🎓 Learn JSON basics with an interactive step-by-step tutorial for beginners
How it works This workflow is an interactive, hands-on tutorial designed to teach you the absolute basics of JSON (JavaScript Object Notation) and, more importantly, how to use it within n8n. It's perfect for beginners who are new to automation and data structures. The tutorial is structured as a series of simple steps. Each node introduces a new, fundamental concept of JSON: Key/Value Pairs: The basic building block of all JSON. Data Types: It then walks you through the most common data types one by one: String (text) Number (integers and decimals) Boolean (true or false) Null (representing "nothing") Array (an ordered list of items) Object (a collection of key/value pairs) Using JSON with Expressions: The most important step! It shows you how to dynamically pull data from a previous node into a new one using n8n's expressions ({{ }}). Final Exam: A final node puts everything together, building a complete JSON object by referencing data from all the previous steps. Each node has a detailed sticky note explaining the concept in simple terms. Set up steps Setup time: 0 minutes! This is a tutorial workflow, so there is no setup required. Simply click the "Execute Workflow" button to run it. Follow the instructions in the main sticky note: click on each node in order, from top to bottom. For each node, observe the output in the right-hand panel and read the sticky note next to it to understand what you're seeing. By the end, you'll have a solid understanding of what JSON is and how to work with it in your own n8n workflows.
By Lucas PeyrinAutomate blog content creation with OpenAI, Google Sheets & email approval flow
Who is this for? This workflow is perfect for: Digital marketers who need to scale SEO-optimized content production Bloggers and content creators who want to maintain consistent publishing schedules Small business owners who need regular blog content but lack writing resources What problem is this workflow solving? Creating high-quality, SEO-optimized blog content consistently is time-consuming and resource-intensive. This workflow solves that by: Automating the content generation process from topic to final draft Ensuring quality control through human-in-the-loop approval Managing topic queues and preventing duplicate content creation Streamlining the revision process based on human feedback Organizing and archiving all generated content for future reference What this workflow does From topics stored in Google Sheets, this workflow: Automatically retrieves pending topics from your Google Sheets tracking document Generates SEO-optimized blog posts (800-1200 words) using OpenAI GPT-4 with structured prompts Sends content for human approval via email with custom approval forms Handles revision requests by incorporating feedback while maintaining SEO best practices Updates topic status to prevent duplicate processing Add approved generated content in Google Sheets for easy access and management Routes workflow based on approval decisions (approve, revise, or cancel) Setup Copy the Google Sheet template here: 👉 Automate Blog Content Creation – Google Sheet Template Connect Google Sheets with your topic tracking document (requires "Topic List" and "Generated Content" sheets) Add your OpenAI API key to the AI agent nodes for content generation Configure Gmail for the approval notification system Set up your topic list in Google Sheets with "Topic" and "Status" columns Customize the schedule trigger to run at your preferred intervals Update email recipient in the approval node to your email address Test with a sample topic marked as "Pending" in your Google Sheet How to customize this workflow to your needs Adjust content length: modify the word count requirements in the AI agent prompts Change writing style: customize the copywriter prompts for different tones (formal, casual, technical) Add multiple reviewers: extend the approval system to include additional stakeholders Integrate with CMS: add nodes to automatically publish approved content to WordPress, Webflow, or other platforms Include keyword research: add Ahrefs or SEMrush nodes to incorporate keyword data Add image generation: integrate DALL-E or Midjourney for automatic featured image creation Customize approval criteria: modify the approval form to include specific feedback categories Add content scoring: integrate readability checkers or SEO analysis tools before approval Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiPersonal portfolio CV Rag chatbot - with conversation store and email summary
Personal Portfolio CV Rag Chatbot - with Conversation Store and Email Summary Target Audience This template is perfect for: Individuals looking to create a working professional and interactive personal portfolio chatbot. Developers interested in integrating RAG Chatbot functionality with conversation storage. Description Create a stunning Personal Portfolio CV with integrated RAG Chatbot capabilities, including conversation storage and daily email summaries. 2.Features: Training: Setup Ingestion stage Upload your CV to Google Drive and let the Drive trigger updates to read your resume cv and convert it into your vector database (RAG purpose). Modify any parts as needed. Chat & Track: Use any frontend/backend interface to call the chat API and chat history API. Reporting Daily Chat Conversations: Receive daily automatic summaries of chat conversations. Data stored via NocoDB. 3.Setup Guide: Step-by-Step Instructions: Ensure all credentials are ready. Follow the notes provided. Ingestion: Upload your CV to Google Drive. The Drive triggers RAG update in your vector database. You can change the folder name, files and indexname of the vector database accordingly. Chat: Use any frontend/backend interface to call the chat API (refer to the notes for details) . [optional] Use any frontend/backend interface to call the update chat history API (refer to the notes for details). 3.Tracking Chat: Get daily automatic summaries of chat conversations.Format email conversations report as you like. You are ready to go!
By Sean LonSend a message with an inline embedded image with Gmail
The built-in Gmail node doesn't yet support embedding images within the body of the email, but you can pull this off using the HTTP node, and this template shows you how. Requirements A Gmail account How it works The workflow downloads an image, converts it into the format that the Gmail API expects (base64), packages it into a multipart MIME email and uses the HTTP node to send it.
By David RobertsManage emails via WhatsApp with Gmail, GPT and voice recognition
🔍 How it works This workflow turns WhatsApp into a smart email command center using AI. Users can speak or type instructions like: "Send a follow-up to Claire” "Write a draft email to Claire to confirm tomorrow’s meeting at 5 PM” "What is the name of Claire's firm?” The agent transcribes voice notes, extracts intent with GPT, interacts with Gmail (send, draft, search), and replies with a confirmation via WhatsApp — either as text or a voice message. ⚙️ Key Modules Used WhatsApp Business Webhook (Meta) OpenAI Whisper (voice transcription) GPT (intent + content generation) Gmail (search, draft, send) Airtable (contact lookup + memory logging) 🧠 Memory Layer (Optional) The agent logs key fields in Airtable: Recipient email Company / job title And more... This creates a lightweight "gut memory” so the agent feels context-aware. 🗺️ Setup Steps Connect WhatsApp Business API (via Meta Developer Console) Add OpenAI and Gmail credentials in n8n Link your Airtable base for contacts and logging 🧩 Best Use Cases Hands-free email reply while commuting Fast Gmail access for busy consultants / solopreneurs Custom business agents for service-based professionals ⏱️ Estimated Setup Time 30–60 minutes ✅ Requirements WhatsApp Business Cloud access OpenAI API Key Gmail or Google Workspace Airtable account (free plan OK) n8n instance (cloud or self-hosted with HTTPS)
By Floyd MahouAutomate LinkedIn profile search & cold email outreach with OpenAI and Hunter
Problem 🚨 LinkedIn search is BROKEN. I waste hours on LinkedIn manually filtering profiles, reading summaries, hoping they’d reply—tedious, frustrating, inefficient. I wish LinkedIn had built an agent that would get me to the right profile with one click! If only I could just type: "Product managers working on YouTube Shorts' generative AI features." and seconds later, have LinkedIn URLs, names, emails, and full context about them. Introducing LinkGPT, a LinkedIn Agent, an automated agentic workflow powered by n8n. Prerequisites: Required accounts/API keys for Hunter.io, Google, and OpenAI. This would be helpful for: 🎯 Job Seekers: Skip ATS, email hiring managers directly ( I wish I had this when I was recruiting!) 🎯 Recruiters: Reach your dream candidates first 🎯 Founders & Sales Teams: Share your demos with customers directly (this does NOT use the expensive Sales Navigator API) Step-by-step workflow: Takes 5-10 minutes to setup. Generate a Boolean search string for LinkedIn profiles. Perform authenticated Google searches using your query. Extract LinkedIn URLs and workplace context from the search results. Use OpenAI to extract first name, last name, and domain name from the context. Use Hunter.io to find emails of the contacts. Append all results to your connected Google Sheet. Columns: firstname, lastname, domain_name, email, context I put together a clear, step-by-step guide on setting this up yourself. Sample Query Sample: Input: "I am headed to NYC later this month, whom should I meet with that works in product management for gen AI products?" Output: List of 10 contacts with first name, last name, workplace, email address and context about them so you can email them.
By Abhijay VuyyuruExtract Gmail metadata to Google Sheets
Extract Gmail Metadata to Google Sheets This n8n template shows how to fetch new emails from a Gmail account, extract key metadata (sender name, email, subject, and message body), and append each email as a new row in a Google Sheet for record-keeping or follow-up workflows. Good to Know Gmail API Quotas: Gmail’s API has usage limits—make sure your application stays under 2500 read requests per day or implement exponential backoff on rate limit errors. OAuth Credentials: You’ll need to configure OAuth2 credentials in n8n to authenticate with Gmail. Sheet Structure: Prepare your Google Sheet with columns: Timestamp, Sender Name, Sender Email, Subject, Message. How It Works Gmail Trigger: Watches for new emails matching your search criteria (e.g., is:unread). Extract Metadata: A Function node reads the incoming payload and pulls: Name and Email from headers or body text Subject from common subject fields Message from body, text, or snippet Timestamp from current system time Append to Sheet: The Google Sheets node appends each processed email as a row in your target spreadsheet. How to Use Import the Template: Click "Use Template" in your n8n instance. Configure Credentials: Gmail OAuth2: Set up your Gmail account credentials in n8n. Google Sheets: Authorize with your Google account and select the spreadsheet. Adjust Search Criteria: Modify the Gmail Trigger to filter specific labels or queries. Activate and Test: Enable the workflow and send a test email. Verify Sheet: Check your Google Sheet for new rows with the extracted email data. Requirements n8n@latest Gmail OAuth2 Credentials Google Sheets API enabled in your Google Cloud project Customizing This Workflow Additional Fields: Extend the Function node to capture attachments, threads, or labels. Notification Flow: Add Slack or email nodes to notify your team of important messages. Data Enrichment: Integrate with NLP or sentiment analysis APIs to annotate messages.
By Mohammed AbidAutomate call center sentiment analysis with GPT-4o-mini and Google Sheets
✅ What problem does this workflow solve? Call centers often record conversations for quality control and training, but reviewing every transcript manually is tedious and inefficient. This workflow automates sentiment analysis for each call, providing structured feedback across multiple key categories, so managers can focus on improving performance and training. --- ⚙️ What does this workflow do? Accepts a Google Sheet containing: Call transcript Agent name Customer name Analyzes each call transcript across multiple sentiment dimensions: 👋 Greeting Sentiment 🧑💼 Agent Friendliness ❓ Problem-Solving Sentiment 🙂 Customer Sentiment 👋 Closing Sentiment ✅ Issue Resolved (Yes/No) Add Conversation Topics discussed in a call Calculates an overall call rating based on combined analysis. Updates the Google Sheet with: Individual sentiment scores Issue resolution status Final call rating --- 🔧 Setup Instructions 📄 Google Sheets Prepare a sheet with the following columns: Transcript Agent Name Customer Name The workflow will append results in new columns automatically: Greeting Sentiment Closing Sentiment Agent Friendliness Problem Solving Customer Sentiment Issue Resolved Overall Call Rating (out of 5 or 10) 🧠 OpenAI Setup Connect OpenAI API to perform NLP-based sentiment classification. For each transcript, use structured prompts to analyze individual components. --- 🧠 How it Works – Step-by-Step Sheet Scan – The workflow reads rows from the provided Google Sheet. Loop Through Calls – For each transcript, it: Sends prompts to OpenAI to analyze: Greeting tone (friendly/neutral/rude) Problem-solving quality (clear/confusing/helpful) Closing sentiment Agent attitude Customer satisfaction Whether the issue was resolved Calculates a composite rating from all factors. Update Sheet – All analyzed data is written back into the Google Sheet. --- 📊 Example Output https://docs.google.com/spreadsheets/d/1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU/edit?gid=0gid=0 --- 👤 Who can use this? This workflow is ideal for: ☎️ Call Centers 🎧 Customer Support Teams 🧠 Training & QA Departments 🏢 BPOs or Support Vendors If you want deeper insight into every customer interaction, this workflow delivers quantified, actionable sentiment metrics automatically. --- 🛠 Customization Ideas 📅 Add scheduled runs (daily/weekly) to auto-analyze new calls. 📝 Export flagged or low-rated calls into a review dashboard. 🧩 Integrate with Slack or email to send alerts for low-score calls. 🗂 Filter by agent, category, or score to track performance trends. --- 🚀 Ready to Use? Just connect: ✅ Google Sheets (with transcript data) ✅ OpenAI API …and this workflow will automatically turn your raw call transcripts into actionable sentiment insights.
By InfyOm TechnologiesQuery your Trello board using natural language with OpenAI GPT
💬 Chat with Your Trello Board (n8n + OpenAI) 📖 Description Turn your Trello board into a conversational assistant. This workflow pulls your board → lists → cards, aggregates the context, and lets you ask natural-language questions (“what’s overdue?”, “summarize In Progress”, “what changed this week?”). OpenAI reasons over the live board data and replies with concise answers or summaries. Great for standups, planning, and quick status checks—without opening Trello. > Setup steps are already embedded in the workflow (Trello API + OpenAI + board URL). Just follow the sticky notes inside the canvas. --- 🧪 Example prompts “Give me a one-paragraph summary of the board.” “List all cards due this week with their lists.” “What’s blocking items in ‘In Progress’?” “Show new cards added in the last 2 days.” --- ⚙️ Setup Instructions 1️⃣ Connect Trello (Developer API) Get your API key: https://trello.com/app-key Generate a token (from the same page → Token) In n8n → Credentials → New → Trello API, paste API Key and Token, save. Open each Trello node (Get Board, Get Lists, Get Cards) and select your Trello credential. 2️⃣ 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 3️⃣ Add Your Board URL to “Get Board” Copy your Trello board URL (e.g., https://trello.com/b/DCpuJbnd/administrative-tasks). Open the Get Board node → Resource: Board, Operation: Get. In ID, choose URL mode and paste the board URL. The node will resolve the board and output its id → used by Get Lists / Get Cards. 📬 Contact Need help customizing this or adding Slack/Email outputs? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com
By Robert BreenEnterprise contract lifecycle management with AI risk analysis
Overview Transform your contract management process with this enterprise-grade workflow that handles the complete contract lifecycle - from initial intake through execution, monitoring, and renewal. This comprehensive solution combines AI-powered contract analysis with automated risk scoring, clause comparison, obligation tracking, and proactive alerts. It integrates with multiple data sources including email, SharePoint, contract CLM systems, and creates a centralized contract intelligence hub that prevents revenue leakage, ensures compliance, and accelerates deal velocity. What You Can Do This advanced workflow orchestrates a complete contract management ecosystem that monitors multiple channels (email, Google Drive, SharePoint, APIs) for new contracts and amendments. It extracts and analyzes over 50 contract data points using AI, performs multi-dimensional risk assessment across legal, financial, and operational factors, compares clauses against your approved template library, tracks all obligations and key dates with automated reminders, integrates with Salesforce/CRM for deal alignment, routes contracts through dynamic approval workflows based on risk scores, generates executive dashboards with contract analytics, and maintains a searchable repository with version control. The system handles complex scenarios including multi-party agreements, framework contracts with statements of work, international contracts requiring jurisdiction analysis, and M&A due diligence requiring bulk contract review. Who It's For Designed for enterprise legal operations teams managing thousands of contracts annually, procurement departments negotiating complex vendor agreements, contract managers overseeing multi-million dollar portfolios, compliance teams ensuring regulatory adherence across jurisdictions, sales operations needing faster contract turnaround, and C-suite executives requiring contract intelligence for strategic decisions. Essential for organizations in regulated industries (healthcare, finance, government) and companies undergoing digital transformation of their legal operations. The Problem It Solves Manual contract management creates massive operational risks and inefficiencies. Organizations typically have contracts scattered across emails, shared drives, and filing cabinets with no central visibility. This leads to missed renewal deadlines costing 5-10% of contract value, unauthorized contract variations creating compliance risks, obligation failures resulting in penalties and damaged relationships, and inability to leverage favorable terms across similar contracts. Studies show that inefficient contract management costs organizations up to 9% of annual revenue. This workflow creates a single source of truth for all contracts, automates tracking and compliance, and provides predictive insights to prevent issues before they occur. Setup Instructions Multi-Channel Integration: Configure connectors for email (Office 365/Gmail), Google Drive, SharePoint, and contract management systems PDF Vector Setup: Install PDF Vector node and configure API with enterprise rate limits Database Configuration: Set up PostgreSQL/MySQL for contract repository with proper indexing Template Library: Upload your standard contract templates and approved clause library Risk Framework: Configure risk scoring matrix for your industry (legal, financial, operational risks) Approval Matrix: Define approval routing based on contract value, type, and risk score CRM Integration: Connect to Salesforce/HubSpot for opportunity and account alignment Notification Setup: Configure Slack/Teams channels and email distribution lists Dashboard Creation: Set up Tableau/PowerBI connectors for executive reporting Security Configuration: Enable encryption, audit logging, and role-based access controls Key Features Intelligent Intake System: Monitor email attachments, shared folders, CRM uploads, and API submissions Advanced AI Extraction: Extract 50+ data points including nested obligations and conditional terms Multi-Dimensional Risk Scoring: Analyze legal, financial, operational, and reputational risks Clause Library Comparison: Compare against approved templates and flag deviations Obligation Management: Track deliverables, milestones, and SLAs with automated alerts Dynamic Approval Routing: Route based on AI risk score, contract value, and deviation analysis Version Control & Redlining: Track all changes and maintain complete audit trail Salesforce Integration: Sync contract data with opportunities and accounts Predictive Analytics: Forecast renewal likelihood and negotiation outcomes Bulk Processing: Handle M&A due diligence with parallel processing of hundreds of contracts Multi-Language Support: Process contracts in 15+ languages with automatic translation Executive Dashboards: Real-time visibility into contract portfolio and risk exposure Customization Options Implement industry-specific modules for healthcare (BAAs, DPAs), financial services (ISDAs, loan agreements), technology (SaaS, licensing), or government contracting. Add AI models trained on your historical contracts for better extraction accuracy. Create custom risk factors for emerging regulations like AI governance or ESG compliance. Build integration with specific CLM systems (Ironclad, Docusign CLM, Icertis). Implement advanced analytics including contract similarity scoring, win-rate analysis by clause variations, and automatic playbook generation. Add blockchain integration for smart contract execution and configure automated contract assembly for standard agreements. Note: This workflow uses the PDF Vector community node. Make sure to install it from the n8n community nodes collection before using this template.
By PDF VectorGenerate stock trading signals with Gemini 2.5 Pro & TwelveData via Telegram Bot
Purpose and Audience This n8n workflow template creates an intelligent stock technical analysis system that delivers professional-grade trading signals directly to your Telegram. Designed for retail traders, investors, and financial professionals who want to combine technical analysis with AI-powered insights for better market timing decisions. Who Is It For Retail Traders: Looking to enhance their technical analysis with AI-driven insights Swing Traders: Need reliable signals for entry and exit timing Investment Professionals: Want automated technical screening for multiple stocks Financial Enthusiasts: Interested in combining traditional TA with modern AI tools Portfolio Managers: Seeking systematic approach to market timing How It Works The workflow operates as a comprehensive technical analysis engine: Data Collection: Fetches real-time stock prices and 90-day historical data from TwelveData API Technical Calculation: Computes key indicators including EMAs, RSI, ATR, and support/resistance levels AI Analysis: Uses Google Gemini 2.5 Pro to analyze confluence of indicators and generate single, high-probability signals Signal Generation: Produces clear BUY/SELL/NEUTRAL recommendations with specific entry, stop-loss, and take-profit levels Delivery: Sends formatted analysis and interactive charts via Telegram bot Risk Management: Includes built-in risk parameters and confidence scoring Setup Requirements Create Telegram bot via BotFather Set up Google Gemini credentials Configure additional nodes as you see in the sticky notes Deploy and test with stock symbols (e.g., "AAPL", "TSLA") Note: Complete setup guide is provided with the workflow file. Technical Indicators Used in Strategy Core Indicators (1-Day Timeframe): EMA 50 & EMA 200: Trend direction and momentum confirmation RSI (14-period): Momentum oscillator for overbought/oversold conditions ATR (14-period): Volatility measurement for risk sizing Support/Resistance: Dynamic levels calculated from 90-day price history. Fibonacci Retracements: Additional confluence levels. Important Disclaimers ⚠️ Analysis timeframe is set to 1-day by default - suitable for swing trading, not day trading ⚠️ Not a get-rich-quick system - This tool provides technical analysis, not financial advice ⚠️ Use with fundamental analysis - Technical signals work best when combined with fundamental research for timing entries and exits ⚠️ Not recommended for isolated use - Always consider fundamentals, market conditions, news, and risk management Key Features Single, clear signal per analysis (no conflicting recommendations; either buy or sell) Built-in confidence scoring system Automated chart generation and delivery Support for any US stock ticker Professional-grade risk management parameters Use Case Examples Pre-market Analysis: Send "AAPL" stock ticker as a message to your telegram bot and get comprehensive technical analysis with 1 Day candlesticks chart Swing Trading: Use signals to time entries on already-researched stocks Portfolio Review: Analyze multiple positions for exit timing Educational Tool: Learn technical analysis through AI explanations This template transforms complex technical analysis into accessible, actionable trading insights while maintaining professional risk management standards.
By Malik HashirSync Azure DevOps work items to GitHub issues with Google Sheets tracking
Who is this for? This workflow is designed for software teams, project managers, and developers who manage work across Azure DevOps and GitHub. It helps organizations that use Azure DevOps for work item tracking but rely on GitHub for issue management and collaboration. If you need to ensure that your DevOps Stories and Tasks are mirrored in GitHub issues while keeping a single source of truth in Google Sheets, this workflow is for you. What problem is this workflow solving? / Use case Managing projects across multiple platforms often leads to missed updates and poor traceability. Stories created in Azure DevOps may not be tracked properly in GitHub.\ Tasks under Stories often lose visibility when teams split between platforms.\ Manual syncing between tools takes time and causes human errors. This workflow solves that problem by automating the sync between Azure DevOps Stories and GitHub Issues, while also keeping a Google Sheets record for cross-referencing and reporting. What this workflow does Triggers from Azure DevOps Stories -- When a Story is created or updated, the workflow is activated.\ Creates a GitHub Issue -- A new issue is generated in the specified GitHub repository.\ Assigns a random collaborator -- One repository collaborator is randomly assigned to the issue.\ Logs mapping in Google Sheets -- The Azure DevOps Story ID, GitHub Issue number, and URL are stored for tracking.\ Triggers from Azure DevOps Tasks -- When a Task linked to a Story is created, the workflow looks up its parent in Google Sheets.\ Updates the GitHub Issue -- The parent GitHub Issue is updated with a clickable link to the new Task for better visibility. Setup Connect your accounts GitHub (OAuth2 or personal token)\ Google Sheets (OAuth2)\ Azure DevOps (Webhook integration) Configure Webhooks Add the workflow's webhook URLs to Azure DevOps service hooks for Work Item Created/Updated events. Update repository details Set the GitHub repository where issues should be created. Customize Sheets Use the provided Google Sheet or link your own for issue mappings. How to customize this workflow to your needs Modify assignment logic: Instead of random collaborator assignment, edit the Code node to assign issues based on workload or labels.\ Change Sheet schema: Add more fields (e.g., State, IterationPath) to your Google Sheet for richer reporting.\ Expand task linking: Customize the way Tasks are appended to GitHub issues (e.g., group by state, show due dates). Powered By Concept Recall https://conceptrecall.com
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