Workflow Templates

This workflow template is designed for dental assistants and anyone looking to automate appointment scheduling. It integrates Google Calendar for booking appointments and Google Sheets as a database to store patient information. How It Works The user interacts with the chatbot to schedule an appointment. The chatbot collects necessary details and checks availability via Google Calendar. If the requested time is available, the AI books the appointment. If unavailable, the AI suggests alternative time slots. Once booked, the AI logs the appointment details into Google Sheets for record-keeping. Setup Instructions 📌 Watch this 🎥 Setup Video for detailed instructions on running and customizing this workflow. Step 1: Set Up Credentials OpenAI API Key (for chatbot functionality). Google Account (for Google Sheets & Google Calendar integration). Step 2: Choose the Right Tools Select the correct Google Calendar in the Google Calendar tool. Choose the appropriate Google Sheets file in the Google Sheets tool. Step 3: Test Run a test to ensure everything works correctly. Once tested. Example Templates Below are sample Google Sheets template to help you get started.

How the sequence works: A "Schedule Trigger" node activates the automation at a defined schedule. An "Airtable" node will search for previously posted questions in your question database. Airtable Base Template: here An "Aggregate" node will take all the questions from Airtable and compress them to a single output. ChatGPT, or a model of your choice, will generate a discussion question based on the options in the system prompt. The discussion question will be posted to the subreddit of your choice by the "Reddit" node. You can choose between a text, image, or link post! The recently-posted discussion question will then be uploaded to your Airtable base using the "Airtable" node. This will be used to prevent ChatGPT from creating duplicate questions. Setup Steps The setup process will take about 5 minutes. An Airtable base template is also pre-made for you here: https://airtable.com/app6wzQqegKIJOiOg/shrzy7L9yv8BFRQdY Set the recurrence in the "Schedule" node Create an Airtable account, you can use the link here. Get an Airtable personal access token here. Configure the "Get Previous Discussions" Airtable node. Configure the options in brackets in the "Generate New Discussion" node. Set the desired subreddit to post to and the post type(text, image, or link) in the "Post Discussion" node. Configure the "Create Archived Discussion" node to map to the Airtable base(required) and specific subreddit(optional).

This n8n workflow demonstrates how to create a really simple yet effective customer support channel and pipeline by combining Slack, Linear and AI tools. Built on n8n's ability to integrate anything, this workflow is intended for small support teams who want to maximise re-use of the tools they already have with an interface which is doesn't require any onboarding. Read the blog post here: https://blog.n8n.io/automated-customer-support-tickets-with-n8n-slack-linear-and-ai/ How it works The workflow is connected to a slack channel setup with the customer to capture support issues. Only messages which are tagged with a "✅" reaction are captured by the workflow. Messages are tagged by the support team in the channel. Each captured support issue is sent to the AI model to classify, prioritise and rewrite into a support ticket. The generated support ticket is uploaded to Linear for the support team to investigate and track. Support team is able to report back to the user via the channel when issue is fixed. Requirements Slack channel to be monitored Linear account and project Customising this workflow Don't have Linear? This workflow can work just as well with traditional ticketing systems like JIRA.

How it works: This workflow automates the entire LinkedIn content distribution process — from AI-powered post creation to auto-posting on both personal LinkedIn profiles and LinkedIn groups, using GPT-4o and Google Sheets as the content source and control panel. Auto-generates professional LinkedIn posts from spreadsheet topics using GPT-4o. Posts to your LinkedIn profile and multiple groups. Updates status to avoid duplicate posting. Fully customizable and reusable with your spreadsheet. Set up Steps Create and Upload the Spreadsheet Name it: Linkedin Post Sheet1 (for post topics): Columns: ID | Linkedin Post Title | Status Add post titles under Linkedin Post Title Set Status to Pending Create new sheet name as "Groups" (for group distribution): Column: GroupIds Add LinkedIn Group IDs, one per row Connect Google Sheets Nodes Connect your Google account to these nodes: Linkedin Post topic (Reads post topics) Get group id (Reads LinkedIn groups) Update Status (Writes back the status after posting) Configure GPT-4o (OpenAI) Add your OpenAI API key in the Linkedin Post creator node This node will generate high-quality content from your topic titles Connect LinkedIn Account Add your LinkedIn credentials in the Linkedin user detail node Ensure appropriate permissions to post on profile and groups Activate the Workflow : Once live, the workflow will: Monitor the Google Sheet for Pending posts. Generate content via GPT-4o. Post to: Your LinkedIn Profile Each LinkedIn Group listed in the Groups sheet Update the post Status to Posted Customization Tips Want to personalize this template? Change AI tone or style in the OpenAI node prompt Add a scheduler node if you'd like to post at fixed intervals Use a Slack or Telegram approval step before posting Integrate analytics tools to track post performance Suggested Sticky Notes for Workflow | Node or Section | Sticky Note Content | | ---------------------- | --------------------------------------------------------------------------- | | Linkedin Post topic | Reads the topic titles and statuses from Sheet1 | | OpenAI (GPT-4o) | Generates content using topic title — you can modify the tone/prompt here | | Linkedin user detail | Your personal LinkedIn credentials — required to post | | Group loop | Iterates through LinkedIn Group IDs and posts the content | | Update Status | Updates spreadsheet so the topic isn't re-posted |

📰 This AI-powered agent performs real-time sentiment analysis on Tesla (TSLA) news to support trading decisions. It aggregates headlines from 5 trusted sources and uses DeepSeek Chat to classify sentiment and generate structured summaries. This tool is a critical sub-agent in the broader Tesla Quant Trading AI Agent system. ⚠️ Not standalone — this agent is designed to be executed by the Tesla Quant Trading AI Agent. ⚙️ Requires: DeepSeek Chat API Key 🔌 Workflow Role This tool processes Tesla-related news and produces output like: { "sentiment": "bullish", "summary": "Tesla stock rallied today after strong delivery numbers and Cybertruck updates. Analysts remain optimistic.", "topHeadlines": [ "Tesla beats Q2 delivery forecast – Yahoo Finance", "Cybertruck ramps up in Texas – Electrek", "Berlin Gigafactory expands battery production – CleanTechnica" ] } Its output feeds directly into the master trading agent’s final trade report. 📰 News Sources Used This agent collects real-time headlines from: Google News (filtered by “Tesla” or “TSLA”) Yahoo Finance (TSLA-specific feed) Electrek (Tesla archive) CleanTechnica (Tesla sustainability news) TeslaNorth (app/product release updates) These five tools are always queried together to ensure market-wide signal coverage. 🤖 What the Agent Does Pulls headlines from all 5 Tesla-specific RSS feeds Uses DeepSeek Chat to: Analyze narrative tone (bullish / bearish / neutral) Identify macro/financial drivers Generate a 2–3 sentence summary Return top 3–5 headlines Outputs structured JSON for downstream use 🛠️ Setup Instructions 1. Install & Name Import this file and name it: Tesla_News_and_Sentiment_Analyst_Tool 2. Add DeepSeek API Credentials Go to: Credentials → Add New → DeepSeek API Save as: DeepSeek account 3. Internet Access Required Ensure RSS feeds can fetch live headlines Works best with a cloud-hosted n8n instance or tunnel-enabled local install 4. Must Be Triggered by Parent Triggered via Execute Workflow by the Tesla Quant Trading AI Agent Requires these inputs: message: optional query context sessionId: passed to maintain short-term memory across executions 🧠 Agent Architecture | Node Name | Function | | ---------------------------------- | ------------------------------------------------ | | DeepSeek Chat Model | Performs AI-based sentiment analysis | | Tesla News and Sentiment Analyst | Combines results, formats output in strict JSON | | Simple Memory | Stores session-level context (short-term memory) | | 5x RSS nodes | Aggregate Tesla news from trusted media outlets | 📌 Sticky Notes Included 🟢 Trigger from Parent Workflow – Executed only by main TSLA agent 🟠 News Feeds Overview – Lists and explains each of the 5 feeds 🧠 DeepSeek Chat Notes – Describes LLM behavior and parsing role 🔵 Short-Term Memory – Buffers sentiment context during user session 📘 Sentiment Analyst Agent – Summarizes key responsibilities 📎 Licensing & Attribution © 2025 Treasurium Capital Limited Company This architecture, workflow structure, and prompt design are licensed for educational and operational use only. Commercial resale or rebranding prohibited without authorization. 🔗 Creator: Don Jayamaha 🔗 Templates: https://n8n.io/creators/don-the-gem-dealer/ 🚀 Power your TSLA trading with AI-driven sentiment—built with DeepSeek Chat and 5 trusted news sources. This tool is required by the Tesla Quant Trading AI Agent.

Document-Aware WhatsApp AI Bot for Customer Support Google Docs-Powered WhatsApp Support Agent 24/7 WhatsApp AI Assistant with Live Knowledge from Google Docs 📝Description Template Smart WhatsApp AI Assistant Using Google Docs Help customers instantly on WhatsApp using a smart AI assistant that reads your company’s internal knowledge from a Google Doc in real time. Built for clubs, restaurants, agencies, or any business where clients ask questions based on a policy, FAQ, or services document. ⚙️ How it works Users send free-form questions to your WhatsApp Business number (e.g. “What are the gym rules?” or “Are you open today?”) The bot automatically reads your company’s internal Google Doc (policy, schedule, etc.) It merges the document content with today’s date and the user’s question to craft a custom AI prompt The AI (Gemini or ChatGPT) then replies back on WhatsApp using natural, helpful language All conversations are logged to Google Sheets for reporting or audit > 💡Bonus: The AI even understands dates inside the document and compares them to today’s date — e.g. if your document says “Closed May 25 for 30 days,” it will say “We're currently closed until June 24. 🧰 Set up steps Connect your WhatsApp Cloud API account (Meta) Add your Google account and grant access to the Doc containing your company info Choose your AI model (ChatGPT/OpenAI or Gemini) Paste your document ID into the Google Docs node Connect your WhatsApp webhook to Meta (only takes 5 minutes) Done — start receiving and answering customer questions! > 📄 Works best with free-tier OpenAI/Gemini, Google Docs, and Meta's Cloud API (no phone required). Everything is modular, extensible, and low-code. 🔄 Customization Tips Change the Google Doc anytime to update answers — no retraining needed Add your logo and business name in the AI agent’s “System Prompt” Add fallback routes like “Escalate to human” if the bot can't help Clone for multiple brands by duplicating the workflow and swapping in new docs 🤝 Need Help Setting It Up? If you'd like help connecting your WhatsApp Business API, setting up Google Docs access, or customizing this AI assistant for your business or clients… 📩 I offer setup, branding, and customization services: WhatsApp Cloud API setup & verification Google OAuth & Doc structure guidance AI model configuration (OpenAI / Gemini) Branding & prompt tone customization Logging, reporting, and escalation logic Just send a message via: Email: tharwat.elsayed2000@gmail.com WhatsApp: +20 106 180 3236

Instantly access real-time decentralized exchange (DEX) insights directly in Telegram! This workflow integrates the DexScreener API with GPT-4o-powered AI and Telegram, allowing users to fetch the latest blockchain token analytics, liquidity pools, and trending tokens effortlessly. Ideal for crypto traders, DeFi analysts, and investors who need actionable market data at their fingertips. How It Works A Telegram bot listens for user queries about tokens or trading pairs. The workflow interacts with the DexScreener API (no API key required) to fetch real-time data, including: Token fundamentals (profiles, images, descriptions, and links) Trending and boosted tokens (hyped projects, potential market movers) Trading pair analytics (liquidity, price action, volumes, volatility) Order and payment activity (transaction insights, investor movements) Liquidity pool depth (market stability, capital flows) Multi-chain pair comparisons (performance tracking across networks) An AI-powered language model (GPT-4o-mini) enhances responses for better insights. The workflow logs session data to improve user interaction tracking. The requested DEX insights are sent back via Telegram in an easy-to-read format. What You Can Do with This Agent This AI-driven Telegram bot enables you to: ✅ Track trending and boosted tokens before they gain mainstream traction. ✅ Monitor real-time liquidity pools to assess token stability. ✅ Analyze active trading pairs across different blockchains. ✅ Identify transaction trends by checking paid orders for tokens. ✅ Compare market activity with detailed trading pair analysis. ✅ Receive instant insights with AI-enhanced responses for deeper understanding. Set Up Steps Create a Telegram Bot Use @BotFather on Telegram to create a bot and obtain an API token. Configure Telegram API Credentials in n8n Add your Telegram bot token under Telegram API credentials. Deploy and Test Send a query (e.g., "SOL/USDC") to your Telegram bot and receive real-time insights instantly! 🚀 Unlock powerful, real-time DEX insights directly in Telegram—no API key required! 📺 Setup Video Tutorial Watch the full setup guide on YouTube:

🔍 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.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🚀 Start-up Ideas Generator – From Idea to Executive Summary in Minutes Description: This AI-powered n8n workflow helps you brainstorm and validate start-up ideas, perform market research using Perplexity Sonar, and automatically generate a professional business plan — all within minutes. It’s designed for entrepreneurs, accelerators, venture studios, and ideation teams looking to go from a single prompt to a detailed proposal ready to pitch or develop. Watch step-by-step build video of n8n workflows like this: https://www.youtube.com/@Automatewithmarc Setup Instructions Required Credentials: OpenAI API Key – For GPT-4.1 Perplexity Sonar Access Token – For deep research Anthropic Claude API Key – For business plan writing Google Service Account Credentials – To write to Docs How It Works: 💬 Chat Trigger  Start the process by typing a simple request like “Give me a few start-up ideas in AI tech.” 🧠 AI Research Agent (OpenAI + Perplexity Sonar)  The system defines the research scope, taps into Perplexity AI for deep market scans, and outputs high-potential business opportunities including: Market size Customer pain points Competition overview Differentiation strategy 📄 Business Case Generator (Claude)  Each opportunity is expanded into a complete business plan using Claude Sonnet, covering: Executive summary Market analysis Product description Competitor gap Business model & GTM Financials & roadmap 📃 Google Docs Export  The full business plan is automatically inserted into a connected Google Doc for easy sharing, editing, or pitching. Google Docs Configuration: Create a Google Doc titled "Startup Business Plan" (or adjust the title in the node settings) Share the document with your Google service account email Update the Document ID field in the Google Docs node accordingly Ensure that the structure accepts plain text input — formatting is handled by the node Tools & Models Used: LangChain Chat Trigger OpenAI GPT-4.1 (Research Prompt Structuring) Perplexity Sonar Deep Research (Market Research) Anthropic Claude Sonnet (Business Plan Writing) Google Docs Node (Formatted Output) Use Cases: Rapid ideation for venture building or incubators Validating start-up ideas before prototyping Automating market research + proposal writing Generating investor-ready pitch materials

Try It Out! This n8n template creates a fully automated Instagram content schedule using AI and Google Sheets. It is perfect for content creators, marketing teams, or local businesses looking to organize and scale their social media posting. How it works The workflow starts by reading two sets of inputs from a Google Sheet: Your content strategy inputs (Pillar, Objective, Frequency, Format, Structure, Examples). A list of scraped blog posts with title, URL, and description (fetched from your website). Blog posts are scraped using Apify and parsed to extract key fields, which are stored in a tab labeled "Input (blog month)". You can assign a preferred posting month for each blog (e.g. fall blog posts get tagged for September). The workflow then merges both inputs and extracts the relevant information for further information added by ChatGPT. AI Scheduling & Personalization Once merged, the workflow loops through each content item and: Identifies if the scheduled post falls on or near a holiday (like Mother’s Day) and adjusts the content accordingly. A reference tool is attached to guide structure and tone, based on a library of post examples. Sends the content to an AI Agent (using GPT-4, but customizable) that generates: A compelling Instagram caption A visual description Hashtags Suggested post date, day, content pillar, and format (carousel, reel, image, etc.) Output All generated content including captions, structure, dates, hashtags, and pillar is exported into a tab titled Output in your Google Sheet. The final schedule is ready for manual review, editing, or publishing to social media. How to use The workflow uses a manual trigger to start, but you can replace it with a Webhook, cron job, or form submission. Add/edit your content strategy in Google Sheets. How to Set-Up Initial Input Tab Define your content pillars and structure Create a tab named "Input" or "Strategy" Include these columns: Pillar: e.g., Family images Objective: e.g., Showcase images Frequency: e.g., Bi-weekly Content Form: e.g., Images, Reels Structure: brief description of expected layout (e.g., carousel Q&A, singular photo) Examples: prompts or questions to guide AI (e.g., Why do you think families should do a session?) Input (blog month) Tab – Store scraped blog content Include these columns: URL: direct link to blog post Title: blog post title Description: short summary of the post Preferred Month: month you want it posted (e.g., August, September) This sheet is partially auto-filled by the workflow (except for Preferred Month) Output Tab – Final scheduled content Include these columns: Date: scheduled posting date (YYYY-MM-DD) Day: day of the week Pillar: content category assigned Format: e.g., Images, Reels, Carousel Description: visual summary Caption: Instagram-ready caption Hashtags: complete hashtag block To use the Apify HTTP Request node: Drag in an HTTP Request node into your n8n workflow. Set the Method and URL based on how you're using Apify: Use POST if you want to run an actor live with dynamic input (e.g. scrape blog posts in real time). Use GET if you want to retrieve results from a completed or static dataset run (faster and cheaper if you're reusing previous data). Configure query or body parameters: Include your Apify API token for authentication (e.g. token=YOUR_API_KEY) For POST: include an input object with any required actor settings (e.g., blog URL to scrape). For GET: specify the dataset ID in the URL Test the node to ensure you're retrieving the blog titles, descriptions, and URLs as expected. Requirements Apify account for scraping blog posts OpenAI key (e.g. GPT-4) or another model of your choice Google Sheets Credentials Example Use Cases A photographer repurposing blogs into Instagram carousels A nonprofit automatically generating seasonal posts A small team managing multi-pillar content across weeks or months Need Help? Join the n8n Discord or ask in the n8n Forum! Happy Content Making ! 📅✨

AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: text similarity, measured character-by-character. The workflow takes images of hand-written codes, extracts the code and compares it with the expected answer from the dataset. The images look like this: The workflow works as follows: We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular trigger so that the workflow can be started from either one. More info We download the image and use AI to extract the code If we’re evaluating (i.e. the execution started from the evaluation trigger), we calculate the string distance metric We pass this information back to n8n as a metric

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.