Workflow Templates

This workflow allows you to receive updates from Wise and add information of a transfer to a base in Airtable. Wise Trigger node: This node will trigger the workflow when the status of your transfer changes. Wise node: This node will get the information about the transfer. Set node: We use the Set node to ensure that only the data that we set in this node gets passed on to the next nodes in the workflow. We set the value of Transfer ID, Date, Reference, and Amount in this node. Airtable node: This node will append the data that we set in the previous node to a table.

Auto Starter On importing workflows these will not be auto started, even if the old version was running. To fix this we created this workflow that can be run after n8n starts. It fits in our auto deploy pipeline and modified n8n container that will import workflows, start n8n and start the tagged workflows. Start this workflow after n8n starts. It will get all workflows in the running n8n instance. If the files have a tag 'Auto start' the workflow will be started. Check our Export workflows with readable names workflow for autostarting workflows after deployment. Configuration You need a a n8n api key configured.

How It Works This workflow sends an HTTP request to OpenAI's Text-to-Speech (TTS) model, returning an .mp3 audio recording of the provided text. This template is meant to be adapted for your individual use case, and requires a valid OpenAI credential. Gotchas Per OpenAI's Usage Policies, you must provide a clear disclosure to end users that the TTS voice they are hearing is AI-generated and not a human voice, if you are using this workflow to provide audio output to users.

This n8n workflow automates the handling of security detections from CrowdStrike, streamlining incident response and notification processes. The workflow is triggered daily at midnight by the Schedule Trigger node. It begins by fetching recent security detections from CrowdStrike using an HTTP Request node. The response is then split into individual detections for further processing. Each detection is enriched by querying the CrowdStrike API for detailed information using another HTTP Request node. The workflow then processes these detections sequentially using the Split In Batches node. Next, it looks up behavioral information associated with each detection in VirusTotal using two HTTP Request nodes. One node queries VirusTotal based on SHA256 values, and the other based on IOC (Indicator of Compromise) values. The workflow includes a 1-second pause using the Wait node to prevent rate limiting when making requests to the VirusTotal API. Subsequently, the workflow sets fields with relevant details from both CrowdStrike and VirusTotal, including detection links, confidence scores, filenames, usernames, and more. These details are concatenated using an Item Lists node for each detection. The final step involves creating Jira issues for each detection, including summaries with CrowdStrike alert severity and hostnames, as well as descriptions that incorporate information from CrowdStrike and VirusTotal. Information about this issue is then sent via a Slack message to a Slack user. Potential issues during setup might include configuring the Schedule Trigger node to trigger at the correct time zone and handling potential rate limiting from the VirusTotal API, which could lead to throttled requests. Additionally, the note about a possible typo in the URL for the Virustotal nodes should be addressed to ensure correct API calls. The Jira node may need to be replaced with the latest version for compatibility. Properly configuring API credentials and handling errors that may occur during API requests are essential for a smooth workflow operation. Careful testing with sample data is recommended to validate the workflow's functionality and ensure it aligns with your organization's security incident response processes.

Workflow based on the following article. https://www.anthropic.com/news/contextual-retrieval This n8n automation is designed to extract, process, and store content from documents into a Pinecone vector store using context-based chunking. The workflow enhances retrieval accuracy in RAG (Retrieval-Augmented Generation) setups by ensuring each chunk retains meaningful context. Workflow Breakdown: 🔹 Google Drive - Retrieve Document: The automation starts by fetching a source document from Google Drive. This document contains structured content, with predefined boundary markers for easy segmentation. 🔹 Extract Text Content - Once retrieved, the document’s text is extracted for processing. Special section boundary markers are used to divide the text into logical sections. 🔹 Code Node - Create Context-Based Chunks: A custom code node processes the extracted text, identifying section boundaries and splitting the document into meaningful chunks. Each chunk is structured to retain its context within the entire document. 🔹 Loop Node - Process Each Chunk: The workflow loops through each chunk, ensuring they are processed individually while maintaining a connection to the overall document context. 🔹 Agent Node - Generate Context for Each Chunk: We use an Agent node powered by OpenAI’s GPT-4.0-mini via OpenRouter to generate contextual metadata for each chunk, ensuring better retrieval accuracy. 🔹 Prepend Context to Chunks & Create Embeddings - The generated context is prepended to the original chunk, creating context-rich embeddings that improve searchability. 🔹 Google Gemini - Text Embeddings: The processed text is passed through Google Gemini text-embedding-004, which converts the text into semantic vector representations. 🔹 Pinecone Vector Store - Store Embeddings: The final embeddings, along with the enriched chunk content and metadata, are stored in Pinecone, making them easily retrievable for RAG-based AI applications. Use Case: This automation enhances RAG retrieval by ensuring each chunk is contextually aware of the entire document, leading to more accurate AI responses. It’s perfect for applications that require semantic search, AI-powered knowledge management, or intelligent document retrieval. By implementing context-based chunking, this workflow ensures that LLMs retrieve the most relevant data, improving response quality and accuracy in AI-driven applications.

CFO Forecasting Agent - Marketplace Listing Headlines (Choose Your Favorite) Option 1 - Direct & Professional "AI-Powered CFO Forecasting Agent: Automated Revenue Predictions from Stripe Data" Option 2 - Benefit-Focused "Automate Your Financial Forecasting: Daily Revenue Predictions with AI Intelligence" Option 3 - Action-Oriented "Transform Stripe Sales Data into Intelligent 3-Month Revenue Forecasts Automatically" Marketplace Description 🚀 AI-Powered Financial Forecasting on Autopilot Turn your Stripe sales data into intelligent revenue forecasts with this comprehensive CFO Forecasting Agent. This workflow automatically analyzes your transaction history, identifies trends, and generates professional 3-month revenue predictions using OpenAI's GPT-4. ✨ What This Workflow Does: 📊 Automated Data Collection**: Fetches and processes all Stripe charges daily 🤖 AI-Powered Analysis**: Uses OpenAI GPT-4 to analyze trends and predict future revenue 📈 Structured Forecasting**: Generates monthly forecasts with confidence levels and insights 💾 Multi-Platform Storage**: Saves results to both Supabase database and Google Sheets 🕒 Scheduled Execution**: Runs automatically every day to keep forecasts current 🧠 Smart Context**: Optional Pinecone integration for historical context and improved accuracy 🔧 Key Features: Daily automated execution** at 9 AM Structured JSON output** with forecasts, trends, and confidence levels Dual storage system** for data backup and easy reporting RAG-enabled** for enhanced forecasting with historical context Professional CFO-grade insights** and trend analysis 📋 Prerequisites: Stripe account with API access OpenAI API key (GPT-4 recommended) Google Sheets API credentials Supabase account (optional) Pinecone account (optional, for enhanced context) 🎯 Perfect For: SaaS companies tracking subscription revenue E-commerce businesses needing sales forecasts Startups requiring investor-ready financial projections Finance teams automating reporting workflows 📦 What You Get: Complete n8n workflow with all nodes configured Detailed documentation and setup instructions Sample data structure and output formats Ready-to-use Google Sheets template 💡 Need Help or Want to Learn More? Created by Yaron Been - Automation & AI Specialist 📧 Support: Yaron@nofluff.online 🎥 YouTube Tutorials: https://www.youtube.com/@YaronBeen/videos 💼 LinkedIn: https://www.linkedin.com/in/yaronbeen/ Get more automation tips, tutorials, and advanced workflows on my channels! 🏷️ Tags: AI, OpenAI, Stripe, Forecasting, Finance, CFO, Automation, Revenue, Analytics, GPT-4

⚙️🛠️🚀🤖🦾 This template is a PoC of a ReAct AI Agent capable of fetching random pages (not only Wikipedia or Google search results). On the top part there's a manual chat node connected to a LangChain ReAct Agent. The agent has access to a workflow tool for getting page content. The page content extraction starts with converting query parameters into a JSON object. There are 3 pre-defined parameters: url** – an address of the page to fetch method** = full / simplified maxlimit** - maximum length for the final page. For longer pages an error message is returned back to the agent Page content fetching is a multistep process: An HTTP Request mode tries to get the page content. If the page content was successfuly retrieved, a series of post-processing begin: Extract HTML BODY; content Remove all unnecessary tags to recuce the page size Further eliminate external URLs and IMG scr values (based on the method query parameter) Remaining HTML is converted to Markdown, thus recuding the page lengh even more while preserving the basic page structure The remaining content is sent back to an Agent if it's not too long (maxlimit = 70000 by default, see CONFIG node). NB: You can isolate the HTTP Request part into a separate workflow. Check the Workflow Tool description, it guides the agent to provide a query string with several parameters instead of a JSON object. Please reach out to Eduard is you need further assistance with you n8n workflows and automations! Note that to use this template, you need to be on n8n version 1.19.4 or later.

This workflow allows you to check for preview for a link and return the preview if it exists. Peekalink node: This node checks if a preview is available for a URL or not. If a preivew is available the node returns true, otherwise false. IF node: The IF node checks the output from the previous node. If the condition is true the node connected to the true branch is executed. If the condition is false the node connected to the false branch is executed. Peekalink1 node: This node will fetch the preview of the URL. Based on your use-case, you can connect the Slack node, Mattermost node etc. to get the response on these platforms. NoOp node: Adding this node here is optional, as the absence of this node won't make a difference to the functioning of the workflow. We've added this as it can sometimes help others with a better understanding of the workflow, visually.

Description This n8n workflow acts as your personal AI speechwriting coach, directly accessible through Telegram. It listens to your spoken or typed drafts, provides insightful feedback on clarity, engagement, structure, and content, and iteratively refines your message based on your updates. Once you're ready, it synthesizes a brand-new speech or talk incorporating all the improvements and your accumulated ideas. This tool streamlines the speechwriting process, offering on-demand AI assistance to help you craft impactful and well-structured presentations. How it Works Input via Telegram: You interact with the workflow by sending your speech drafts or talking points directly to a designated Telegram bot. AI Feedback: The workflow processes your input using AI models (OpenAI and/or Google Gemini) to analyze various aspects of your speech and provides constructive feedback via Telegram. Iterative Refinement: You can then send updated versions of your speech to the bot, receiving further feedback to guide your revisions. Speech Synthesis: When you send the command to "generate speech," the workflow compiles all your previous input and the AI's feedback to synthesize a new, improved speech or talk, which is then sent back to you via Telegram. New Speech Cycle: By sending the command "new speech," the workflow clears its memory, allowing you to start the process anew for a different topic. Set Up Steps (Takes Approximatly 5 Minutes) Step 1: Create a Telegram Bot and Obtain its ID Open the Telegram application and search for "BotFather". Start a chat with BotFather by clicking "Start" or sending the /start command. Create a new bot by sending the command /newbot. Follow BotFather's instructions to choose a name and username for your bot. Once your bot is created, BotFather will provide you with an API token. Keep this token secure as it's required to connect your n8n workflow to your bot. Step 2: Obtain an OpenAI API Key Go to the OpenAI website (https://platform.openai.com/) and sign up for an account if you don't already have one. Navigate to the API keys section (usually under your profile settings or a "Developers" tab). Click on "Create new secret key". Copy the generated API key and store it securely. You will need to provide this key to your n8n workflow to access OpenAI's language models. Step 3: Obtain a Google Gemini LLM API Key Go to the Google Cloud AI Platform or Google AI Studio website (the specific platform may vary depending on the current Google AI offerings; search for "Google AI API"). Sign up or log in with your Google account. Follow the instructions to enable the Gemini API and create an API key. This might involve creating a project if you haven't already. Copy the generated API key and store it securely. You can then configure your n8n workflow to utilize Google Gemini's language models as well. Customization Options This n8n workflow offers significant flexibility, below are a few options: Modify AI prompts to tailor feedback and generation for presentations, storytelling, interviews, sales pitches, academic talks, and creative writing. Switch the interface from Telegram to Slack, WhatsApp, or even a web interface by replacing the relevant n8n nodes. Integrate analysis for sentiment, keyword density, pacing (with voice input), and filler word detection by adjusting the workflow. Connect to external data sources to provide context to the AI for more targeted feedback and generation. This adaptability allows you to re use this workflow for a wide range of specific use cases and communication environments.

This workflow looks for a Close Date value using REGEX in the IF node. If it finds the correct value, it will pass that value on. If it does not find the correct value, it will generate a value based on the present time plus three weeks. The final result will show up in the NoOps node. You can text this execution by enabling and disabling the Set node when you run the execution.

This workflow template creates an audio stream session on UltraVox compatible with Plivo and sends it to Plivo. How It Works : Plivo initiates a call and requests the Answer URL. The workflow responds with Plivo XML to join the session. Note: Ensure you update the UltraVox API Key in the credentials. Update System Prompt based on your requirements. Check Youtube Video

This workflow acts as your personal AI-powered analyst for Meta Ads. It's pretty straightforward: First, it grabs a list of Facebook Ad Library URLs you want to check out from a Google Sheet. Then, it automatically scrapes the active ads from those pages. Here's the cool part: it sends each ad's image and text to Google Gemini, which analyzes it like an expert marketer would. Finally, Gemini's full analysis—we're talking strengths, weaknesses, actionable suggestions, and a performance score—gets dropped neatly into another Google Sheet for you. Set up steps You should be ready to roll in about 5 minutes. There are no complex configurations, you just need to: Connect your accounts: The workflow has placeholders waiting for your credentials for Google (for Sheets and the Gemini API) and ScrapingFlash. Link your Google Sheets: Just point the first Google Sheets node to the sheet with your URLs, and tell the last node where you want to save the results. All the nitty-gritty details and expressions are explained in the sticky notes inside the workflow itself!