Workflow Templates

🚀 AI Marketing Campaign Generator Upload product image + details → Get complete professional marketing campaign with 5 custom-generated assets automatically. 🤖 AI Model GPT-4o Mini (OpenAI) - For campaign strategy | Prompt Image generation GPT Image-1 (OpenAI) - For visual asset generation 🔑 Required API Keys OpenAI API - AI analysis & image generation Google Drive API - Asset storage & organization 🎯 What It Generates 5 Marketing Assets: Instagram Post, Instagram Story, Website Banner, Ad Creative, Testimonial Graphic Brand Strategy: Colors, tone, positioning from your product image Campaign Strategy: Messaging, target audience, objectives Visual Analysis: Extracts colors, materials, styling from uploaded image ⚙️ Setup Import JSON to n8n Add OpenAI & Google Drive credentials Configure Google Drive folder for asset storage Deploy form webhook Test with product image upload 📱 How It Works Upload product image → AI analyzes visual + text → Generates complete campaign → Creates 5 custom marketing assets → Saves to Google Drive

Auto-detect news from n8n and turn into a human-approved LinkedIn post. gotoHuman is used to keep a human in the loop. There you can manually edit the AI draft of the post or request to regenerate it. How it works The workflow is triggered each day to fetch the latest version of https://blog.n8n.io. It then fetches each article, checks if it was published in the last 24 hours and uses an LLM to summarize it. An LLM then drafts a related LinkedIn post which is sent to gotoHuman for approval. In gotoHuman, the reviewer can manually edit it or ask to regenerate it with the option to even edit the prompt (Retries loop back to the AI Draft LinkedIn Post node) Approved Posts are automatically published to LinkedIn How to set up Most importantly, install the gotoHuman node before importing this template! (Just add the node to a blank canvas before importing) Set up your credentials for gotoHuman, OpenAI, and LinkedIn In gotoHuman, select and create the pre-built review template "Blog scraper agent" or import the ID: sMxevC9tSAgdfWsr6XIW Select this template in the gotoHuman node Requirements You need accounts for gotoHuman (human supervision) OpenAI (summary, draft) LinkedIn How to customize Change the blog URL to monitor. Adapt to its' HTML structure Provide the AI Draft LinkedIn Post with examples of previous posts so it picks up your writing style (consider adding gotoHuman's dataset of approved examples) Use the workflow to target other publications, like your newsletter, blog or other socials

How it works This workflow automates customer feedback management by capturing reviews through a form, analyzing them with AI for sentiment and insights, and then creating structured tasks across Monday.com, ClickUp, and HubSpot. It ensures that customer concerns are categorized, prioritized, and assigned to the right teams with actionable metadata. Step-by-step Trigger & Input The workflow starts when a customer submits the Feedback Form containing their Name, Message, Rating, and Product/Service. The submitted data is pre-processed with a Code node to cleanly extract fields for analysis. AI Analysis & Processing The extracted review is sent to OpenAI GPT-4 for analysis. AI identifies sentiment, sentiment score, category (e.g., product, service, support, delivery, pricing), department, priority, required actions, keywords, and suggested response tone. A Data Processing node enriches the output with due dates, task titles, structured descriptions, and fallback handling in case of parsing issues. Structured Output Generation An AI Agent and OpenAI Chat model transform the enriched data into a strict JSON format that is compatible with Monday.com, ClickUp, and HubSpot. This ensures consistent field order, formatting, and metadata for all downstream integrations. Task Creation in Platforms The structured task data is automatically pushed to: Monday.com → Creates an item in a specified board. ClickUp → Creates a task with mapped fields and priority. HubSpot → Creates an engagement task in CRM with due date and priority. Benefits Automates end-to-end customer feedback analysis and task creation. Ensures structured, AI-driven insights for actionable responses. Reduces manual work in categorizing and assigning reviews. Keeps customer feedback synchronized across multiple platforms (Monday.com, ClickUp, HubSpot). Improves response time by prioritizing high-impact feedback with due dates.

J.A.R.V.I.S. Multimodal AI assistant on Telegram with OpenAI This workflow transforms your Telegram bot into J.A.R.V.I.S., a powerful, multimodal AI assistant. It can understand and process text, voice messages, images, and documents. The assistant can search the web, scrape websites, generate images, perform calculations, and reference uploaded documents to provide comprehensive and context-aware responses in either text or audio format. 🧑‍💻 Who’s it for This workflow is for developers, AI enthusiasts, and businesses who want to create an advanced, interactive AI assistant on Telegram. It’s perfect for automating customer support, creating a personal AI helper, or exploring the capabilities of multimodal large language models (LLMs) in a practical application. ⚙️ How it works The workflow begins when a message is received by your Telegram bot. A Switch node then directs the data based on the message type: Text:** The message is formatted and sent directly to the main AI agent. Voice:** The audio file is downloaded from Telegram and transcribed into text using the OpenAI API. Image:** The image is downloaded and analyzed by an OpenAI vision model to understand its content. Document:** The file is downloaded and its content is stored in a temporary vector store, making it searchable for the AI. The processed input is then passed to the core "J.A.R.V.I.S." Agent node. This agent uses an OpenAI model, conversational memory, and a suite of tools (Google Search, Web Scraper, Image Generator, Calculator, and the document vector store) to formulate a response. Finally, the workflow checks if the initial message was a voice note; if so, it generates an audio response. Otherwise, it sends the answer as a text message back to the user. 🛠️ How to set up Telegram: Create a Telegram Bot - Use @BotFather to create a bot and obtain your bot token; Add Telegram API credentials in n8n with your bot token to the Receive Message Trigger node and all other Telegram nodes. In the Receive Message node, enter the chatId of the user or group authorized to interact with the bot. OpenAI: Add your OpenAI API credentials to all OpenAI, AI Agent, and AI tool nodes. SerpAPI: Add your SerpAPI credentials to the Basic Google Search node to enable web search functionality. Jina AI: Add your Jina AI API key to the Setup Node - The API Key is used on the Webpage Scraper node. ✅ Requirements Telegram Bot API credentials and Bot token. OpenAI API credentials. SerpAPI API credentials. Jina.ai API credentials 🎨 How to customize the workflow Change the AI model:** You can select a different OpenAI model in the OpenAI Chat Model node (e.g., switch from gpt-4.1 to gpt-4o) or in the Analyze Image and Transcribe nodes. Modify the AI's personality:** Edit the system prompt in the J.A.R.V.I.S. Agent node to change its name, tone, instructions, or default language. Expand its tools:** Connect more tools to the J.A.R.V.I.S. Agent node to extend its capabilities, such as connecting to a database or another third-party API. Adjust the response format:** Modify the If Audio Response node to change the conditions for sending text or audio messages. For example, you could configure it to always respond with text. 💬 Need Help? Join the Discord or ask in the Forum

How It Works User sends a reminder request via Telegram (e.g., “Remind me to clean the garage tomorrow at 12 pm”). The request is parsed by AI Agent and stored in Airtable with a unique reminder code. The reminder workflow checks Airtable at scheduled intervals and sends a Telegram notification when the reminder is due. Each reminder includes a unique cancel code (e.g., Reply 4936 to stop this reminder). If the user replies with the code, the bot searches Airtable, deletes the reminder, and confirms the deletion in Telegram. If the code doesn’t exist, the bot replies “Code not found.” ⚡ Setup Steps Create a Telegram Bot Use BotFather on Telegram. Run /newbot and copy your bot token. Add the token in your Telegram Trigger and Telegram Send nodes in n8n. Set Up Airtable Create an Airtable base called REMINDER-TABLE. Add a table with fields: title (Text) – reminder text due_at (Date/Time) – when the reminder is due chat_id (Text) – user’s Telegram chat ID code (Number/Text) – unique cancel code Generate an API key / Personal Access Token and connect it in n8n. Import This Workflow In n8n, click Import Workflow. Paste the JSON template. Connect your Telegram and Airtable credentials. Activate the Workflow Start the workflow in n8n Cloud or Self-Hosted. Send a test reminder in Telegram (e.g., “Remind me in 5 minutes to call mom”). When notified, reply with the cancel code to test deletion. Optional Customizations Modify reminder frequency (Every 5 minutes node). Change reminder message formatting in the Format Message node. Add logging/analytics by connecting Google Sheets or another DB. ⚡ Result: You now have a fully automated AI-powered Telegram Reminder Bot with Airtable storage, cancel codes, and real-time notifications!

Description Transform Figma design files into detailed QA test cases with AI-driven analysis and structured export to Google Sheets. This workflow helps QA and product teams streamline design validation, test coverage, and documentation — all without manual effort. 🎨🤖📋 What This Template Does Step 1: Trigger manually and input your Figma file ID. 🎯 Step 2: Fetches the full Figma design data (layers, frames, components) via API. 🧩 Step 3: Sends structured design JSON to GPT-4o-mini for intelligent test case generation. 🧠 Step 4: AI analyzes UI components, user flows, and accessibility aspects to generate 5–10 test cases. ✅ Step 5: Parses and formats results into a clean structure. Step 6: Exports test cases directly to Google Sheets for QA tracking and reporting. 📊 Key Benefits ✅ Saves 2–3 hours per design by automating test case creation ✅ Ensures consistent, comprehensive QA documentation ✅ Uses AI to detect UX, accessibility, and functional coverage gaps ✅ Centralizes output in Google Sheets for easy collaboration Features Figma API integration for design parsing GPT-4o-mini model for structured test generation Automated Google Sheets export Dynamic file ID and output schema mapping Built-in error handling for large design files Requirements Figma Personal Access Token OpenAI API key (GPT-4o-mini) Google Sheets OAuth2 credentials Target Audience QA and Test Automation Engineers Product & Design Teams Startups and Agencies validating Figma prototypes Setup Instructions Connect your Figma token as HTTP Header Auth (X-Figma-Token). Add your OpenAI API key in n8n credentials (model: gpt-4o-mini). Configure Google Sheets OAuth2 and select your sheet. Input Figma file ID from the design URL. Run once manually, verify output, then enable for regular use.

👥 Who's it for This workflow is perfect for businesses or individuals who want to automate WhatsApp conversations 💬 with an intelligent AI chatbot that can handle text, voice notes 🎵, and images 🖼️. No advanced coding required! 🤖 What it does It automatically receives WhatsApp messages through WasenderAPI, intelligently buffers consecutive messages to avoid fragmented responses, processes multimedia content (transcribing audio and analyzing images with AI), and responds naturally using GPT-4o mini with conversation memory. All while protecting your WhatsApp account from being banned. ⚙️ How it works 📱 Webhook Trigger – Receives new messages from WasenderAPI 🗃️ Redis Buffer System – Groups consecutive messages intelligently (7-second window) 🔀 Content Classifier – Routes messages by type (text, audio, or image) 🎵 Audio Processing – Decrypts and transcribes voice notes using OpenAI Whisper 🖼️ Image Analysis – Decrypts and analyzes images with GPT-4O Vision 🧠 AI Agent (GPT-4o mini) – Generates intelligent responses with 10-message memory ⏱️ Anti-Ban Wait – 6-second delay to simulate human typing 📤 Message Sender – Delivers response back to WhatsApp user 📋 Requirements WasenderAPI account with connected WhatsApp number : https://wasenderapi.com/ Redis database (free tier works fine) OpenAI API key with access to GPT-4o mini and Whisper n8n's AI Agent, LangChain, and Redis nodes 🛠️ How to set up Create your WasenderAPI account and connect a WhatsApp number Set up a free Redis database and get connection credentials Configure OpenAI API key in n8n credentials Replace the WasenderAPI Bearer token in "Get the audio", "Get the photo", and "Send Message to User" nodes Change the Manual Trigger to a Webhook and configure it in WasenderAPI Customize the AI Agent prompt to match your business needs Adjust wait times if needed (default: 6 seconds for responses, 7 seconds for buffer) Save and activate the workflow ✅ 🎨 How to customize Modify the AI Agent prompt to change bot personality and instructions Adjust buffer wait time (7 seconds) for faster/slower message grouping Change response delay (6 seconds) based on your use case , its recomendable 30 seconds. Add more content types (documents, videos) by extending the Switch Type node Configure conversation memory window (default: 10 messages)

📚 Telegram RAG Chatbot with PDF Document & Google Drive Backup An upgraded Retrieval-Augmented Generation (RAG) chatbot built in n8n that lets users ask questions via Telegram and receive accurate answers from uploaded PDFs. It embeds documents using OpenAI and backs them up to Google Drive. 👤 Who’s it for Perfect for: Knowledge workers who want instant access to private documents Support teams needing searchable SOPs and guides Educators enabling course material Q&A for students Individuals automating personal document search + cloud backup ⚙️ How it works / What it does 💬 Telegram Chat Handling User sends a message Triggered by the Telegram bot, the workflow checks if the message is text. Text message → OpenAI RAG Agent If the message is text, it's passed to a GPT-powered document agent. This agent: Retrieves relevant info from embedded documents using semantic search Returns a context-aware answer to the user Send answer back The bot sends the generated response back to the Telegram user. Non-text input fallback If the message is not text, the bot replies with a polite unsupported message. 📄 PDF Upload and Embedding User uploads PDFs manually A manual trigger starts the embedding flow. Default Data Loader Reads and chunks the PDF(s) into text segments. Insert to Vector Store (Embedding) Text chunks are embedded using OpenAI and saved for retrieval. Backup to Google Drive The original PDF is uploaded to Google Drive for safekeeping. 🛠️ How to set up Telegram Bot Create via BotFather Connect it to the Telegram Trigger node OpenAI Use your OpenAI API key Connect the Embeddings and Chat Model nodes (GPT-3.5/4) Ensure both embedding and querying use the same Embedding node Google Drive Set up credentials in n8n for your Google account Connect the “Backup to Google Drive” node PDF Ingestion Use the “Upload your PDF here” trigger Connect it to the loader, embedder, and backup flow ✅ Requirements Telegram bot token OpenAI API key (GPT + Embeddings) n8n instance (self-hosted or cloud) Google Drive integration PDF files to upload 🧩 How to customize the workflow | Feature | How to Customize | |-------------------------------|-------------------------------------------------------------------| | Auto-ingest from folders | Add Google Drive/Dropbox watchers for new PDFs | | Add file upload via Telegram | Extend Telegram bot to receive PDFs and run the embedding flow | | Track user questions | Log Telegram usernames and questions to a database | | Summarize documents | Add summarization step on upload | | Add Markdown or HTML support | Format replies for better Telegram rendering | Built with 💬 Telegram + 📄 PDF + 🧠 OpenAI Embeddings + ☁️ Google Drive + ⚡ n8n

This AI receptionist handles restaurant bookings and delivery orders with Vapi, Telegram, and Airtable Who’s it for This n8n template is built for restaurants that want to automate table bookings and delivery or takeaway orders using an AI receptionist. It’s suitable for small to mid-sized restaurants that receive bookings and orders via voice calls or Telegram and want a structured, reliable backend without manual handling. How it works The workflow powers an AI receptionist that operates through Vapi (voice) and Telegram (chat). For table bookings, it collects party size and preferred time, checks table availability within the requested time range, and returns available options or a “no availability” response. For orders, the menu is fetched from Airtable, items are validated, prices are calculated, and order details are collected. Delivery addresses are validated and checked against supported areas. If delivery is unavailable, the system automatically offers takeaway. All confirmed bookings and orders are saved to Airtable. How to set up Download JSON flows from the Dropbox folder, copy Airtable base with template tables to your account. Get Airtable, OpenAI, Telegram Bot, Google Maps API credentials. Set up credentials and test. How to customize the workflow You can plug a VAPI assistant. Copy the prompt from the AI agent and paste it into VAPI system prompt section. Also add MCP tool and call it restaurant tool. You can adjust booking rules, table capacity logic, menu structure, restaurant location, delivery zones, pricing calculations, and message wording to match your restaurant’s operations.

Turn your favorite podcast episodes into engaging social media content automatically. This workflow fetches new episodes from an RSS feed, transcribes the audio using OpenAI Whisper, generates a concise summary using GPT-4o, and drafts a tweet. It then sends the draft to Slack for your review before posting it to X (Twitter). Who is this for Content creators, social media managers, and podcast enthusiasts who want to share insights without manually listening to and typing out every episode. Key Features Large File Support:** Includes a custom logic to download audio in chunks, ensuring stability even with long episodes (preventing timeouts). Human-in-the-Loop:** Nothing gets posted without your approval. You can review the AI-generated draft in Slack before it goes live. High-Quality AI:** Uses OpenAI's Whisper for accurate transcription and GPT-4o for intelligent summarization. How it works Monitor: Checks the Podcast RSS feed daily for new episodes. Process: Downloads the audio (handling large files via chunking) and transcribes it. Draft: AI summarizes the transcript into bullet points and formats it for X (Twitter). Approve: Sends the draft to a Slack channel. Publish: Once approved by you, it posts the tweet to your X account. Requirements OpenAI API Key Slack Account & App (Bot Token) X (Twitter) Developer Account (OAuth2) Setup instructions RSS Feed: The template defaults to "TED Talks Daily" for demonstration. Open the [Step 1] RSS node and replace the URL with your target podcast. Connect Credentials: Set up your credentials for OpenAI, Slack, and X (Twitter) in the respective nodes. Slack Channel: In the [Step 12] Slack node, select the Channel ID where you want to receive the approval request.

Automate Bug Reports: GitHub Issues → AI Analysis → Jira Tickets with Slack & Discord Alerts Automatically convert GitHub issues into analyzed Jira tickets with AI-powered severity detection, developer assignment, and instant team alerts. Overview This workflow captures GitHub issues in real-time, analyzes them with GPT-4o for severity and categorization, creates enriched Jira tickets, assigns the right developers, and notifies your team across Slack and Discord—all automatically. Features AI-Powered Triage**: GPT-4o analyzes bug severity, category, root cause, and generates reproduction steps Smart Assignment**: Automatically assigns developers based on mentioned files and issue context Two-Way Sync**: Posts Jira ticket links back to GitHub issues Multi-Channel Alerts**: Rich notifications in Slack and Discord with action buttons Time Savings**: Eliminates 15-30 minutes of manual triage per bug Customizable Routing**: Easy developer mapping and priority rules What Gets Created Jira Ticket: Original GitHub issue details with reporter info AI severity assessment and categorization Reproduction steps and root cause analysis Estimated completion time Automatic labeling and priority assignment GitHub Comment: Jira ticket link AI analysis summary Assigned developer and estimated time Team Notifications: Severity badges and quick-access buttons Developer assignment and root cause summary Color-coded priority indicators Use Cases Development teams managing 10+ bugs per week Open source projects handling community reports DevOps teams tracking infrastructure issues QA teams coordinating with developers Product teams monitoring user-reported bugs Setup Requirements Required: GitHub repository with admin access Jira Software workspace OpenAI API key (GPT-4o access) Slack workspace OR Discord server Customization Needed: Update developer email mappings in "Parse GPT Response & Map Data" node Replace YOUR_JIRA_PROJECT_KEY with your project key Update Slack channel name (default: dev-alerts) Replace YOUR_DISCORD_WEBHOOK_URL with your webhook Change your-company.atlassian.net to your Jira URL Setup Time: 15-20 minutes Configuration Steps Import workflow JSON into n8n Add credentials: GitHub OAuth2, Jira API, OpenAI API, Slack, Discord Configure GitHub webhook in repository settings Customize developer mappings and project settings Test with sample GitHub issue Activate workflow Expected Results 90% faster bug triage (20 min → 2 min per issue) 100% consistency in bug analysis Zero missed notifications Better developer allocation Improved bug documentation Tags GitHub, Jira, AI, GPT-4, Bug Tracking, DevOps, Automation, Slack, Discord, Issue Management, Development, Project Management, OpenAI, Webhook, Team Collaboration

📊 Description Automate your YouTube research workflow by extracting audio from any video, transcribing it with Whisper AI, and generating structured GEO (Goal–Execution–Outcome) summaries using GPT-4o-mini. 🎥🤖 This template transforms unstructured video content into actionable, searchable insights that are automatically stored in Notion with rich metadata. It’s ideal for creators, educators, analysts, and knowledge workers who want to convert long videos into concise, high-quality summaries without manual effort. Perfect for content indexing, research automation, and knowledge-base enrichment. 📚✨ 🔁 What This Template Does • Triggers on a schedule to continuously process new YouTube videos. ⏰ • Fetches video metadata (title, description, thumbnails, published date) via the YouTube API. 🎥 • Downloads audio using RapidAPI and prepares it for transcription. 🎧 • Transcribes audio into text using OpenAI Whisper. 📝 • Skips invalid entries when no transcript is generated. 🚫 • Merges the transcript with metadata for richer AI context. 🔗 • Uses GPT-4o-mini to generate Goal, Execution, Outcome, and Keywords via structured JSON. 🤖📊 • Parses the AI-generated JSON into Notion-friendly formats. 🔍 • Creates a Notion page with GEO sections, keywords, and video metadata. 📄🏷️ • Produces a fully searchable knowledge record for every processed video. 📚✨ ⭐ Key Benefits ✅ Converts long YouTube videos into concise, structured knowledge ✅ AI-powered GEO summaries improve comprehension and recall ✅ Zero manual transcription or note-taking — 100% automated ✅ Seamless Notion integration creates a powerful video knowledge base ✅ Works on autopilot with scheduled triggers ✅ Saves hours for educators, researchers, analysts, and content teams 🧩 Features YouTube API integration for metadata retrieval RapidAPI audio downloader OpenAI Whisper transcription GPT-4o-mini structured analysis through LangChain Memory buffer + structured JSON parser for consistent results Automatic Notion page creation Fail-safe transcript validation (IF node) Metadata + transcript merging for richer AI context GEO (Goal–Execution–Outcome) summarization workflow 🔐 Requirements YouTube OAuth2 credentials OpenAI API key (Whisper + GPT-4o-mini) Notion API integration token + database ID RapidAPI key for YouTube audio downloading n8n with LangChain nodes enabled 🎯 Target Audience YouTubers and content creators archiving their content Researchers and educators summarizing long videos Knowledge managers building searchable Notion databases Automation teams creating video intelligence workflows 🛠️ Step-by-Step Setup Instructions Add YouTube OAuth2, OpenAI, Notion, and RapidAPI credentials. 🔑 Replace the placeholder RapidAPI key in the “Get YouTube Audio” node. ⚙️ Update the Notion database ID where summaries should be stored. 📄 Configure the Schedule Trigger interval based on your needs. ⏰ Replace the hardcoded video ID (if present) with dynamic input or playlist logic. 🔗 Test with a sample video to verify transcription + AI + Notion output. ▶️ Enable the workflow to run automatically. 🚀