Workflow Templates

Primer workflow for OpenAI models: ChatGPT, DALLE-2, Whisper This workflow contains 5 examples on how to work with OpenAI API. Transcribe voice into text via Whisper model (disabled, please put your own mp3 file with voice) The old way of using OpenAI conversational model via text-davinci-003 Examples 1.x. Simple ChatGPT calls. Text completion and text edit Example 2. Provide system and user content into ChatGPT Examples 3.x. Create system / user / assistanc content via Code Node. Promtp chaining technique example Example 4. Generate code via ChatGPT Example 5. Return multiple answers. Useful for providing picking the most relevant reply IMPORTANT! Do not run the whole workflow, it's rather slow Better execute the last node of each branch or simply disconnect branches that are not needed

Fact-Checking Workflow Documentation Overview This workflow is designed for automated fact-checking of texts. It uses AI models to compare a given text with a list of facts and identify potential discrepancies or hallucinations. Components 1. Input The workflow can be initiated in two ways: a) Manually via the "When clicking 'Test workflow'" trigger b) By calling from another workflow via the "When Executed by Another Workflow" trigger Required inputs: facts: A list of verified facts text: The text to be checked 2. Text Preparation The "Code" node splits the input text into individual sentences Takes into account date specifications and list elements 3. Fact Checking Each sentence is individually compared with the given facts Uses the "bespoke-minicheck" Ollama model for verification The model responds with "Yes" or "No" for each sentence 4. Filtering and Aggregation Sentences marked as "No" (not fact-based) are filtered The filtered results are aggregated 5. Summary A larger language model (Qwen2.5) creates a summary of the results The summary contains: Number of incorrect factual statements List of incorrect statements Final assessment of the article's accuracy Usage Ensure the "bespoke-minicheck" model is installed in Ollama (ollama pull bespoke-minicheck) Prepare a list of verified facts Enter the text to be checked Start the workflow The results are output as a structured summary Notes The workflow ignores small talk and focuses on verifiable factual statements Accuracy depends on the quality of the provided facts and the performance of the AI models Customization Options The summarization function can be adjusted or removed to return only the raw data of the issues found The AI models used can be exchanged if needed This workflow provides an efficient method for automated fact-checking and can be easily integrated into larger systems or editorial workflows.

🔮 Mystic Tarot Bot — AI-Powered iMessage Readings This magical n8n template turns your iMessage inbox into a soulful tarot reading experience powered by Blooio and AI. Users can send in questions or photos of their tarot spreads, and the bot replies like a mystical oracle — interpreting symbols, offering gentle insights, and guiding with poetic warmth. ✨ Ideal for solo reflection, spiritual creators, or client-based guidance services — no tech knowledge needed. 🌟 Use Cases Offer intuitive, emotionally resonant tarot readings via iMessage Support coaching, wellness, and metaphysical businesses with AI-enhanced readings Accept photos of real tarot card spreads or plain text questions Great for automating daily card pulls, client responses, or onboarding into spiritual flows 🧠 Good to Know Built using Blooio’s iMessage API — supports image attachments and conversational replies Includes visual recognition and symbolic interpretation of real tarot card photos Responses generated by OpenAI with a custom “Mystic Tarot Reader” persona Onboards users if they say “Hi” or request a virtual card draw Responds in poetic, spiritually attuned language — no markdown, no tech-speak ⚙️ How it Works Trigger: iMessage webhook via Blooio receives user message or image Check: Bot ignores self-sent messages to prevent loops Detect: If a photo is attached, it’s passed to AI for card recognition Interpret: The AI agent gives a heartfelt, symbolic interpretation Respond: A final, warm tarot reading is sent back through iMessage 📝 How to Use Set Up Blooio: Sign up at https://blooio.com Choose a Dedicated or Enterprise plan (image support required) Copy your API key from Settings → API Keys Paste it into the Send Message HTTP node as a Bearer token Customize the Experience: Adjust the prompt for a different tone or deck style Add journaling prompts, affirmations, or follow-ups Use other workflows to track users, create reading logs, or offer upsells Try It Out: Text your Blooio-connected number with: “Hi” → get onboarding “Draw a card for me” → get a virtual pull A tarot photo + question → get a full, soulful reading ✅ Requirements Blooio Account & API Token (Dedicated plan or higher for images) Optional: Tarot images, user questions, or both 🔧 Customizing This Workflow Add personalized spreads (e.g. past/present/future layouts) Send AI-generated visuals of the pulled cards Route readings into Notion, Airtable, or Google Sheets Expand to WhatsApp, web, or email with Blooio’s multichannel support 🃏 Let the cards speak. Let the messages flow.

This workflow automatically identifies and tracks backlink opportunities by analyzing competitor link profiles and finding potential linking websites. It saves you time by eliminating the need to manually research backlink prospects and provides a systematic approach to link building and SEO improvement. Overview This workflow automatically scrapes competitor backlink profiles and analyzes potential linking opportunities by examining referring domains, anchor text patterns, and link quality metrics. It uses Bright Data to access backlink data sources and AI to intelligently identify high-value linking opportunities for your SEO strategy. Tools Used n8n**: The automation platform that orchestrates the workflow Bright Data**: For scraping backlink analysis platforms without being blocked OpenAI**: AI agent for intelligent backlink opportunity analysis Google Sheets**: For storing backlink opportunities and tracking data How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Bright Data: Add your Bright Data credentials to the MCP Client node Set Up OpenAI: Configure your OpenAI API credentials Configure Google Sheets: Connect your Google Sheets account and set up your backlink tracking spreadsheet Customize: Define target domains and backlink analysis parameters Use Cases SEO Teams**: Identify high-quality backlink opportunities for link building campaigns Content Marketing**: Find websites that might be interested in linking to your content Competitive Analysis**: Analyze competitor link profiles to discover new opportunities Digital PR**: Identify potential media outlets and industry websites for outreach Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #backlinks #seo #linkbuilding #brightdata #webscraping #seotools #n8nworkflow #workflow #nocode #linkanalysis #backlinkresearch #seoautomation #linkprospecting #digitalmarketing #backlinkmonitoring #seoanalysis #linkopportunities #competitoranalysis #seoresearch #linkstrategy #backlinkanalysis #domainanalysis #linktracking #seomonitoring #searchmarketing #organicseo #linkbuilding #seocampaigns

This workflow is for anyone looking to automatically fetch, validate, and parse complex language-based queries into a structured format. Its unique capability lies in not only processing language but also fixing invalid outputs before structuring them. Note that to use this template, you need to be on n8n version 1.19.4 or later.

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.

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 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.