Workflow Templates

🚀 Overview This modern n8n workflow implements a multi-agent trading engine that orchestrates valuation, sentiment, fundamentals, technicals, and macro analyses to generate a single portfolio action with built-in risk controls. It integrates Telegram for live commands, fetches market data, fans out to expert LLM agents, applies position limits via a Risk Manager, executes orders, logs to Notion, and sends a summary back to Telegram. 🔧 What It Does Telegram Trigger** listens for ticker commands and context inputs 📲 Market Data Node** fetches live prices and exchange rates from an API (no hardcoded keys) 🔗 LLM Agents** run parallel analyses: valuation, sentiment, macro, fundamentals, technicals 🌐 Risk Manager** enforces max position sizes, stop-loss limits, and confidence thresholds ⚖️ Portfolio Manager** aggregates signals into a final BUY/SELL/HOLD decision with allocation % 📊 Execute Order** sends trade requests via HTTP Request 🔒 Log to Notion** writes a full audit trail for compliance 📓 Telegram Output** posts a concise report with signals, risk notes, and final decision 📤 💡 Why It’s Useful This template illustrates a modular “investment committee” architecture that is easy to extend, swap agents, and maintain. It follows n8n’s best practices for template submissions: sticky-note documentation, placeholder credentials, markdown descriptions, and clear H2 headings. 🔑 Prerequisites Telegram Bot credentials configured in n8n Exchange or data API credentials stored as n8n Credentials (no inline keys) OpenAI (or other LLM) API credential Notion integration credentials 🛠️ How to Use Import the JSON into n8n and open the canvas. Read each Sticky Note for node-by-node setup tips and rate-limit guidance 🗒️ Configure credentials via the n8n Credentials Manager 🔐 Test each branch (data fetch, agents, risk logic) in isolation before enabling order execution ✅ 📐 Architecture Layers Trigger**: Telegram Trigger → Data**: HTTP Request → Analysis**: Parallel LLM Agents → Risk**: Risk Manager → Decision**: Portfolio Manager → Action**: Execute Order, Log to Notion, Send Telegram summary 🔒 Security & Maintenance All API keys are stored securely as credentials. Sticky Notes document required scopes, retry strategies, and error-handling paths to ensure observability and safe testing. Enjoy building and customizing your own AI-powered hedge-fund workflow!

n8n Graphical Input Template - AI Agent Interface A beautiful, ready-to-use HTML interface for n8n workflows that allows your users to interact with AI agents through a clean web UI. No frontend skills required! 🎯 Why Use This Template? No Frontend Skills Required**: Get a professional interface without writing React, Vue, or complex JavaScript Real-Time AI Responses**: Display AI responses directly in the interface with loading animations User-Friendly**: Your clients get a beautiful UI instead of dealing with APIs or command-line tools Plug & Play**: Just paste the code in an n8n Code node and connect your AI agents Fully Customizable**: Easy to modify colors, add more agents, or change the layout Dark/Light Mode**: Built-in theme toggle with localStorage persistence 🚀 When to Use This? Perfect for: AI Agent Interactions**: Let users chat with different specialized AI agents (Database, Web Search, RAG) Customer Support**: Route customer questions to appropriate AI assistants Data Collection**: Gather information from clients with instant AI-powered responses Customer Portals**: Create simple interfaces for customers to interact with your AI automations Internal Tools**: Build quick admin panels with AI assistance 📦 What's Included? ✅ Text Input Area: Large textarea for user messages ✅ Send Button: Main action button with smooth animations ✅ 4 Specialized Agent Buttons: Pre-configured for General, Database, Web, and RAG agents ✅ AI Response Display: Beautiful response area with agent badges and loading states ✅ Project Guide Modal: Built-in documentation for your users ✅ Theme Toggle: Dark/Light mode with localStorage persistence ✅ Responsive Design: Works perfectly on desktop, tablet, and mobile ✅ Font Awesome Icons: Beautiful icons throughout the interface ✅ Error Handling: Graceful error messages if something goes wrong 🛠️ How to Use Part 1: Display the Interface Create a 3-node workflow to show the UI: Webhook (GET) → Code Node → Respond to Webhook Configuration: Webhook Node (GET): Method: GET Path: /your-interface (e.g., /ai-chat) Authentication: Optional Code Node: Copy the entire content of main.js Paste it into the Code field Respond to Webhook: Respond With: First incoming item Response Data Source: Binary Binary Property: data Part 2: Process AI Requests Create a separate workflow to handle AI processing: Webhook (POST) → Switch → AI Agents → Code Node → Respond to Webhook Configuration: Webhook Node (POST): Method: POST Path: /webhook-endpoint Response Mode: "Respond to Webhook" Switch Node - Route by agent type: Rule 1: {{ $json.body.agent_type }} equals general Rule 2: {{ $json.body.agent_type }} equals database Rule 3: {{ $json.body.agent_type }} equals web Rule 4: {{ $json.body.agent_type }} equals rag AI Agent Nodes (4 nodes, one per agent type): Connect one AI Agent to each Switch output Configure with OpenAI, Anthropic, or local LLM Add tools, memory, system prompts as needed Code Node - Format the response: const webhookData = $('Webhook').first().json.body; const aiResponse = $input.first().json; return [{ json: { response: aiResponse.output || aiResponse.text || aiResponse.response, agent_type: webhookData.agent_type, user_message: webhookData.message, timestamp: new Date().toISOString() } }]; Respond to Webhook - Send back the formatted response 🔧 What to Update In main.js Line 847 - Update webhook URL to match your n8n path: const WEBHOOK_URL = '/webhook/webhook-endpoint'; Line 20 - Customize project name: const projectName = "AI Assistant Hub"; Lines 34-56 - Change colors (optional): :root { --primary: #6366f1; /* Main accent color */ --primary-hover: #4f46e5; /* Hover state */ --background: #ffffff; /* Background */ } 📊 How It Works User visits /your-interface ↓ Sees the chat interface ↓ Types message + clicks agent button ↓ POST to /webhook/webhook-endpoint { "message": "Find users in database", "agent_type": "database", "timestamp": "2025-10-19T..." } ↓ Switch routes to Database AI Agent ↓ AI Agent processes with tools/memory ↓ Code Node formats response ↓ Returns { "response": "Found 10 users..." } ↓ Interface displays response with badge + animation 🎨 Customization Guide Add More Agents Copy an agent card (lines ~700-730) and modify: Custom AI Agent Specialized in your custom task. Then add CSS for the new agent type: .agent-card.custom-agent::before { background: #f59e0b; } .agent-card.custom-agent:hover { border-color: #f59e0b; } .agent-icon.custom-icon { background: linear-gradient(135deg, #f59e0b, #d97706); } .response-agent-badge.custom-badge { background: rgba(245, 158, 11, 0.1); color: #f59e0b; } And update the Switch node to handle the new agent type! Modify Text Content Modal Guide**: Lines ~754-810 - Update help text Placeholder**: Line ~689 - Change textarea placeholder Subtitles**: Lines 677, 693 - Modify section descriptions Change Agent Descriptions Lines 705, 717, ~729 - Update the description text for each agent. 📱 Built-in Features Enter to Send**: Press Enter to send (Shift+Enter for new line) Escape to Close**: Press Esc to close modals Loading State**: Animated spinner while AI processes Agent Badges**: Color-coded badges show which agent responded Clear Button**: Easily clear responses to start fresh Theme Persistence**: Theme choice saved in browser Smooth Animations**: Professional transitions and hover effects Error Handling**: User-friendly error messages 💡 Example Workflow Ideas Customer Support Bot General Agent**: Answers common questions Database Agent**: Looks up order status, account info Web Agent**: Searches knowledge base articles RAG Agent**: Searches company documentation Data Analysis Tool General Agent**: Explains data concepts Database Agent**: Runs SQL queries on your data Web Agent**: Fetches external data sources RAG Agent**: Searches analysis reports Internal Admin Panel General Agent**: General assistance Database Agent**: User management queries Web Agent**: Check external integrations RAG Agent**: Search internal docs/wikis 🐛 Troubleshooting Response not displaying? Check that Code Node after AI Agent formats response with response field Verify webhook URL in main.js matches your n8n webhook path Check browser console for JavaScript errors AI Agent not responding? Ensure Switch node routes match agent types: general, database, web, rag Verify AI Agent nodes are properly configured with API keys Check n8n execution logs for errors Styling issues? Clear browser cache Check that Font Awesome CDN is loading Verify CSS variables are properly defined 📝 Technical Details Framework**: Pure HTML/CSS/JavaScript (no dependencies!) Icons**: Font Awesome 6.4.0 Browser Support**: All modern browsers (Chrome, Firefox, Safari, Edge) Mobile**: Fully responsive with touch support File Size**: 1050 lines (35KB minified) 🤝 Contributing & Support This template is designed to be simple and self-explanatory. The code structure: Lines 1-23: Configuration and setup Lines 24-640: CSS styles Lines 641-751: HTML structure Lines 752-1048: JavaScript functions Feel free to modify and adapt to your needs! 📝 License Free to use and modify for your n8n workflows. No attribution required.

CLO Agent with Legal Team Description Navigate legal complexities with an AI-powered Chief Legal Officer (CLO) agent orchestrating specialized legal team members for comprehensive legal operations and risk management. Overview This n8n workflow creates a comprehensive legal department using AI agents. The CLO agent analyzes legal requirements and delegates tasks to specialized agents for contract management, compliance, intellectual property, privacy law, corporate governance, and employment law. ⚠️ IMPORTANT DISCLAIMER: These AI agents provide legal information and templates, NOT legal advice. Always consult qualified legal professionals for binding legal matters. This workflow does not create attorney-client privilege or provide professional legal liability coverage. Building Blocks Approach This workflow provides foundational AI agents as building blocks for your legal operations. Feel free to: Customize agent prompts to match your industry and legal requirements Add relevant legal tools and integrations (contract management, compliance platforms) Modify specialist focus areas based on your specific legal needs Integrate with legal research databases and document management systems Adjust the CLO's strategic oversight to align with your risk tolerance Features Strategic CLO agent using OpenAI O3 for complex legal strategy and risk assessment Six specialized legal agents powered by GPT-4.1-mini for efficient execution Complete legal lifecycle coverage from contracts to compliance Automated document generation and review processes Risk assessment and mitigation strategies Intellectual property protection workflows Privacy and data protection compliance Team Structure CLO Agent**: Legal strategy and risk management coordination (O3 model) Contract Specialist**: Contract drafting, review, negotiation terms, agreement analysis Compliance Officer**: Regulatory compliance, legal requirements, audits, risk assessment IP Specialist**: Patents, trademarks, copyrights, trade secrets, IP protection Privacy Lawyer**: GDPR, CCPA, data privacy policies, data protection compliance Corporate Lawyer**: Corporate governance, M&A, securities law, business formation Employment Lawyer**: Employment contracts, workplace policies, labor law, HR legal issues 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 legal requests via chat (e.g., "Draft a software licensing agreement") The CLO will analyze and delegate to appropriate specialists Receive comprehensive legal deliverables and risk assessments Use Cases Contract Lifecycle Management**: Draft → Review → Negotiate → Execute → Monitor Compliance Programs**: Policy creation → Risk assessment → Audit preparation IP Protection Strategy**: Patent applications → Trademark registration → Copyright notices Privacy Compliance**: GDPR assessments → Privacy policies → Data mapping exercises Corporate Governance**: Board resolutions → Shareholder agreements → Corporate bylaws Employment Law**: Policy manuals → Contract templates → Dispute resolution procedures Legal Document Automation**: Template creation → Review workflows → Version control Risk Assessment**: Legal risk evaluation → Mitigation strategies → Compliance monitoring Requirements n8n instance with LangChain nodes OpenAI API access (O3 for CLO, GPT-4.1-mini for specialists) Webhook capability for chat interactions Optional: Integration with legal management tools (contract management systems, legal research databases) Legal Scope & Limitations This AI workflow provides: ✅ Legal document templates and frameworks ✅ Compliance checklists and procedures ✅ Risk assessment methodologies ✅ Legal research summaries and insights This AI workflow does NOT provide: ❌ Legal advice or professional legal counsel ❌ Attorney-client privilege protection ❌ Court representation or litigation support ❌ Professional legal liability coverage ❌ Jurisdiction-specific legal opinions Cost Optimization O3 model used only for strategic CLO decisions and complex legal analysis GPT-4.1-mini provides 90% cost reduction for specialist document tasks Parallel processing enables simultaneous legal workstream execution Template library reduces redundant legal document generation Integration Options Connect to contract management systems (DocuSign, PandaDoc, ContractWorks) Integrate with legal research databases (Westlaw, LexisNexis) Link to compliance management platforms (GRC tools, audit systems) Export to document management systems (SharePoint, Box, Google Drive) Performance Metrics Contract cycle time reduction and accuracy Compliance audit success rates Legal risk identification and mitigation effectiveness Document review efficiency and consistency Cost per legal matter and resource utilization Contact & Resources Website**: nofluff.online YouTube**: @YaronBeen LinkedIn**: Yaron Been Tags #LegalTech #ContractAutomation #ComplianceTech #LegalAI #LegalOps #IntellectualProperty #PrivacyLaw #CorporateLaw #EmploymentLaw #LegalInnovation #n8n #OpenAI #MultiAgentSystem #LegalDocument #RiskManagement #LegalStrategy

How It Works Generate the document structure based on the provided title or short description. Use prompt chaining to create detailed content for each section while maintaining consistent context. Append the final content to a Google Document for easy access and review. How to Use Open the submission form. Enter your title and word count. Click Submit to generate your Google Document link. Wait a few minutes — completed document will be ready at that link. Requirements OpenAI account** Google Docs account** Customization Options Adjust the document length by changing the word count input. Modify the prompt logic to control writing style or tone. Update the section structure to fit different document types (e.g., blog, report, proposal). Replace the output destination if you prefer another storage option instead of Google Docs.

Description Turn images into viral-ready Twitter/X captions in seconds! This n8n automation watches a Google Drive folder for new images, uploads them to Cloudinary, and uses Azure OpenAI (GPT-4o-mini) to generate engaging, platform-optimized captions. Each caption package includes: Punchy headlines and primary tweets (≤280 characters) Mini tweet threads with insights & actions Hashtags, @mentions & posting time recommendations HTML email delivery for quick publishing Perfect for social media managers, creators, and marketing teams who want to speed up content creation while keeping posts high-quality and on-brand. Step-by-Step Workflow: 📂 Google Drive Trigger (Google Drive Trigger Node) Watches a specific folder for new or updated image files. Instantly starts the workflow on detection. 📥 File Download (Google Drive Node) Downloads the new file from Google Drive for processing. ☁️ Cloud Upload (HTTP Request Node → Cloudinary) Uploads the image to Cloudinary. Returns a publicly accessible URL for AI analysis. 🧠 AI Caption Generation (LangChain + Azure OpenAI GPT-4o-mini) Analyzes the image and produces: Short headline & primary tweet A 3-part tweet thread (Hook → Insight → Action) Alt text for accessibility Suggested first-reply content 10–12 optimized hashtags Recommended @mentions Ideal posting times (IST) 📧 Email Delivery (SMTP Node) Sends a professionally formatted HTML email with: The analyzed image All generated Twitter/X content blocks Key visual summary Feature & user targeting notes Perfect For: Social Media Managers – Automate caption creation for client accounts. Content Creators – Turn visuals into instantly postable Twitter/X threads. Marketing Teams – Maintain consistency & posting frequency without manual work. Built With: Google Drive API – File monitoring & download Cloudinary API – Image hosting & URL generation Azure OpenAI GPT-4o-mini – AI caption creation & formatting n8n LangChain Integration – Structured AI prompt execution SMTP Email – Automated content delivery Key Benefits: ✅ Save hours on manual caption writing. 📈 Boost engagement with AI-optimized hashtags & post timing. 🧠 Get both short posts & full threads ready to publish. ⚡ Fully automated — runs whenever you upload a file.

Description: Keep your internal documentation always up to date with this n8n automation template. The workflow listens for GitHub pull request merges to the main branch, detects any changes in documentation files (README, /docs, or OpenAPI specs), and automatically summarizes and syncs updates to Confluence (or internal knowledge systems). It also alerts your team instantly via Slack with a summary of what changed. Ideal for DevOps, technical writers, and engineering teams who want to eliminate manual documentation updates after code merges. ✅ What This Template Does (Step-by-Step) ⚡ Trigger on GitHub Pull Requests: Automatically activates when a PR is merged into the main branch. 🧩 Validate Merge Conditions: Ensures the PR is both merged and targeted at the main branch before continuing. 📥 Fetch Updated Files (README, Docs, OpenAPI): Retrieves key documentation files directly from the GitHub repository for analysis. 🔍 Detect Documentation Changes: Scans payloads for any doc-related keywords or file changes (README, /docs, or OpenAPI). 🤖 AI-Powered Summarization: Uses Azure OpenAI GPT-4o Mini to create a concise 2-3 sentence summary of the changes, perfect for documentation notes or changelogs. 📤 Post Summary to Slack: Shares the AI-generated summary in your #documentation-updates or #general-information channel for instant visibility. 📢 Team Notifications: Sends a detailed Slack message with PR title, author, repo, and branch for full transparency. 🔁 Continuous Sync: Every merged documentation update is detected, summarized, and communicated—without human effort. 🧠 Key Features 🔍 Smart detection for README, Docs, and OpenAPI changes 🤖 AI summarization via Azure OpenAI GPT-4o Mini 📢 Automatic Slack alerts with PR context ⚙️ GitHub OAuth2 integration for secure repo access 📋 Prevents irrelevant PRs from triggering updates 💼 Use Cases 📚 Keep internal Confluence or Notion documentation in sync with code changes 🧾 Auto-generate release notes or changelog summaries 👩‍💻 Keep dev and QA teams informed of key doc updates 🧠 Reduce time spent on manual documentation tracking 📦 Required Integrations GitHub (for PR event and file fetch) Azure OpenAI (for doc change summarization) Slack (for instant team notifications) 🎯 Why Use This Template? ✅ Ensures your docs stay current with every merge ✅ Reduces manual copy-pasting and review effort ✅ Keeps engineering, product, and docs teams aligned ✅ Fully extensible—add Confluence, Notion, or changelog publishing in seconds

Intelligent Document Processing & Data Extraction Extract structured data from unstructured documents like invoices, contracts, reports, and forms. Uses AI to identify and extract key information automatically. Pipeline Features: Process multiple document types (PDFs, Word docs) AI-powered field extraction Custom extraction templates Data validation and cleaning Export to databases or spreadsheets Workflow Steps: Document Input: Various sources supported Parse Document: Convert to structured text Extract Fields: AI identifies key data points Validate Data: Check extracted values Transform: Format for destination system Store/Export: Save to database or file Use Cases: Invoice processing automation Contract data extraction Form digitization Report mining

💬 GPT-5 Slack Impersonation Agent with RAG – Auto-Respond to Messages Using Live Project Docs Let AI handle your Slack conversations — and always have the right answer. This n8n workflow transforms GPT-5 into your on-brand Slack assistant, capable of responding as you in real-time while referencing a Google Docs RAG (Retrieval-Augmented Generation) document for accurate project updates. Watch step-by-step build like these on: https://www.youtube.com/@automatewithmarc Here’s how it works: Listens for Slack mentions or messages — triggered instantly when someone talks to you. Understands the conversation context using GPT-5 and conversation memory. Retrieves the latest project updates from your linked Google Doc via RAG. Responds in Slack as you — maintaining your tone, style, and workplace personality. Key Features & Benefits: 🧠 RAG-powered accuracy – Always pulls the latest info from your project docs. 🤖 GPT-5 natural conversation – Replies feel human, friendly, and context-aware. ⚡ Instant responses – No more message backlog or missed updates. 🎯 Impersonation mode – Sends replies under your Slack name for seamless collaboration. 🔄 Continuous conversation memory – Keeps track of what was said before. Ideal Use Cases: Acting as a stand-in during busy periods so no message goes unanswered. Project managers who want instant, document-backed answers. Customer support or client-facing roles needing quick, accurate replies. Included Integrations: Slack Trigger & Send Message – Listen and reply in real-time. GPT-5 Agent – Craft context-aware, on-brand responses. Google Docs Tool – Pull live data from your RAG document. Conversation Memory – Maintain context across messages. 💡 Pro Tip: Customize the system prompt to mimic your exact tone and integrate with multiple docs for broader knowledge coverage.

Slack Workflow Router: AI-Powered Workflow Selection Problem Statement Slack only allows one webhook per Slack app, and n8n generates a unique webhook for each workflow. This limitation means you typically need to create multiple Slack apps to trigger multiple n8n workflows from Slack. This workflow solves that problem by acting as a gateway for a single Slack app, enabling it to trigger multiple n8n workflows. How It Works When a message is received from Slack, an AI agent analyzes the message and selects the most suitable workflow to execute. The available workflows are stored in a data table, including their ID, name, and description, which the agent uses to make its decision. This approach allows you to manage and trigger multiple workflows from a single Slack app, making your Slack-to-n8n integration much more scalable and maintainable. Key Features Trigger multiple n8n workflows from a single Slack app mention. AI-powered workflow selection based on user message and workflow descriptions. Centralized management of available workflows via a data table. Scalable and easy to maintain—no need to create multiple Slack apps. Setup Instructions Create a data table in your n8n project with these columns: workflow_id, workflow_name, and workflow_description. Add your workflows to the table. Connect your Slack and OpenAI accounts. Deploy the workflow and mention your Slack app to trigger automations. This template is ideal for teams who want to centralize and scale their Slack automation without creating multiple Slack apps.

This workflow acts as a System Prompt Optimizer Agent. You send it a draft prompt or goal, and it returns: A rewritten optimized system prompt that is clear, specific, and actionable. A recommendation for the best OpenAI model to use based on reasoning needs, complexity, and latency/cost tradeoffs. The workflow uses memory for context, so you can iteratively refine prompts. ⚙️ Setup Instructions 1️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 📝 Example Question

Remediate security vulnerabilities with Port This workflow automatically enriches security vulnerability alerts with organizational context from Port and routes them to the appropriate teams or AI agents for remediation. How it works n8n receives a new vulnerability from your security scanner (e.g., Snyk) via webhook The workflow calls Port's context lake to enrich the alert with service, ownership, environment, and dependency data. With this context, the workflow either sends targeted Slack notifications to the owning team or triggers an AI remediation flow to propose and apply a fix. Setup steps [ ] Sign up with a free account on port.io. [ ] Create the required AI agent in Port. [ ] Configure credentials in n8n for Port, Slack, and OpenAI/Claude. [ ] Trigger the webhook with a sample vulnerability to verify context retrieval, Slack notifications, and AI remediation.",

This workflow helps template creators automatically generate an overview sticky note for any n8n template. Paste your workflow JSON into the Set node, run the workflow, and the AI returns a ready-to-use sticky note node JSON with a clear title, “How it works” steps and a setup checklist - all formatted in Markdown and sized correctly for the canvas.