Workflow Templates

What this workflow does Front-door chat orchestrator that delegates calendar requests to a separate Sub-Agent workflow which holds Google Calendar tools (Get, Create, Delete). Keeps the agent persona and memory in the Parent for clean separation of concerns. Pipeline: Chat Trigger → Parent Agent ("Albert") → sub_agent_cal (Execute Workflow Tool) → Child Sub-Agent → Google Calendar Category: Productivity / Calendar / Agentic\ Time to set up: ~10--15 minutes\ Difficulty: Intermediate\ Cost: Mostly free (n8n CE; OpenAI + Google Calendar usage as configured) * What you'll need n8n with chat trigger enabled. OpenAI credentials. The companion template: Agentic Google Calendar Assistant --- Sub-Agent (Calendar Tools). After importing both, open this Parent and re-select the Sub-Agent in the toolWorkflow node. * Set up steps Import this Parent workflow. Import the Sub-Agent workflow (Template B). In the Parent, open sub_agent_cal (Tool → Workflow) and select the imported Sub-Agent workflow. Ensure the input mapping passes: chatInput → text sessionId → sessionid Add your OpenAI credential to the OpenAI Chat Model node. Activate the Parent workflow. * Testing "Create a meeting tomorrow 3--4pm called 'Product Sync'" → Sub-Agent should create the event and the agent should confirm. "What's on my calendar this week?" → Lists events. "Delete my 'Dentist' appointment on Thursday" → Finds and deletes the event.

Done-For-You Social Media Trend Tracker for Content Creators | Instant AI Video Ideas 💥 What It Does This pre-built n8n workflow is your ultimate shortcut to viral content. It automatically scouts the web for trending social media topics and generates hyper-relevant video ideas, complete with engaging hooks and calls to action, directly from the latest trends. No more endless scrolling or brainstorming sessions – just plug in and receive daily, actionable content inspiration delivered straight to your Discord channel. Stop missing out on viral trends and start creating content that captivates your audience from day one, effortlessly. This fully installed automation transforms your content strategy, giving you an unfair advantage in the crowded digital landscape. ⚙️ Key Features ⚡ Instant deployment: Pre-configured n8n workflow, ready to run in minutes. 🧠 AI-powered content engine: Generates viral video ideas with hooks & CTAs (powered by OpenAI). 📈 Automated trend discovery: Daily insights from top social platforms without manual research. 💬 Discord integration: Delivers actionable ideas directly to your team or private channel. 🚀 Zero-setup solution: No coding, no complex API configurations required. 😩 Pain Points Solved Sick of endless trend research and content ideation headaches? Tired of missing out on viral opportunities and falling behind competitors? Frustrated with complex API setups and coding your own automations? Struggling to consistently produce fresh, engaging content that performs? Wasting valuable time on manual content planning and brainstorming? 📦 What’s Included Fully configured n8n workflow file (.json) Step-by-step installation & connection guide Pre-written AI prompt for optimal video idea generation Dedicated support to ensure seamless launch 🚀 Call to Action Get your viral content ideas delivered daily. No setup. No stress. 🏷️ Optimized Tags done for you system, ai automation, n8n workflow, social media trends, content ideas, viral video, tiktok content, youtube shorts, instagram reels, discord bot, pre built workflow, instant download, marketing automation

What It Does This workflow lets users create Google Calendar events through natural chat messages — no forms, no clicking around, just type like you're talking to a friend. For example, you can say: “Lunch with John tomorrow at 12:30” and it’ll auto-create a calendar event with the correct title, time, and duration. How It Works Trigger: Chat Message Received The flow starts with a chat interface node (When chat message received) that listens for incoming user messages like: “Book dentist next Wed 10am” “Schedule Zoom call with Jane Friday 3–4pm” AI Agent with Scheduling Instructions The message is handed off to a Langchain-powered AI Agent that: Parses the message Resolves relative time (like "next Tuesday") into actual ISO timestamps Generates a title (summary) if not provided by the user Ensures all required fields are correctly filled Handles vague messages by asking a single clarifying question LLM (OpenAI) The agent is powered by gpt-4o-mini (or your preferred OpenAI model). You can customize this or swap it out. Google Calendar Integration Once the AI agent has structured the event details, it uses the Google Calendar Tool Node to create the event via your connected Google account. (Optional) A response node (Respond to Chat) is included (but currently disabled) — you can enable it to send a confirmation message back to the user like: “📅 Booked: Lunch with John on Aug 30 at 12:30 PM Asia/Manila.” Requirements To make this workflow functional, you need to connect: 🔐 Google Calendar OAuth2 credentials Add your Google account under Credentials > Google Calendar OAuth2 API. 🧠 OpenAI credentials Provide your OpenAI API key (used for message interpretation and slot filling). Customization Ideas Add email collection to invite attendees Expand to support recurring events Add error handling or fallback if date parsing fails Connect to Slack or Telegram for real-time event booking Important Note on Credentials This template does not include any personal API keys or credential tokens. You’ll need to connect your own Google and OpenAI credentials after import.

📊 Description Automate the creation of production-ready n8n workflows using AI 🤖. This template receives a plain-text automation idea via webhook, processes it with Azure OpenAI, and instantly generates a fully valid, import-ready n8n workflow JSON file. The automation sanitizes the prompt, enforces strict JSON validation, and returns a downloadable workflow file in seconds. Perfect for building scalable automation tools, SaaS workflow builders, or internal AI workflow generators ⏱️📤. What This Template Does 📥 Receives automation idea via Webhook – Accepts a POST request containing a workflow prompt. 🧹 Cleans and normalizes input – Formats and sanitizes the prompt for consistent AI processing. 🤖 Generates workflow using Azure OpenAI – AI Agent creates a complete, import-ready n8n JSON workflow. ✅ Parses and validates AI output – Ensures the returned JSON is valid and error-free. 📄 Converts JSON into a downloadable file – Wraps structured output into a binary .json file. 📤 Returns workflow file to caller – Sends the ready-to-import workflow back as an HTTP response. Key Benefits ✅ Instantly generate n8n workflows from plain English prompts ✅ Eliminates manual workflow building ✅ Ensures valid, import-ready JSON every time ✅ Perfect for SaaS workflow builders and automation marketplaces ✅ Fully automated AI → validation → export pipeline ✅ Scalable backend for AI-powered automation platforms Features Webhook trigger for dynamic workflow requests Azure OpenAI GPT model integration for intelligent workflow generation AI Agent with strict JSON enforcement rules Automatic JSON parsing and validation logic Binary file conversion for direct workflow download Error handling for invalid AI responses Fully connected, import-ready n8n workflow output Requirements Azure OpenAI credentials (azureOpenAiApi) Active Azure deployment (e.g., gpt-4o-mini) n8n instance with webhook access enabled Target Audience 🚀 SaaS founders building AI automation tools 🤖 Automation agencies creating workflow marketplaces 🛠️ n8n power users building internal workflow generators 💡 Developers building AI-powered no-code platforms

📊 Description Automate the optimization of your n8n workflows using AI-powered analysis and restructuring 🤖. This workflow receives any existing n8n JSON via webhook, analyzes it using Azure OpenAI, and returns a fully optimized, import-ready workflow file. It improves execution speed, reduces redundant nodes, enhances API efficiency, and ensures structural cleanliness — all while preserving the original logic. Perfect for automation builders who want cleaner, faster, and production-ready workflows instantly. 🚀 What This Template Does 📥 Receives an n8n workflow JSON via a secure POST webhook. 🔍 Extracts and validates the workflow body to ensure proper structure. 🤖 Sends the workflow to Azure OpenAI for performance and structural optimization. 🧹 Strips markdown, parses, and validates the AI-returned JSON. 📄 Converts the optimized workflow into a downloadable .json file. 📤 Returns the optimized workflow file directly to the caller. Key Benefits ✅ Automatically optimizes workflow performance and execution speed ✅ Reduces redundant nodes and unnecessary API calls ✅ Ensures clean, structured, import-ready n8n JSON ✅ Preserves original business logic and integrations ✅ Eliminates manual workflow refactoring ✅ Adds structural clarity and best-practice improvements Features Webhook trigger for receiving workflow JSON Azure OpenAI integration (GPT-4o-mini) for AI-driven optimization Automated JSON parsing and structural validation Markdown stripping and error-safe parsing logic Binary file conversion for direct n8n re-import Built-in validation to prevent broken or orphaned workflows Production-safe response handling Requirements Azure OpenAI credentials (azureOpenAiApi) Active Azure deployment (e.g., gpt-4o-mini) n8n instance with webhook access enabled Target Audience Automation agencies optimizing client workflows n8n template creators selling premium workflows SaaS founders improving internal automation performance Advanced n8n users maintaining large workflow libraries

AI-Driven daily construction report (DCR) standardization What This Workflow Does Standardize Daily Construction Reports (DCR) with AI by capturing raw site inputs via chat and automatically generating structured Work Performance Data. This workflow enables you to: Capture field reports through a Chat Interface Validate inputs using AI Guardrails (anti-jailbreak protection) Standardize DCR content with OpenAI Distribute structured technical reports via Gmail Log Work Performance Data into Google Sheets Ensure traceability and governance-ready documentation How to Use This Template Use this template to automate Daily Construction Report standardization and logging by combining: Chat Trigger** → Collect raw field inputs in real time OpenAI Guardrails** → Validate and block unsafe or adversarial submissions OpenAI (GPT model)** → Transform raw notes into structured DCR format Google Sheets** → Store structured Work Performance Data Gmail** → Notify stakeholders and distribute reports Action-Oriented Overview You can: Capture raw DCR notes directly from site personnel via chat** Validate input integrity using AI guardrails with jailbreak detection** Automatically block and alert stakeholders in case of suspicious input** Standardize informal notes into a structured DCR template including:** Project identification Field team Activities performed Working hours Weather conditions Occurrences and issues Materials and equipment Physical progress Responsible person Log the structured DCR into Google Sheets as Work Performance Data** Send the standardized report automatically via Gmail** Provide immediate confirmation back to the field user** What You Achieve With this workflow, you can: Do AI-powered DCR standardization with OpenAI Do secure field data collection with AI guardrails Do automated Work Performance Data logging with Google Sheets Do real-time stakeholder communication with Gmail Do governance-ready execution documentation aligned with PMBOK® Ideal For Construction site managers Field engineers Project control teams PMO environments Organizations aligned with PMI / PMBOK® execution practices Companies implementing digital transformation in site reporting This template operationalizes Manage Project Execution by transforming raw field notes into structured, standardized Work Performance Data (WPD). Categories AI** Project Management** Alignment with PMI – PMBOK® 8 Focus Area: Executing Process: Manage Project Execution Artifact Generated: Work Performance Data (WPD)

AI-Driven construction execution monitoring What This Workflow Does Monitor construction execution with AI by analyzing site photos from Google Drive and automatically generating structured Work Performance Data. This workflow enables you to: Monitor construction progress with Google Drive and OpenAI Generate engineering analysis reports with AI Distribute structured technical reports via Gmail Log Work Performance Data into Google Sheets Archive processed evidence in Google Drive for audit traceability How to Use This Template Use this template to automate construction inspection and execution monitoring by combining: Google Drive** → Retrieve and manage site photos OpenAI (GPT model)** → Perform structured engineering analysis Gmail** → Send technical reports to stakeholders Google Sheets** → Store structured Work Performance Data Google Drive (Move & Share)** → Archive and control processed files Action-Oriented Overview You can: Retrieve construction photos with Google Drive and filter only image files** Analyze construction execution with OpenAI using a structured engineering prompt** Generate a technical report covering:** Stage of work Execution quality Risks and non-conformities Safety conditions Technical recommendations Send the structured report via Gmail with the original image attached** Log execution data into Google Sheets as Work Performance Data** Move processed images to an archive folder in Google Drive** What You Achieve With this workflow, you can: Do AI-powered construction monitoring with Google Drive and OpenAI Do digital quality and safety verification using image analysis Do automated stakeholder reporting with Gmail Do structured execution logging with Google Sheets Do governance-ready documentation and traceability with Drive archiving Ideal For Construction managers Project control teams PMO environments Engineering consultants Organizations aligned with PMI / PMBOK® execution practices This template operationalizes Manage Project Execution by transforming raw site images into structured, traceable Work Performance Data. Categories AI** Project Management** Alignment with PMI – PMBOK® 8 Focus Area: Executing Process: Manage Project Execution Artifact Generated: Work Performance Data (WPD)

CPO Agent with Product Team Description Streamline product development with an AI-powered Chief Product Officer (CPO) agent orchestrating specialized product team members for comprehensive product strategy and execution. Overview This n8n workflow creates a comprehensive product development department using AI agents. The CPO agent analyzes product opportunities and delegates tasks to specialized agents for product management, UX design, user research, analytics, documentation, and strategic planning. Features Strategic CPO agent using OpenAI O3 for complex product strategy and decision-making Six specialized product agents powered by GPT-4.1-mini for efficient execution Complete product lifecycle coverage from ideation to launch Automated user research and persona development UX/UI design specifications and wireframing Product analytics and KPI tracking Technical documentation and API specifications Team Structure CPO Agent**: Product vision and strategy coordination (O3 model) Product Manager**: Roadmaps, feature specifications, user stories, planning UX/UI Designer**: User flows, wireframes, interface design, usability User Research Specialist**: Research plans, personas, market analysis, insights Product Analytics Specialist**: Metrics, KPIs, A/B testing, data analysis Technical Writer**: Product documentation, API docs, user guides Product Strategy Analyst**: Competitive analysis, market positioning, GTM strategy How to Use Import the workflow into your n8n instance Configure OpenAI API credentials for all chat models Deploy the webhook for chat interactions Send product requests via chat (e.g., "Design a new mobile app feature for user onboarding") The CPO will analyze and delegate to appropriate specialists Receive comprehensive product deliverables and strategic insights Use Cases Feature Development**: Concept → Research → Design → Specifications → Metrics Product Launch**: Strategy → Documentation → Analytics → Go-to-market planning User Experience Optimization**: Research → Personas → User flows → Testing → Iteration Competitive Analysis**: Market research → Positioning → Differentiation strategies Product Roadmapping**: Vision → Priorities → Timeline → Resource planning Documentation Suite**: User guides → API documentation → Technical specifications Analytics Implementation**: KPI definition → Tracking setup → Performance analysis Market Research**: Customer interviews → Persona development → Requirements gathering Requirements n8n instance with LangChain nodes OpenAI API access (O3 for CPO, GPT-4.1-mini for specialists) Webhook capability for chat interactions Optional: Integration with product management tools (Jira, Figma, etc.) Cost Optimization O3 model used only for strategic CPO decisions GPT-4.1-mini provides 90% cost reduction for specialist tasks Parallel processing enables simultaneous agent execution Template library leverages proven product frameworks Integration Options Connect to product management tools (Jira, Asana, Linear) Integrate with design platforms (Figma, Sketch, Adobe XD) Link to analytics tools (Mixpanel, Amplitude, Google Analytics) Export to documentation platforms (Notion, Confluence) Performance Metrics Feature adoption rates and user engagement Product-market fit indicators User satisfaction and NPS scores Development velocity and cycle times Documentation completeness and clarity Contact & Resources Website**: nofluff.online YouTube**: @YaronBeen LinkedIn**: Yaron Been Tags #ProductManagement #UXDesign #UserResearch #ProductStrategy #ProductOps #ProductAnalytics #TechnicalWriting #ProductDevelopment #FeatureDesign #ProductAI #n8n #OpenAI #MultiAgentSystem #ProductTech #ProductLeadership #Innovation

Transform messy receipt photos into a structured, searchable expense database in seconds. This workflow automates the entire journey from a WhatsApp message to a live Google Sheets entry by combining WATI for communication, OpenAI Vision for extraction, and automated reporting logic. 🎯 What This Workflow Does Turns a simple WhatsApp photo or text command into a professional expense management system: 📝 Captures Receipt Assets Receives an image or text command via WATI Trigger from the user's phone. 🚦 Smart Message Routing A Switch node detects the input type: Image: Routes to the AI scanning branch for receipt processing. Text ("report"): Routes to the reporting branch to generate monthly summaries. 👁️ Vision AI Analysis OpenAI GPT-4o "looks" at the receipt image to extract the merchant name, total amount, currency, and date. ☁️ Base64 Data Processing A specialized Code node uses getBinaryDataBuffer to convert receipt images into a high-speed data URL, ensuring OpenAI always receives the actual image instead of a placeholder. 📊 Automated Logging & Reporting Logging: Appends validated data to Google Sheets with automated month categorization. Reporting: Aggregates totals by category and sends a visual dashboard back to WhatsApp. ✨ Key Features Zero-Manual Entry:** AI extracts 100% of the data from the photo, including currency codes and spending categories. Visual Progress Reports:** The workflow generates formatted WhatsApp reports with visual percentage bars (███░░). Automatic Month Tracking:** Uses Luxon date expressions to derive "Month" names automatically from receipt dates. Dual-Mode Trigger:** Handles both new expense logging and historical data retrieval within a single WhatsApp chat. Robust Error Handling:** Includes logic to catch "filesystem" errors and ensure binary data is properly converted for the AI. 💼 Perfect For Small Business Owners:** Tracking business expenses on the go without saving paper receipts. Freelancers:** Quickly logging billable expenses for client reimbursement. Personal Finance Users:** Maintaining a real-time budget directly from their primary messaging app. Teams:** Allowing multiple employees to "WhatsApp" their receipts to a central company sheet. 🔧 What You'll Need Required Integrations WATI** – To receive WhatsApp messages and send automated replies. OpenAI API** – GPT-4o Vision for image analysis and structured JSON extraction. Google Sheets** – To host the master expense database. Optional Customizations Currency Conversion:** Add a node to convert all foreign expenses into your local currency automatically. Budget Alerts:** Set a threshold to notify you via WhatsApp if your monthly total exceeds a specific limit. 🚀 Quick Start Import Template – Copy the JSON and import it into your n8n instance. Set Credentials – Connect your WATI, OpenAI, and Google Sheets accounts. Configure Sheet – Ensure your Google Sheet has headers for: timestamp phone vendor amount currency date category month Test Scanning – Send a photo of a receipt to your WATI number. Request Report – Type report in WhatsApp to see your spending breakdown. 🎨 Customization Options Category Mapping:** Modify the OpenAI prompt to use categories specific to your tax filing needs (e.g., "Office Supplies," "Travel"). Filtering Logic:** Adjust the Build Monthly Report code to show weekly instead of monthly summaries. Multi-User Support:** The workflow is already built to filter data based on the sender's phone number. 📈 Expected Results 90% reduction in time spent on monthly expense reconciliation. 100% accuracy in date and amount extraction using GPT-4o Vision. Real-time visibility into spending habits without ever opening a spreadsheet. Zero lost receipts by logging them the moment they are received. 🏆 Use Cases Business Travel A consultant snaps photos of taxi and meal receipts during a trip; by the time they land, their expense sheet is already populated and categorized. Personal Budgeting A user types report at the end of the week to instantly see what percentage of their budget went to "Food" vs "Entertainment". Subscription Management Upload screenshots of digital invoices to track monthly software costs and recurring bills. 💡 Pro Tips Clear Lighting:** For best AI extraction, ensure the receipt text is clear and not folded. Keyword Commands:** You can add more keywords like summary or last week by expanding the Route Message switch node. JSON Validation:** The Parse & Validate node ensures that even if the AI adds extra text, only the clean data is saved. Ready to automate your expenses? Import this template and connect your WATI number to start scanning receipts today! `

📘 Description This workflow acts as an AI Multi-Agent Architecture Advisor for n8n. It receives a problem statement via webhook, uses Azure OpenAI (gpt-4o-mini) to decide whether the problem needs a multi-agent design or a simple workflow, then returns a styled HTML report showing the decision, recommended agents (if any), and the suggested step flow. ⚙️ Step-by-Step Flow Receive Problem Description via POST (Webhook) Accepts a POST payload containing a description field. Extract Request Body (Code) Strips the wrapper and outputs only the body JSON to simplify downstream prompts. Multi-Agent Architecture Decision Agent (AI Agent) Analyzes the problem description and outputs one of: Decision: Multi-Agent Required + agent definitions + workflow steps Decision: Not Required + minimal simplified workflow nodes Parse Decision, Agents & Steps (Code) Extracts three structured fields from the AI output: decision agents[] (name, purpose, node, reason) workflow_flow[] (ordered steps) Build HTML Architecture Report (Code) Renders a clean card-based HTML dashboard: Decision badge (multi vs simple) Agent cards (if present) Workflow flow chips (steps) Return HTML Report to Caller (Respond to Webhook) Returns the HTML report directly as the webhook response. 🧩 Prerequisites • Azure OpenAI credential with an active gpt-4o-mini deployment • n8n webhook endpoint exposed to the caller (or via tunnel) 💡 Key Benefits ✔ Fast “multi-agent vs simple” decisioning ✔ Outputs an actionable architecture, not generic advice ✔ HTML report is ready to embed in internal tools (Base44/UI) ✔ Structured parsing makes it easy to store or extend later 👥 Perfect For Automation agencies doing solution design calls Teams standardizing how they choose agent-based workflows Internal tooling that needs instant architecture recommendations

This workflow solves a critical problem in AI chat implementations: handling multiple rapid messages naturally without creating processing bottlenecks. Unlike traditional approaches where every user waits in the same queue, our solution implements intelligent conditional buffering that allows each conversation to flow independently. Key Features: Aggregates rapid user messages (like when someone types multiple lines quickly) into single context Only the first message in a burst waits - subsequent messages skip the queue entirely Each user session operates independently with isolated Redis queues Reduces LLM API calls by 45% through intelligent message batching Maintains conversation memory for contextual responses Perfect for: Customer service bots, AI assistants, support systems, and any chat application where users naturally send multiple messages in quick succession. The workflow scales linearly with users, handling hundreds of concurrent conversations without performance degradation. Some Use Cases: Customer support systems handling multiple concurrent conversations AI assistants that need to understand complete user thoughts before responding Educational chatbots where students ask multi-part questions Sales bots that need to capture complete customer inquiries Internal company AI agents processing complex employee requests Any scenario where users naturally communicate in message bursts Why This Template? Most chat buffer implementations force all users to wait in a single queue, creating exponential delays as usage scales. This template revolutionizes the approach by making only the first message wait while subsequent messages flow through immediately. The result? Natural conversations that scale effortlessly from one to hundreds of users without compromising response quality or speed. Prerequisites n8n instance (v1.0.0 or higher) Redis database connection OpenAI API key (or alternative LLM provider) Basic understanding of webhook configuration Tags ai-chat, redis, buffer, scalable, conversation, langchain, openai, message-aggregation, customer-service, chatbot

📄 Description This workflow automates the extraction of structured invoice data from PDF files sent via Telegram and stores it in Airtable. It leverages GPT-4o for intelligent parsing and includes conversational memory for a seamless user experience. Designed for businesses and freelancers who receive invoices digitally and want to streamline their record-keeping. ⚙️ How It Works Telegram Trigger – Listens for incoming messages and PDF attachments. Switch Node – Filters messages to ensure only PDFs are processed. Extract from File – Parses the PDF content for text extraction. Edit Fields – Prepares the extracted data for AI processing. AI Agent (GPT-4o) – Orchestrates the workflow, prompts the user for missing info, and extracts structured data. Simple Memory – Maintains conversational context across sessions. Create Invoice (Airtable Tool) – Creates a new invoice record in Airtable. Create Line Item (Airtable Tool) – Adds individual line items linked to the invoice. Telegram Response – Sends confirmation back to the user. 🔐 Required Credentials To run this workflow successfully, you’ll need: Telegram Bot Token** (via @BotFather) OpenAI API Key** (with GPT-4o access) Airtable API Key** and access to: Base: Invoice Tracker Proper Tables: Invoices and Line Items 🧰 Airtable Structure Invoices Table Fields: Invoice Number Date Supplier Supplier Address Tax ID PO Number Due Date Receiver Name Receiver Address Delivery Date Total Tax Total Amount Line Items Table Fields: Product Code Description Unit Price Quantity Unit Type Sub Total Invoice (linked) 🧠 Features AI-powered invoice parsing PDF text extraction Airtable record creation with relational linking Telegram-based user interaction Conversational memory Error handling and data validation