Workflow Templates

📝 Description This workflow automates the collection, filtering, and scoring of trending AskReddit posts for viral potential. It pulls posts from Reddit, removes duplicates, calculates a custom virality score, and writes the final candidates into Google Sheets for later use in content creation. This is Phase 1 of the AskReddit → YouTube Shorts automation pipeline. It prepares clean, high-quality data that can be used in the next phases (script generation, AI video creation, and publishing). ⚙️ Setup Steps Import Workflow into your n8n instance. Reddit API: Add your Reddit API credentials in the "Get AskReddit Posts" node. Google Sheets: Connect your Google account. Point the "Write Candidates" node to your target Google Sheet. Virality Scoring: The "Add Virality Score" node assigns weights (e.g., upvotes, comments). Adjust the scoring logic as needed for your niche. Run Workflow: Execute manually or schedule with Cron. Verify that trending AskReddit posts appear in your sheet, scored and cleaned.

This beginner-friendly n8n workflow teaches essential data manipulation techniques using Google Sheets and AI. You'll learn how to: ✅ Merge two datasets by a shared column (Channel) 🔍 Filter rows based on performance metrics (Clicks, Spend) 🔀 Branch logic into "Great" vs. "Poor" outcomes 📊 Summarize results by team leader 🤖 Use an OpenAI-powered agent to generate a written analysis highlighting the best and worst performers Perfect for marketers, analysts, or anyone learning how to clean, transform, and interpret data inside n8n. Includes: 📁 Sample Google Sheet to copy 🛠 Setup instructions for Google Sheets & OpenAI ✨ AI summary powered by GPT-4o-mini 👋 Questions or Feedback? Feel free to reach out — I’m happy to help! Robert Breen Founder, Ynteractive 🌐 ynteractive.com 📧 robert@ynteractive.com 📺 YouTube: YnteractiveTraining 🔗 LinkedIn: linkedin.com/in/robertbreen

This n8n workflow demonstrates how to use AI to update your grocery list in Asana via Telegram chat or voice. Use cases Update grocery list details in Asana eg. check or uncheck the items, update expiry dates, update quantities etc. How it works Instruct telegram bot (via chat or voice) to update a grocery item using natural language. For example, "we just bought 10 cartons of milk that expires in 6 months". If via text, just the text message will be sent to the Grocery Agent. If via voice, voice file will be downloaded then transcribed into text using OpenAI. Once Grocery agent receives the text, it will search the item in your grocery list in Asana. It will then check the item since it's bought, and update the quantity and expiry date accordingly. Once task is done, it will respond with the changes it made and insert a hyperlink to Asana if you want to see it. How to set up Set up Telegram bot via Botfather. See setup instructions here Setup OpenAI API for transcription services (Credits required) here Set up Openrouter account. See details here Set up Asana API using the account where you have your grocery list set in. See details here Customization Options You can have other custom fields you use to track other than expiry dates or quantity. For example, food type, date purchased etc. Requirements Asana account where you manage your grocery list Telegram bot Open AI account Open Router account

How it works This workflow automates the classification and routing of incoming Intercom conversations. When a new customer message arrives, it is analyzed by AI to determine category, sentiment, urgency, and tags. Based on this classification, the workflow creates tasks in ClickUp for Support or Product requests, or sends real-time alerts to Slack for Sales inquiries. Step-by-step Webhook Intake Triggered when Intercom sends a new conversation payload. Captures customer details, message content, and metadata. AI Classification Sends the conversation JSON to OpenAI (gpt-4o-mini) with a structured prompt. AI returns a JSON object with category (Support, Product, Sales, Other), sentiment, urgency, reasoning, and tags. Processing & Structuring A Code node parses the AI output and merges it with conversation details. Prepares formatted task fields such as title, description, customer info, and priority. Conditional Routing Support requests → Task created in ClickUp with urgency and tags. Product requests → Task created in ClickUp with structured details. Sales inquiries → Slack alert sent to the Sales channel with context and AI reasoning. Other → No task/action triggered. Benefits Automates Intercom ticket triage and routing in real time. Ensures consistent, AI-driven classification of all customer conversations. Reduces manual review time for Support, Product, and Sales teams. Creates structured tasks with enriched metadata for faster resolution. Keeps Sales teams instantly informed with Slack alerts for urgent leads.

Who’s it for This template is for users who want to combine the power of AI with Google Sheets for managing and calculating data quickly. It’s ideal for small businesses, data entry teams, and anyone who tracks lists, orders, or tasks in Google Sheets and needs AI-driven insights or calculations. How it works The workflow connects an AI agent with Google Sheets and a calculator tool. When a user sends a chat message, the AI interprets the request, retrieves or updates rows in the connected sheet, and performs calculations when needed. For example, it can read a list of orders from a sheet and calculate totals or averages instantly. It also supports creating, updating, and deleting rows from the sheet through natural language instructions. How to set up Copy the provided Google Sheet into your Google Drive. Connect your Google Sheets credentials in n8n. Add your OpenAI credentials for the AI agent. Deploy the workflow and start interacting with it by sending chat prompts. Requirements OpenAI account (for AI responses) Google Sheets account with a spreadsheet n8n instance with LangChain nodes enabled How to customize the workflow Change the spreadsheet fields (ID, Name, etc.) to match your own data structure. Modify the AI prompt to guide the agent’s tone or behavior. Extend the workflow by adding more Google Sheets operations or AI tools for advanced tasks.

Overview This workflow deploys a fully autonomous "AI SEO Agency" inside your n8n instance. Unlike simple chatbots, this is a hierarchical agent swarm. A "Director" agent acts as the project manager, using live market data to orchestrate a team of 6 specialized AI workers. It takes a single user prompt and turns it into a comprehensive, professional-grade SEO strategy report. Key Features Hierarchical Architecture:** A "Manager" agent delegates tasks to "Worker" agents. Live Market Research:* Uses *SerpApi** to fetch real-time Google Search results and competitor data. Conversational Memory:** Remembers business details across the chat session. 6 Expert Specialists:** Includes dedicated agents for Keyword Research, Technical SEO, Link Building, Analytics, Local SEO, and Content Writing. How it works Analysis: The SEO Director Agent receives your request and consults its memory. Live Research: The Director uses the SerpApi tool to perform live Google searches on the target website and niche to gather context. Delegation: Based on the research, the Director dynamically assigns tasks to the relevant Specialist Agents (e.g., calling the "Technical Specialist" for site speed issues or the "Keyword Specialist" for content ideas). Synthesis: The Director compiles the outputs from all specialists into one cohesive, actionable strategy report. Set up steps Estimated time: 5 minutes OpenAI Keys: Add your OpenAI API Key to all 7 "OpenAI Chat Model" nodes (1 for the Director, 6 for the Specialists). SerpApi Key: Open the "SEO Director Agent" node. Under "Tools" > "SerpApi," add your SerpApi Key (free tier available). This enables the live Google Search capability. Run: Toggle the workflow to "Active" and start chatting! About the Creator Built by Pixril. We specialize in building advanced, production-ready AI agents for n8n. Find more professional workflows in our shop: https://pixril.etsy.com

🧠 RAG-Based Customer Support Agent (GPT-5 + Telegram) Description: This workflow builds a powerful Retrieval-Augmented Generation (RAG) Customer Support Agent that interacts with users directly through Telegram using the GPT-5 model. It combines real-time conversational capabilities with context-aware responses by leveraging vector search via Pinecone, making it ideal for automated, intelligent support systems. Watch Video Tutorial Build on Workflows Like These: https://www.youtube.com/@Automatewithmarc 💬 Key Features: Telegram Integration: Listens to customer queries via the Telegram Trigger node and sends back intelligent responses in the same chat. GPT-5 Agent (LangChain): A powerful AI agent node orchestrates the conversation using OpenAI's GPT-5 model. Contextual Memory: A Memory Buffer stores the last 15 interactions per user to provide more personalized and coherent multi-turn conversations. RAG with Pinecone: Integrates with Pinecone to fetch relevant answers from your “Customer FAQ” vector namespace, enabling grounded and accurate responses. Embeddings Generation: Uses OpenAI’s Embeddings node to process and vectorize documents for retrieval. End-to-End AI Pipeline: Connects all components from input to output, providing seamless and intelligent customer support. 🔧 Tech Stack: GPT-5 via OpenAI API Pinecone vector store (namespace: Customer FAQ) Telegram Bot API LangChain agent, memory, and embedding tools n8n self-hosted or cloud instance 📌 Ideal Use Cases: Automated customer support for e-commerce, SaaS, or community support FAQ bots with up-to-date product or policy documents Multilingual support agents (customizable via GPT-5) 🛠️ Setup Instructions: Set up your Telegram bot and insert credentials. Add your OpenAI and Pinecone API keys. Upload or index your support documents into the Customer FAQ namespace on Pinecone. Deploy and test your Telegram bot.

📧 Master Your First AI Email Agent with Smart Fallback! Welcome to your hands-on guide for building a resilient, intelligent email support system in n8n! This workflow is specifically designed as an educational tool to help you understand advanced AI automation concepts in a practical, easy-to-follow way. 🚀 What You'll Learn & Build: This powerful template enables you to create an automated email support agent that: Monitors Gmail** for new customer inquiries in real-time. Processes requests** using a primary AI model (Google Gemini) for efficiency. Intelligently falls back to a secondary AI model** (OpenAI GPT) if the primary model fails or for more complex queries, ensuring robust reliability. Generates personalized and helpful replies** automatically. Logs every interaction** meticulously to a Google Sheet for easy tracking and analysis. 💡 Why a Fallback Model is Game-Changing (and Why You Should Learn It): Unmatched Reliability (99.9% Uptime):** If one AI service experiences an outage or rate limits, your automation seamlessly switches to another, ensuring no customer email goes unanswered. Cost Optimization:** Leverage more affordable models (like Gemini) for standard queries, reserving premium models (like GPT) only when truly needed, significantly reducing your API costs. Superior Quality Assurance:** Get the best of both worlds – the speed of cost-effective models combined with the accuracy of more powerful ones for complex scenarios. Real-World Application:** This isn't just theory; it's a critical pattern for building resilient, production-ready AI systems. 🎓 Perfect for Beginners & Aspiring Automators: Simple Setup:** With drag-and-drop design and pre-built integrations, you can get this workflow running with minimal configuration. Just add your API keys! Clear Educational Value:** Learn core concepts like AI model orchestration strategies, customer service automation best practices, and multi-model AI implementation patterns. Immediate Results:** See your AI agent in action, responding to emails and logging data within minutes of setup. 🛠️ Getting Started Checklist: To use this workflow, you'll need: A Gmail account with API access enabled. A Google Sheets document created for logging. A Gemini API key (your primary AI model). An OpenAI API key (your fallback AI model). An n8n instance (cloud or desktop). Embark on your journey to building intelligent, resilient automation systems today!

🔗 Slack + Bitly UTM Generator — Powered by OpenAI Description: This no-code n8n workflow transforms how marketing teams generate Bitly links with UTM parameters — directly from Slack. Powered by AI and fully automated, this system extracts relevant campaign data from a Slack message, creates a clean Bitly shortlink with UTM tags, and logs everything to a Google Sheet for tracking and reporting. Perfect for growth marketers, content teams, and anyone tired of manually building UTM-tagged links. If you like to follow step-by-step build of workflows like these, check out: https://www.youtube.com/@Automatewithmarc ⚙️ How It Works 🟢 Slack Trigger The workflow starts when a user mentions the bot in a Slack channel (e.g., @BitlyBot link this for IG campaign). 🧠 AI Agent (LangChain) Uses GPT-4o-mini to infer UTM values (e.g., utm_source, utm_medium, utm_campaign) Normalizes short forms like "IG" to "instagram" Follows UTM naming conventions (e.g., lowercase, underscore-separated) 🔍 Information Extractor Pulls cleanly structured UTM data from the AI response to prep for Bitly. 🔗 Bitly Tool Node Generates a short link using the inferred target URL + UTM values. 📋 Google Sheets Logger Automatically appends the full details (Bitly link, UTM parameters, campaign owner) to a Google Sheet for easy access. 📢 Slack Response Replies in-thread with the new Bitly link and campaign details, formatted clearly for the user. 🛑 Error Handling If Bitly link generation fails, the workflow gracefully stops with an error message. 🔧 Tools & Services Used Slack (Trigger + Response) LangChain AI Agent (with GPT-4o-mini) Bitly (via Bitly Tool Node) Google Sheets (auto-log generated links) OpenAI GPT-4o-mini (Language model for prompt understanding) 💡 Use Cases 🔗 Instantly create UTM-tagged links for campaigns 📊 Maintain a central Bitly + UTM link database in Google Sheets 🧠 Use AI to reduce manual tagging and formatting errors 🤝 Empower your team to request links via Slack, no forms needed ✅ Setup Instructions Slack: Set up a Slack bot and connect it using Slack Trigger and Slack response nodes. Bitly API: Generate a Bitly access token and set up credentials in the Bitly node. OpenAI / LangChain: Connect your GPT-4o or GPT-4 API key to the OpenAI Chat Model nodes. Google Sheets: Use OAuth2 credentials to connect to your Google Sheet. Make sure the sheet has matching columns for UTM parameters (sample headers included in the node schema).

📊 Description Enhance content quality, SEO performance, and editorial consistency using an AI-powered optimization engine that blends OpenAI, Google Sheets history, Pinecone knowledge, and real-time SERP intelligence. This workflow transforms rough drafts into polished, SEO-optimized content while preserving original meaning — and includes human review before final publication. 🚀✍️ What This Template Does Step 1: Trigger the optimization from Chat or manual run: Starts the optimization process using the Chat Trigger node, passing topic, content ID, and customization parameters. 💬 Step 2: Retrieve contextual knowledge: Pulls historical versions from Google Sheets and relevant company information from Pinecone vector storage to guide consistent optimization. 📚 Step 3: Fetch SERP competitor data: Uses SerpAPI to gather ranking competitors, headings, snippets, PAA questions, and search intent to strengthen the optimized draft. 🔍 Step 4: Run AI content optimization: AI Agent (GPT-4o-mini) rewrites the draft without starting from scratch, improving structure, SEO, tone, clarity, and keyword coverage. 🤖 Step 5: Enforce structured JSON output: Ensures the optimized draft follows a strict JSON schema containing title, meta description, sections, keywords, and metadata. 🧩 Step 6: Request human review in Slack: Sends the optimized draft to Slack and waits for approval (approve/reject). Team members can refine or confirm before finalization. 💬🧑‍💼 Step 7: Save approved version back to Google Sheets: Updates or appends a new version in the content_versions sheet with metadata, SEO fields, and version history. 📊 Step 8: Send success confirmation to Slack: Posts a notification confirming that the approved draft has been published. 🔔 Key Benefits ✓ Eliminates manual editing and SEO refinement ✓ Produces consistent, high-quality, conversion-focused content ✓ Ensures factual accuracy and tone preservation ✓ Enhances content using SERP-based competitor insights ✓ Maintains version history for auditability ✓ Introduces structured human approval workflow ✓ Fully automated publishing pipeline Features AI-assisted rewrite using GPT-4o-mini Google Sheets version retrieval + updating Pinecone knowledge base retrieval SERP competitor and keyword intelligence Slack approval workflow (sendAndWait) Structured JSON output enforcement Version incrementing & metadata tracking Secure credentials management Requirements OpenAI API Key (GPT-4o-mini or higher) Google Sheets OAuth2 credentials SerpAPI Key Slack Bot Token with chat:write Pinecone API and vector index Pre-created Google Sheet for versioning Optional: Existing company knowledge stored in Pinecone Target Audience SEO content teams optimizing blog drafts Marketing teams refining landing pages Agencies managing editorial workflows Enterprises maintaining knowledge-based content Writers/editorial teams that need AI assistance + human QA Teams that require version-controlled SEO content Step-by-Step Setup Instructions Connect these credentials in n8n: OpenAI, Slack, Google Sheets, Pinecone, SerpAPI. 🔐 Replace Google Sheet ID in the Sheets nodes with your own. Ensure your Pinecone index exists and contains embeddings. Configure Slack channel ID for approvals and notifications. Update test topic/content ID in the Set Input Parameters node. Run a manual test to confirm SERP retrieval, data context, and AI output. Deploy and use Chat Trigger to start generating optimized content on demand.

📝 Auto-Generate Meeting Notes & Summaries (Zoom → Google Docs + Slack) This workflow automatically captures Zoom meeting data when a meeting ends, generates AI-powered notes, saves them to Google Docs, and instantly posts a summary with a link in Slack. ⚙️ How It Works Zoom Webhook → Triggers on meeting.ended or recording.completed. Normalize Data → Extracts meeting details (topic, host, duration, transcript). AI Notes (GPT-4) → Summarizes transcript into key decisions, action items, and next steps. Google Docs → Saves formatted meeting notes + transcript archive. Slack Post → Shares summary + link to notes in #team-meetings. 🛠️ Setup Steps 1. Zoom App Go to Zoom Developer Console → create App. Enable event meeting.ended. Paste workflow webhook URL. 2. Google Docs Connect Google OAuth in n8n. Docs auto-saved in your Google Drive. 3. Slack Connect Slack OAuth. Replace channel #team-meetings. 4. OpenAI Add your OpenAI API key. Uses GPT-4 for accurate summaries. 📊 Example Output Slack Message: 📝 Auto-Generate Meeting Notes & Summaries (Zoom → Google Docs + Slack) This workflow automatically captures Zoom meeting data when a meeting ends, generates AI-powered notes, saves them to Google Docs, and instantly posts a summary with a link in Slack. ⚙️ How It Works Zoom Webhook → Triggers on meeting.ended or recording.completed. Normalize Data → Extracts meeting details (topic, host, duration, transcript). AI Notes (GPT-4) → Summarizes transcript into key decisions, action items, and next steps. Google Docs → Saves formatted meeting notes + transcript archive. Slack Post → Shares summary + link to notes in #team-meetings. 🛠️ Setup Steps 1. Zoom App Go to Zoom Developer Console → create App. Enable event meeting.ended. Paste workflow webhook URL. 2. Google Docs Connect Google OAuth in n8n. Docs auto-saved in your Google Drive. 3. Slack Connect Slack OAuth. Replace channel #team-meetings. 4. OpenAI Add your OpenAI API key. Uses GPT-4 for accurate summaries. 📊 Example Output Slack Message: 📝 New Meeting Notes Available Topic: Marketing Sync Host: david@company.com Duration: 45 mins 👉 Read full notes here: https://docs.google.com/document/d/xxxx Google Doc: Executive Summary Key Decisions Action Items w/ Owners Next Steps Full Transcript ⚡ With this workflow, your team never scrambles for meeting notes again.

Who is this for? This n8n workflow template is designed for customer support, CX, and ops teams that manage customer messages through HubSpot and use Jira for internal task management. It is especially useful for SaaS companies aiming to automate ticket triage, sentiment detection, and team assignment using AI agents. 🧩 What problem is this workflow solving? Customer service teams often struggle with manual message classification, delayed reactions to churn signals, and inefficiencies in routing support issues to the right internal teams. This workflow uses LLMs and automated profiling to: Detect churn risk or intent in customer messages Summarize issues Classify tickets into categories (e.g. fulfillment, technical, invoicing) Automatically create Jira tickets based on enriched insights 🤖 What this workflow does This AI-powered workflow processes HubSpot support tickets and routes them to Jira based on sentiment and topic. Here’s the full breakdown: Triggers: Either manually or on a schedule (via cron). Fetch HubSpot tickets: Retrieves new messages and their metadata. Run Orchestration Agent: Uses Sentinel Agent to detect emotional tone, churn risk, and purchase intent. Calls Profiler Agent to enrich customer profiles from HubSpot. Summarizes the message using OpenAI. Classifies the ticket using a custom classifier (technical, fulfillment, etc.). Generate a Jira ticket: Title and description are generated using GPT. The assignee and project are predefined. AI agents can be expanded (e.g. add Guide or Facilitator agents). ⚙️ Setup To use this template, you’ll need: HubSpot account** with OAuth2 credentials in n8n Jira Software Cloud account** and project ID OpenAI credentials** for GPT-based nodes Optional: Create sub-workflows for additional AI agents Steps: Clone the workflow in your n8n instance. Replace placeholder credentials for HubSpot, OpenAI, and Jira. Adjust Jira project/issue type IDs to match your setup. Test the workflow using the manual trigger or scheduled trigger node. 🛠️ How to customize this workflow to your needs 1. Edit category logic In the “Category Classifier” node, modify categories and prompt structure to match your internal team structures (e.g., billing, account management, tech support). 2. Refine AI prompts Customize the agent prompt definitions in: Sentinel_agent Profiler_agent Orchestrator to better align with your brand tone or service goals. 3. Update Jira integration You can route tickets to different projects or team leads by adjusting the “Create an issue in Jira” node based on classification output. 4. Add escalation paths Insert Slack, email, or webhook notifications for specific risk levels or customer segments. This workflow empowers your team with real-time message triage, automated decision-making, and AI-enhanced customer insight, turning every inbound ticket into a data-driven action item.