Workflow Templates

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 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.

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

Workflow Description: Automated Content Publishing for WordPress This n8n workflow automates the entire process of content generation, image selection, and scheduled publishing to a self-hosted WordPress website. It is designed for bloggers, marketers, and businesses who want to streamline their content creation and posting workflow. 🌟 Features ✅ AI-Powered Content Generation Uses ChatGPT to generate engaging, market-ready blog articles Dynamically incorporates high-search volume keywords ✅ Automated Image Selection Searches for relevant stock images from Pexels Embeds images directly into posts (Optional)* Supports *Featured Image from URL (FIFU) plugin** for WordPress ✅ Scheduled & Randomized Posting Automatically schedules posts at predefined intervals Supports randomized delay (0-6 hours) for natural publishing ✅ WordPress API Integration Uses WordPress REST API to directly publish posts Configures featured images, categories, and metadata Supports SEO-friendly meta fields ✅ Flexible & Customizable Works with any WordPress website (self-hosted) Can be modified for other CMS platforms 🔧 How It Works 1️⃣ Trigger & Scheduling Automatically runs at preset times or on-demand Supports cron-like scheduling 2️⃣ AI Content Generation Uses a well-crafted prompt to generate high-quality blog posts Extracts relevant keywords for both SEO and image selection 3️⃣ Image Fetching from Pexels Searches and retrieves high-quality images Embeds image credits and ensures proper formatting 4️⃣ WordPress API Integration Sends post title, content, image, and metadata via HTTP Request Can include custom fields, categories, and tags 5️⃣ Randomized Delay Before Publishing Ensures natural posting behavior Avoids bulk publishing issues 📌 Requirements Self-hosted WordPress website* with *REST API enabled** FIFU Plugin* (optional) for *external featured images** n8n Self-Hosted or Cloud Instance** 🚀 Who Is This For? ✅ Bloggers who want to automate content publishing ✅ Marketing teams looking to scale content production ✅ Business owners who want to boost online presence ✅ SEO professionals who need consistent, optimized content 💡 Ready to Automate? 👉 Click here to get this workflow! (Replace with Purchase URL)

This workflow will trigger daily at 6am to retrieve your day's calendar events from Google Calendar and send them as a summary message to Slack. I've used a low-code method to filter the dates as I can't code much in JSON :) Contact me on https://twitter.com/sami_abid if you have any questions!

Track NFT listings, offers, orders, and trait-based pricing in real time! This workflow integrates OpenSea API, AI-powered analytics (GPT-4o-mini), and n8n automation to provide instant insights into NFT trading activity. Ideal for NFT traders, collectors, and investors looking to monitor the market and identify profitable opportunities. How It Works A user submits a query about NFT listings, offers, or order history. The OpenSea Marketplace Agent determines the correct API tool: Retrieve active NFT listings for a collection. Fetch valid offers for individual NFTs or entire collections. Identify the cheapest NFT listings by collection or token ID. Track the highest offer made for a single NFT. Access detailed order history for a transaction. The OpenSea API (requires API key) is queried to fetch real-time data. The AI engine processes and structures the response, making it easy to interpret. The NFT marketplace insights are delivered via Telegram, Slack, or stored in a database. What You Can Do with This Agent 🔹 Find the Best NFT Listings → Retrieve the cheapest available listings in any collection. 🔹 Track Offers on NFTs → See all active offers, including highest bids. 🔹 Analyze Collection-Wide Market Data → Compare listings, offers, and sales activity. 🔹 Retrieve Order Details → Search by order hash to check buyer, seller, and transaction status. 🔹 Fetch NFT Trait-Based Offers → Identify rare traits that receive premium bids. 🔹 Monitor Multi-Chain Listings → Works across Ethereum, Polygon (Matic), Arbitrum, Optimism, and more. Example Queries You Can Use ✅ "Show me the 10 cheapest listings for Bored Ape Yacht Club." ✅ "Find the highest bid for CryptoPunk #1234." ✅ "Track all open offers for Azuki NFTs." ✅ "Retrieve details for this OpenSea order: 0x123abc... on Ethereum." ✅ "List all NFTs for sale in the 'CloneX' collection." Available API Tools & Endpoints 1️⃣ Get All Listings by Collection → /api/v2/listings/collection/{collection_slug}/all (Fetches active listings for a collection) 2️⃣ Get All Offers by Collection → /api/v2/offers/collection/{collection_slug}/all (Retrieves all offers for a collection) 3️⃣ Get Best Listing by NFT → /api/v2/listings/collection/{collection_slug}/nfts/{identifier}/best (Finds the lowest-priced NFT listing) 4️⃣ Get Best Listings by Collection → /api/v2/listings/collection/{collection_slug}/best (Fetches the cheapest listings per collection) 5️⃣ Get Best Offer by NFT → /api/v2/offers/collection/{collection_slug}/nfts/{identifier}/best (Retrieves the highest offer for an NFT) 6️⃣ Get Collection Offers → /api/v2/offers/collection/{collection_slug} (Shows collection-wide offers) 7️⃣ Get Item Offers → /api/v2/orders/{chain}/{protocol}/offers (Fetches active item-specific offers) 8️⃣ Get Listings by Chain & Protocol → /api/v2/orders/{chain}/{protocol}/listings (Retrieves active listings across blockchains) 9️⃣ Get Order Details by Hash → /api/v2/orders/chain/{chain}/protocol/{protocol_address}/{order_hash} (Checks order status using an order hash) 🔟 Get Trait-Based Offers → /api/v2/offers/collection/{collection_slug}/traits (Fetches offers for specific NFT traits) Set Up Steps Get an OpenSea API Key Sign up at OpenSea API and request an API key. Configure API Credentials in n8n Add your OpenSea API key under HTTP Header Authentication. Connect the Workflow to Telegram, Slack, or Database (Optional) Use n8n integrations to send alerts to Telegram, Slack, or save results to Google Sheets, Notion, etc. Deploy and Test Send a query (e.g., "Get the best listing for BAYC #5678") and receive instant insights! Stay ahead of the NFT market—gain powerful insights with AI-powered OpenSea analytics!

This workflow allows you to easily evaluate and compare the outputs of two language models (LLMs) before choosing one for production. In the chat interface, both model outputs are shown side by side. Their responses are also logged into a Google Sheet, where they can be evaluated manually or automatically using a more advanced model. Use Case You're developing an AI agent, and since LLMs are non-deterministic, you want to determine which one performs best for your specific use case. This template is designed to help you compare them effectively. How It Works The user sends a message to the chat interface. The input is duplicated and sent to two different LLMs. Each model processes the same prompt independently, using its own memory context. Their answers, along with the user input and previous context, are logged to Google Sheets. You can review, compare, and evaluate the model outputs manually (or automate it later). In the chat, both responses are also shown one after the other for direct comparison. How To Use It Copy this Google Sheets template (File > Make a Copy). Set up your System Prompt and Tools in the AI Agent node to suit your use case. Start chatting! Each message will trigger both models and log their responses to the spreadsheet. Note: This version is set up for two models. If you want to compare more, you’ll need to extend the workflow logic and update the sheet. About Models You can use OpenRouter or Vertex AI to test models across providers. If you're using a node for a specific provider, like OpenAI, you can compare different models from that provider (e.g., gpt-4.1 vs gpt-4.1-mini). Evaluation in Google Sheets This is ideal for teams, allowing non-technical stakeholders (not just data scientists) to evaluate responses based on real-world needs. Advanced users can automate this evaluation using a more capable model (like o3 from OpenAI), but note that this will increase token usage and cost. Token Considerations Since each input is processed by two different models, the workflow will consume more tokens overall. Keep an eye on usage, especially if working with longer prompts or running multiple evaluations, as this can impact cost.

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.

A powerful sub-agent that collects real-time market structure data from Binance for any trading pair — including price, volume, order book depth, and candlestick snapshots across multiple timeframes (15m, 1h, 4h, 1d). 🎥 Watch Tutorial: 🎯 Purpose This workflow powers the Quant AI system with: ✅ Real-time price feed (/ticker/price) ✅ 24-hour stats (OHLC, % change, volume via /ticker/24hr) ✅ Live order book depth (/depth) ✅ Latest candlestick data (/klines) for all major intervals All outputs are parsed and formatted using GPT and returned to the parent agent (e.g., Financial Analyst Tool) as a Telegram-optimized summary. ⚙️ Workflow Architecture | Node | Role | | ------------------------------------ | ------------------------------------------------------------ | | 🔗 Execute Workflow Trigger | Accepts input from parent workflow | | 🧠 Simple Memory | Stores session + symbol info | | 🤖 Binance SM Market Agent | Parses prompt, routes tool calls | | 💡 OpenAI Chat Model (gpt-4o-mini) | Converts raw data into a clean, readable format for Telegram | | 🌐 getCurrentPrice | Gets latest price | | 🌐 get24hrStats | Gets OHLC/volume over past 24 hours | | 🌐 getOrderBook | Gets top 100 bids and asks | | 🌐 getKlines | Gets latest 15m, 1h, 4h, and 1d candles | 📥 Input Requirements This workflow is not called directly by the user. Instead, it is triggered by another workflow, such as: { "message": "BTCUSDT", "sessionId": "539847013" } 📤 Telegram Output Example 📊 BTCUSDT Market Overview 💰 Price: $63,220 📈 24h Change: +2.3% | Volume: 45,210 BTC 📉 Order Book • Top Bid: $63,190 • Top Ask: $63,230 🕰️ Latest Candles • 15m: O: $63,000 | C: $63,220 | Vol: 320 BTC • 1h : O: $62,700 | C: $63,300 | Vol: 980 BTC • 4h : O: $61,800 | C: $63,500 | Vol: 2,410 BTC • 1d : O: $59,200 | C: $63,220 | Vol: 7,850 BTC ✅ Use Cases | Scenario | Output Provided | | ---------------------------------- | ------------------------------------------------------------ | | “Show current BTC price and trend” | Price, 24h stats, candles, and order book in one message | | “Candles for SOL” | 15m, 1h, 4h, 1d candlesticks for SOLUSDT | | Triggered by Quant AI system | Clean Telegram-ready summary with all structure tools merged | 🧩 Toolchain Breakdown | Tool Name | Endpoint | Purpose | | ----------------- | ---------------------- | ------------------------------ | | getCurrentPrice | /api/v3/ticker/price | Latest trade price | | get24hrStats | /api/v3/ticker/24hr | 24h OHLC, % change, volume | | getOrderBook | /api/v3/depth | Top 100 bids and asks | | getKlines | /api/v3/klines | 1-candle snapshot across 4 TFs | 🚀 Installation Steps Import the JSON into your n8n instance Connect your OpenAI credentials for the Chat Model node No Binance API key needed — public endpoints Trigger this tool only via: Binance SM Financial Analyst Tool Binance Spot Market Quant AI Agent 🔐 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn

A professional-grade AI automation system for spot market trading insights on Binance. It analyzes multi-timeframe technical indicators, live price/order data, and crypto sentiment, then delivers fully formatted Telegram-style trading reports. 🎥 Watch Tutorial: 🧩 Required Workflows You must install and activate all of the following workflows for the system to function correctly: | ✅ Workflow Name | 📌 Function Description | | -------------------------------------------------- | -------------------------------------------------------------------------------- | | Binance Spot Market Quant AI Agent | Final AI orchestrator. Parses user prompt and generates Telegram-ready reports. | | Binance SM Financial Analyst Tool | Calls indicator tools and price/order data tools. Synthesizes structured inputs. | | Binance SM News and Sentiment Analyst Webhook Tool | Analyzes crypto sentiment, gives summary and headlines via POST webhook. | | Binance SM Price/24hrStats/OrderBook/Kline Tool | Pulls price, order book, 24h stats, and OHLCV klines for 15m–1d. | | Binance SM 15min Indicators Tool | Calculates 15m RSI, MACD, BBANDS, ADX, SMA/EMA from Binance kline data. | | Binance SM 1hour Indicators Tool | Same as above but for 1h timeframe. | | Binance SM 4hour Indicators Tool | Same as above but for 4h timeframe. | | Binance SM 1day Indicators Tool | Same as above but for 1d timeframe. | | Binance SM Indicators Webhook Tool | Technical backend. Handles all webhook logic for each timeframe tool. | ⚙️ Installation Instructions Step 1: Import Workflows Open your n8n Editor UI Import each workflow JSON file one by one Activate them or ensure they're called via Execute Workflow Step 2: Set Credentials OpenAI API Key** (GPT-4o recommended) Binance endpoints** are public (no auth required) Step 3: Configure Webhook Endpoints Deploy Binance SM Indicators Webhook Tool Ensure the following paths are reachable: /webhook/15m /webhook/1h /webhook/4h /webhook/1d Step 4: Telegram Integration Create a Telegram bot using @BotFather Add your Telegram API token to n8n credentials Replace the Telegram ID placeholder with your own Step 5: Final Trigger Trigger the Binance Spot Market Quant AI Agent manually or from Telegram The agent: Extracts the trading pair (e.g. BTCUSDT) Calls all tools for market data and sentiment Generates a clean, HTML-formatted Telegram report 💬 Telegram Report Output Format BTCUSDT Market Report Spot Strategy • Action: Buy • Entry: $63,800 | SL: $61,200 | TP: $66,500 • Rationale:  MACD Crossover (1h)  RSI Rebound from Oversold (15m)  Sentiment: Bullish Leverage Strategy • Position: Long 3x • Entry: $63,800 • SL/TP zones same as above News Sentiment: Slightly Bullish • "Bitcoin rallies as ETF inflows surge" – CoinDesk • "Whales accumulate BTC at key support" – NewsBTC 🧠 System Overview [Telegram Trigger] → [Session + Auth Logic] → [Binance Spot Market Quant AI Agent] → [Financial Analyst Tool + News Tool] → [All Technical Indicator Tools (15m, 1h, 4h, 1d)] → [OrderBook/Price/Kline Fetcher] → [GPT-4o Reasoning] → [Split & Send Message to Telegram] 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding or resale permitted. 🔗 For support: LinkedIn – Don Jayamaha

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.

Overview This n8n workflow processes user feedback automatically, tags it with sentiment, and links it to relevant insights in Notion. It uses GPT-4 to analyze each feedback entry, determine whether it corresponds to an existing insight or a new one, and update the Notion databases accordingly. It helps teams centralize and structure qualitative user feedback at scale. Who It’s For Product teams looking to organize and prioritize user feedback. Founders or solo builders seeking actionable insights from qualitative data. Anyone managing a Notion workspace where feedback is collected and needs to be tagged or linked to features and improvements. Prerequisites A Notion account with: A Feedback database (must include fields for feedback content and status). An Insights database with multi-select fields for Solution, User Persona, and a relation to Feedback. The Notion template (linked below) helps you get started quickly — just remove the mock data. A configured Notion API integration in n8n. 👉 Don’t forget to connect the n8n integration to the correct Notion page. An OpenAI API key Notion Template This workflow is designed to work seamlessly with a pre-configured Notion template that includes the required feedback and insights structure. 👉 User Feedback Analysis – Notion Template How It Works The workflow is triggered when a feedback item is updated in Notion (e.g. new feedback is submitted). Sentiment analysis (Positive, Neutral, or Negative) is run using OpenAI and stored in a select field in Notion. The AI agent analyzes the feedback to: Identify whether it matches an existing insight. Or create a new insight in Notion with a concise name, solution, and user persona. The feedback is then linked to the appropriate insight and marked as "Processed." How to Use It Connect your Notion databases in all Notion nodes (including those used by the AI agent) for both Feedback and Insights — follow the node names provided. Ensure your OpenAI and Notion credentials are correctly set. Set up your product context: Define a “Product Overview” and list your “Core Features”. This helps the AI agent categorize insights more accurately. (The Basecamp product is used as an example in the template.) (Optional) Modify the prompt to better fit your specific product context. Once feedback is added or updated in Notion, the workflow triggers automatically. Notes Only feedback with the status Received is processed. New insights are only created if no relevant match is found. Feedback is linked to insights via Notion’s relation property. A fallback parser is included to fix potential formatting issues in the AI output. You can swap the default n8n memory for a more robust backend like Supabase. 🙏 Please share your feedback with us. It helps us tremendously!