking like this? With this template, you can have this instead: What does this automation do? AI-powered categorization:** Every new email is analyzed with OpenRouter AI and sorted into categories you define (like Orders, Support, Invoices, Urgent, etc.). Instant color-coded labels:** The workflow creates and applies Gmail labels with custom colors, so you can spot important messages at a glance. Supports Gmail’s Multiple Inboxes:** Display different categories in their own sections—see what matters most right away. Flexible and customizable:** You control the categories and definitions using a simple Google Sheet. How it works – Step by Step See the full setup & demo: Copy the Template Open the n8n workflow template and click Use for free. Log in (or sign up) for n8n Cloud for the quickest start. Customize Your Categories in Google Sheets Use the provided Google Sheets template linked in the workflow notes. Go to File → Make a copy to your own Drive. Edit the categories and their definitions for your business. Example: Add categories like “Existing Order Questions,” define each one to guide the AI, and copy your Google Sheet’s URL into the workflow config node. Connect AI with OpenRouter Go to OpenRouter.ai, log in, and generate a new API key. Paste your API key into the workflow where prompted. Test and Activate the Workflow Connect your Gmail account to n8n. Hit “Test Workflow”—watch as the AI processes your latest emails and applies labels automatically. Labels will appear instantly in Gmail, and any missing ones are created by the automation. Schedule Automatic Runs Switch workflow status to Active in n8n. Set the scheduler trigger—most people use hourly, but you can use crontab.guru for custom times (like only business hours). Tips for Best Results Color Code Your Labels:** In Gmail, you can assign colors to labels—set high-priority categories (like “Customer Complaints”) to a bright color to stand out. Upgrade Your Gmail View:** Enable Multiple Inboxes in Gmail’s settings and set up sections for your key categories. Example search queries: in:inbox label:customer-complaints OR label:urgent-emails in:inbox label:existing-order-questions in:inbox label:support-requests Why Use This? Get rid of inbox chaos for good - no more lost emails or missed deadlines Fully customize the system to your business with just a Google Sheet Works with zero coding - set up in 10-15 minutes Flexible: add auto-replies, draft suggestions, and more as you grow