Workflow Templates

Generate Images from Text with IBM Granite Vision 3.3 2B AI Model 🌍 Overview This workflow uses the ibm-granite/granite-vision-3.3-2b model (hosted on Replicate) to generate AI images. It starts manually, sends a request to the Replicate API, waits for the result, and finally outputs the generated image link. Think of it as your AI art assistant — you click once, and it handles the full request/response cycle for image generation. 🟢 Section 1: Trigger & API Setup 🔗 Nodes: Manual Trigger* → Starts when you click *Execute. Set API Key** → Stores your Replicate API Key safely in the workflow. 💡 Beginner takeaway: This section is like turning the key in the ignition. You start the workflow, and it loads your credentials so you can talk to Replicate’s API. 📈 Advantage: Keeps your API key stored inside the workflow instead of hard-coding it everywhere. 🟦 Section 2: Create Prediction 🔗 Nodes: HTTP Request (Create Prediction)** → Sends a request to Replicate with the chosen model (granite-vision-3.3-2b) and input parameters (seed, temperature, max\_tokens, etc.). 💡 Beginner takeaway: This is where the workflow actually asks the AI model to generate an image. 📈 Advantage: You can tweak parameters like creativity (temperature) or randomness (seed) to control results. 🟣 Section 3: Polling & Status Check 🔗 Nodes: Extract Prediction ID (Code)** → Saves the unique job ID. Wait (2s)** → Pauses before checking status. Check Prediction Status (HTTP Request)** → Calls Replicate to see if the image is ready. If Condition (Check If Complete)** → ✅ If status = succeeded → move to result 🔄 Else → go back to Wait and check again 💡 Beginner takeaway: Since image generation takes a few seconds, this section keeps asking the AI “are you done yet?” until the image is ready. 📈 Advantage: No need to guess — the workflow waits automatically and retries until success. 🔵 Section 4: Process Result 🔗 Nodes: Process Result (Code)** → Extracts the final data: ✅ Status ✅ Output image URL ✅ Metrics (time taken, etc.) ✅ Model info 💡 Beginner takeaway: This section collects the finished image link and prepares it neatly for you. 📈 Advantage: You get structured output that you can save, display, or use in another workflow (like auto-sending images to Slack or saving to Google Drive). 📊 Final Overview Table | Section | Nodes | Purpose | Benefit | | -------------------- | ---------------------------------- | --------------------------- | --------------------------- | | 🟢 Trigger & Setup | Manual Trigger, Set API Key | Start + load credentials | Secure API key management | | 🟦 Create Prediction | HTTP Request | Ask AI to generate image | Control creativity & output | | 🟣 Polling | Extract ID, Wait, Check Status, If | Repeatedly check job status | Auto-wait until done | | 🔵 Process Result | Process Result | Extract image + details | Get clean output for reuse | 🚀 Why This Workflow is Useful Automates full API cycle** → From request to final image URL Handles delays automatically** → Keeps checking until your image is ready Customizable parameters** → Adjust creativity, randomness, and token limits Reusable** → Connect it to email, Slack, Notion, or storage for instant sharing Beginner-friendly* → Just plug in your API key and hit *Execute

This is an n8n workflow designed to implement an advanced AI chatbot with real-time conversation and search capabilities. Configured with a minimalist European design, this chatbot is ready to be integrated into any website. What Does This Workflow Do? The workflow uses a combination of nodes to create a complete chatbot: Chat Trigger: Starts the process when a user sends a message. The configuration includes a customized visual design (minimalist European CSS), welcome messages, and titles. AI Agent: Acts as the chatbot's brain. It coordinates interaction with the language model, memory, and tools to generate intelligent responses. Conversational Memory: Allows the chatbot to remember the context of the conversation, providing a smoother and more coherent experience. Language Model (GPT): Generates the chat responses. Search Tool: Enables the AI agent to search for information on the web and answer questions it doesn't already know. Respond to Chat: Sends the final response back to the user. Use Cases Customer Support**: Answers frequently asked questions and transfers complex conversations to a human agent. Virtual Assistant**: Provides information about products or services, helps users navigate your website, or completes simple tasks. Content Generator**: Serves as an assistant for generating ideas, writing drafts, or summarizing texts. Who Is This For? This workflow is ideal for: Businesses and developers** looking for a versatile and customizable chatbot solution without having to build it from scratch. Business owners** who want to improve customer service and user interaction in an automated way. Curious individuals** and AI enthusiasts who want to explore how chatbots are built and experiment with their own configurations. This workflow includes detailed documentation that explains how each node works and how to customize it for your needs.

🚨Are alert storms overwhelming your Security Operations workflows? This n8n workflow supercharges your SOC by fully automating triage, analysis, and notification for Wazuh alerts—blending event-driven automation, OpenAI-powered contextual analysis, and real-time collaboration for incident response. 🔑 Key Features: ✅ Automated Triage: Instantly filters Wazuh alerts by severity to focus analyst effort on the signals that matter. 🤖 AI-Driven Investigation Reports: Uses OpenAI's GPT-4o-mini to auto-generate context-rich incident reports, including: MITRE Tactic & Technique mapping Impacted scope (IP addresses, hostnames) External artifact reputation checks Actionable security recommendations Fully customizable prompt format aligned with your SOC playbooks 📡 Multi-Channel Notification Delivers clean, actionable reports directly to your SOC team via Telegram. Easily extendable to Slack, Outlook, Gmail, Discord, or any other preferred channel. 🔇 Noise Reduction Eliminates alert fatigue using smart filters and custom AI prompts that suppress false positives and highlight real threats. 🔧 Fully Customizable Tweak severity thresholds, update prompt logic, or integrate additional data sources and channels — all with minimal effort ⚙️ How It Works Webhook Listens for incoming Wazuh alerts in real time. If Condition Filters based on severity (1 low, 2 medium, etc.) or other logic you define. AI Investigation (LangChain + OpenAI) Summarizes full alert logs and context using custom prompts to generate: Incident Overview Key Indicators Log Analysis Threat Classification Risk Assessment Security Recommendations Notification Delivery The report is parsed, cleaned, and sent to your SOC team in real-time, enabling rapid response — even during high-alert volumes. No-Op Path Efficiently discards irrelevant alerts without breaking the flow. 🧠 Why n8n + AI? Traditional alert triage is manual, slow, and error-prone — leading to analyst burnout and missed critical threats. This workflow shows how combining workflow automation with a tailored AI model enables your SOC to shift from reactive to proactive. Analysts can now: Focus on critical investigations Respond to alerts faster Eliminate copy-paste fatigue Get instant contextual summaries > ⚠️ Note: We learned that generic AI isn’t enough. Context-rich prompts and alignment with your actual SOC processes are key to meaningful, scalable automation. 🚀 Ready to build a smarter, less stressful SOC? Clone this workflow, adapt it to your processes, and never miss a critical alert again. 📬 Contributions welcome! Feel free to raise PRs, suggest new enhancements, or fork for your own use cases. Created by Mariskarthick M Senior Security Analyst | Detection Engineer | Threat Hunter | Open-Source Enthusiast

This automated n8n workflow provides an AI-powered email classifier for support emails, automatically categorizing incoming emails and routing them to the appropriate inbox, creating a Jira task, and sending an autoresponse within minutes. Main Components IMAP Email** - Monitors incoming support emails via IMAP OpenAI** - Classifies emails into categories (billing, bug, feature) Switch** - Routes emails based on the classified category Send Billing Email** - Forwards billing-related emails to the billing inbox Send Bug Email** - Forwards bug-related emails to the bugs inbox Send Feature Email** - Forwards feature-related emails to the features inbox Create Jira Task** - Creates a task in Jira for each classified email Send Autoresponse** - Sends a confirmation email to the sender Essential Prerequisites IMAP access to the support email account OpenAI API key SMTP server credentials for sending emails Jira account with API access Customization Guide Update IMAP host and credentials in the IMAP Email node Adjust OpenAI model or prompt in the OpenAI node Modify email addresses (billing@yourdomain.com, bugs@yourdomain.com, features@yourdomain.com) in Send Email nodes Configure Jira project ID and credentials in the Create Jira Task node Change autoresponse text in the Send Autoresponse node Features 🤖 AI Classification:** Uses OpenAI to categorize emails into billing, bug, or feature 🔄 Automated Routing:** Routes emails to the correct inbox based on category 🎯 Task Creation:** Creates a Jira task for each support request 📧 Autoresponse:** Sends instant confirmation to the sender ⚡ Optimizations Made:** Streamlined email processing with single-pass classification Parameters to Configure imap_host: Your IMAP server address imap_user: IMAP username (e.g., support@yourdomain.com) imap_password: IMAP password openai_api_key: OpenAI API key smtp_host: Your SMTP server address smtp_user: SMTP username smtp_password: SMTP password jira_project_id: Your Jira project ID jira_user: Jira username jira_api_token: Jira API token How to Use Copy the JSON code from the artifact Open your n8n workspace Select “Import from JSON” or “+” → “From JSON” Paste the JSON code Configure parameters in the respective nodes with your credentials and settings Run the workflow Workflow Actions Classify:** Uses OpenAI to categorize incoming emails Route:** Forwards emails to the appropriate inbox Create:** Generates a Jira task for each email Respond:** Sends an autoresponse to the sender

This automation retrieves company information from a Google Sheet, uses the Anymail Finder API to discover email addresses associated with each company, and then writes the results (including the email status) back into the same Google Sheet and send alert on Telegram. Key Advantages ✅ Automated Email Discovery:** No need for manual lookups—emails are found via the Anymail Finder API in bulk. 🔁 Seamless Google Sheets Integration:** Works directly with Google Sheets for input and output, allowing easy data management. 🧠 Smart Filtering:** Automatically classifies emails as valid, risky, or not found for quality control. ⚙️ Reusable & Scalable:** Can be run anytime with a manual trigger or expanded to handle thousands of records with minimal setup. 📊 Real-Time Updates:** Results are immediately reflected in your spreadsheet, streamlining lead generation and outreach workflows. 💸 Cost-Efficient:** Uses a free Anymail Finder trial or API key for testing and validation before scaling up. How it Works This automated workflow finds email addresses for a list of companies using the Anymail Finder API and updates a Google Sheets document with the results. Trigger & Data Retrieval: The workflow starts manually. It first connects to a specified Google Sheet and retrieves a list of company leads that are marked for processing (where the "PROCESSING" column is empty). Batch Processing & API Call: The list of leads is then split into batches (typically one item at a time) to be processed individually. For each company, the workflow sends the "Company Name" and "Website" to the Anymail Finder API to search for a relevant email address. Result Classification: The API's response, which includes the found email and its status (e.g., valid, risky), is passed to a Switch node. This node routes the data down different paths based on the email status. Sheet Update: Depending on the status: Valid/Risky Email: The workflow updates the original Google Sheet row. It marks the "PROCESSING" column with an "x" and writes the found email address into the "EMAIL" column. No Email Found: The workflow also updates the sheet, marking "PROCESSING" with an "x" and leaving the "EMAIL" column empty to indicate no email was found. Loop Completion: After processing each item, the workflow loops back to process the next lead in the batch until all companies have been handled. Set up Steps To use this workflow, you need to complete the following configuration steps: Duplicate the Template Sheet: Clone the provided Google Sheets template to your own Google Drive. This sheet contains the necessary columns ("COMPANY NAME", "WEBSITE", "EMAIL", "PROCESSING") for the workflow to function. Get an API Key: Sign up for a free trial at Anymail Finder to obtain your personal API key. Configure Credentials in n8n: Google Sheets: In both the "Get Leads" and update nodes, set up the Google Sheets OAuth2 credential to grant n8n access to your copied spreadsheet. Anymail Finder: In the "Email finder" HTTP Request node, create a new credential of type "HTTP Header Auth". Name it "Anymail Finder". In the "Name" field, enter Authorization. In the "Value" field, paste your Anymail Finder API key. Update Sheet ID in Nodes: In the n8n workflow, update all Google Sheets nodes ("Get Leads", "Email found", "Email not found") with the Document ID of your cloned Google Sheet. The Sheet ID can be found in your sheet's URL: https://docs.google.com/spreadsheets/d/[YOUR_SHEET_ID_HERE]/edit.... Execute: Once configured, add your list of companies and their websites to the sheet and run the workflow using the "Manual Trigger" node. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Description: Automatically classify invoices by industry (Retail, Manufacturing, or EdTech) using GPT-4o-powered AI parsing in this intelligent n8n automation template. Designed for teams managing high-volume billing data, this workflow fetches invoices from Google Drive, extracts PDF text, classifies each document using AI, and automatically moves files to the correct folder based on the predicted industry. This smart auto-sorting system turns your invoice processing into a zero-touch AI workflow—ideal for finance teams, document processing agencies, and operations managers dealing with multi-client or multi-industry invoicing pipelines. What This Template Does (Step-by-Step) 📂 Google Drive Search Scans a designated folder (e.g., “Incoming Invoices”) Collects all PDF files available for classification ⬇️ Download & Extract PDF Text Downloads each file using Google Drive API Extracts invoice text from PDFs using the “Extract from File” node 🔁 Batch Handling Loops through each invoice in a batch using the SplitInBatches node Ensures each document is processed one at a time 🧠 GPT-4o Mini via LangChain Agent Sends extracted invoice content to GPT-4o AI Classifies the document into one of: Retail, Manufacturing, EdTech Returns clean, structured classification output 🔀 Smart Switch Logic Evaluates the classification result Routes the invoice to the correct folder based on its predicted industry 📁 Auto-Move Files Uses Google Drive API to move files into industry-specific folders: Retail → Folder A Manufacturing → Folder B EdTech → Folder C Required Integrations: ✅ Google Drive (OAuth2 authentication) ✅ Azure OpenAI (GPT-4o or compatible model) ✅ LangChain agent setup in n8n Best For: 🧾 Finance teams classifying vendor or client invoices 🏭 Companies handling multi-industry procurement 🧠 AI automation agencies building custom document sorters 🗂️ Back-office automation for Google Drive file workflows Key Benefits: 💡 No manual labeling required — AI classifies based on content 📦 Automatically moves files to clean, organized folders 🔄 Works in batch mode for bulk invoice handling 💬 Simple prompt customization for other classification types 🧠 GPT-4o-powered classification ensures high accuracy

Bakery Data Analytics Workflow Explanation Aim The aim of the Bakery Data Analytics Workflow is to automate the process of analyzing bakery sales and stock data stored in Google Sheets. It allows bakery owners or managers to interact with an AI assistant via chat and receive clear, concise, and actionable insights about their business performance without manually reviewing spreadsheets. Goal The goal is to: Enable users to query bakery sales and stock data through a chat interface. Use an AI Agent to interpret user queries and fetch the required data. Retrieve relevant sales/stock figures from a Google Sheets dataset. Generate insights in plain English, with short summaries, highlights, or breakdowns. Maintain conversation context so users can ask follow-up questions naturally. This ensures that bakery owners can make quick, informed decisions about sales trends, inventory shortages, or product performance with minimal manual effort. Requirements The workflow relies on the following components and configurations: n8n Platform The automation platform hosting the workflow. Node Requirements When chat message received (Trigger) Captures user input via chat. Initiates the workflow execution. AI Agent Central reasoning engine. Interprets queries, decides when to fetch data, and ensures professional responses. Uses short, structured insights (bullets, tables, or compact summaries). Simple Memory Stores short-term conversation history. Maintains context across multiple user queries. Retrieve bakery data (Google Sheets) Connects to a linked Google Sheets file. Fetches sales/stock data (e.g., daily totals, item performance). Data source: Bakery Google Sheet. Azure OpenAI Chat Model Backend language model powering the AI Agent. Provides natural language understanding and generates concise responses. Credentials Google Sheets OAuth2 account** (for accessing bakery data). Azure OpenAI API account** (for AI-driven reasoning and conversation). Input Requirements User question/query via chat (e.g., “What was the best-selling pastry last week?”). Output Compact, conversational insights (totals, highlights, trends) delivered via chat. API Usage The workflow integrates two main APIs: Google Sheets API Used by the Retrieve bakery data node. Fetches structured data (sales, stock, dates) from the bakery dataset. Provides the AI Agent with real-time data access. Azure OpenAI API Used by the Azure OpenAI Chat Model node. Powers natural conversation, ensures responses are plain English, concise, and business-focused. Aligns with AI Agent rules to avoid assumptions and provide actionable insights only when asked. Workflow Summary The Bakery Data Analytics Workflow automates bakery performance analysis by: Triggering on chat message input. Passing the query to the AI Agent for interpretation. Using Simple Memory to track context across the conversation. Fetching relevant data from Google Sheets when needed. Leveraging Azure OpenAI to generate structured, professional responses. This creates an interactive AI-powered assistant for bakery data, enabling quick insights into sales and inventory trends without manually combing through spreadsheets.

Scale Your Creative Strategy: 100+ Creative Ads from 1 Image using Fal.AI, Nano Banana model and GPT-5.1 This workflow turns a single reference image into up to 100 high-performing ad variations using Fal.AI's Nano Banana model and GPT-5.1. Simply upload your inspiration to a form, and watch as unique, campaign-ready images appear in your Google Drive. Why use this? Scale Instantly:** Turn one idea into a full campaign without manual design work. Smart Variations:** Uses GPT-5.1 to analyze your reference and rewrite prompts based on proven creative recipes (Metaphors, Pointers, Comparisons). Cost Effective:* Generates 100 variations for approximately *$4.60** (vs. hundreds of dollars with manual design). How does it work? You submit the form with your reference image, company name, and selected "Creative Recipe." GPT-5.1 analyzes your image deeply ("Describe the image extremely comprehensively..."). It rewrites the prompt into multiple unique variations based on your chosen strategy (e.g., "The Metaphor Bake"). Fal.AI generates the images using the fast and efficient Nano Banana model. The results are saved directly to your Google Drive output folder. What do you need? Google Drive Credentials:** To upload your reference and save the results (Guide). OpenAI API Key:** For GPT-5.1 analysis and prompt engineering. Fal.AI API Key:** For generating the images (ensure you have credits). A Google Drive Folder:** One for inputs and one for outputs. 💰 Estimated Costs Fal.AI:** ~$4.00 for 100 images ($0.04/image). GPT-5.1:** ~$0.60 for 100 descriptions (Input: $1.25/1M tokens, Output: $10.00/1M tokens). Total:** ~$4.60 per 100-ad campaign. Important: The Prompt Strategy This automation doesn't just copy your image. It uses a specific instruction to "Describe the image extremely comprehensively. don't leave anything behind". This ensures GPT-5.1 captures every visual detail—lighting, composition, and mood—before rewriting it into new creative angles. That’s it! Just fill the form and let the automation build your ad campaign. If you have any questions, just contact me in X @maxrojasdelgado.

Description: Deliver instant answers and automate customer support on WhatsApp with this intelligent n8n workflow template! The system routes incoming messages using keyword-based logic and provides dynamic, AI-powered responses for greetings, FAQs, and complex queries—ensuring your customers always get the right reply without manual effort. This automation is designed for businesses, service providers, and support teams who want to streamline WhatsApp engagement, reduce manual workload, and provide consistent, conversational answers that scale with demand. What This Template Does (Step-by-Step): 📲 Capture Incoming WhatsApp Messages Triggers on every new message received via WhatsApp API. 🔄 Keyword-Based Routing Sequential IF conditions check for predefined keywords (e.g., “hi”, “pricing”, “support”). 💬 Send Tailored Keyword Responses Returns fast, pre-written responses for greetings, FAQs, or common scenarios. 🤖 AI-Powered Fallback with OpenAI Chat Model For advanced or unrecognized queries, the workflow generates context-aware, conversational answers using AI. 🚀 Deliver Automated Replies in Real Time Replies are instantly sent back to WhatsApp for seamless customer communication. 📊 Optional: Conversation Logging Extend the template to log chats in Notion, Airtable, or your CRM for tracking and insights. Perfect For: Customer support teams handling repetitive queries Businesses wanting instant replies for FAQs & greetings Service providers delivering personalized, scalable engagement Anyone looking to combine rule-based automation with AI intelligence Built With: WhatsApp API (message triggers & replies) n8n IF Node (keyword routing) OpenAI Chat Model (AI fallback for complex queries) Extendable storage (Notion, Google Sheets, Airtable, etc.) Key Benefits: ✅ Faster, automated customer support on WhatsApp 🔍 Accurate, human-like replies for complex questions 🧠 Hybrid system: keyword rules + AI intelligence 📒 Centralized chat logging for insights (optional) 🛠 100% no-code and customizable in n8n

How it works Create a user for doing Hybrid Search. Clear Existing Data, if present. Add Documents into the table. Create a hybrid index. Run Semantic search on Documents table for "prioritize teamwork and leadership experience". Run Hybrid search for the text inputted in Chat interface. Setup Steps Download the ONNX model all_MiniLM_L12_v2_augmented.zip Extract the ZIP file on the database server into a directory, for example /opt/oracle/onnx. After extraction, the folder contents should look like: bash-4.4$ pwd /opt/oracle/onnx bash-4.4$ ls all_MiniLM_L12_v2.onnx Connect as SYSDBA and create the DBA user -- Create DBA user CREATE USER app_admin IDENTIFIED BY "StrongPassword123" DEFAULT TABLESPACE users TEMPORARY TABLESPACE temp QUOTA UNLIMITED ON users; -- Grant privileges GRANT DBA TO app_admin; GRANT CREATE TABLESPACE, ALTER TABLESPACE, DROP TABLESPACE TO app_admin; Create n8n Oracle DB credentials hybridsearchuser → for hybrid search operations dbadocuser → for DBA setup (user and tablespace creation) Run the workflow Click the manual Trigger It displays Pure semantic search results Enter search text in Chat interface It displays results for vector and keyword search. Note The workflow currently creates the hybrid search user, docuser with the password visible in plain text inside the n8n Execute SQL node. For better security, consider performing the user creation manually outside n8n. Oracle 23ai or 26ai Database has to be used` Reference Hybrid Search End-End Example

🧾 Smart Sales Invoice Processor (Data tables Edition) Transform uploaded sales CSV files into validated, enriched invoices, all handled natively inside n8n using Data tables, validation logic, enrichment, duplicate detection, and automated email notifications. This workflow demonstrates a full ETL + business automation pattern, turning raw CSV data into structured, auditable records ready for storage and customer notifications. ✨ Features ✅ Multi-format CSV input (file upload or raw text) ✅ Validation for email, quantity, date, and required fields ✅ Automatic error handling with 400 Bad Request JSON response for invalid CSVs ✅ Product enrichment from Products Datatable ✅ Invoice creation and storage in Invoices Datatable ✅ Automated subtotal, tax, and total calculation ✅ Duplicate order detection with 409 Conflict response ✅ Ready-to-send email confirmations (simulated in this version) ✅ Fully native, no external integrations required 🧩 Use Cases E-commerce order and invoice automation Internal accounting or ERP data ingestion Migrating CSV-based legacy systems into n8n Automated business logic for B2B integrations ⚙️ Setup Instructions 1️⃣ Create two n8n Data tables Products Stores your product catalog with SKU-based pricing and tax details. | Column | Type | Example | | -------- | ------ | -------------- | | sku | String | PROD-001 | | name | String | Premium Widget | | price | Number | 49.99 | | tax_rate | Number | 0.10 | Invoices Stores validated, calculated invoices created by this workflow. | Column | Type | Example | | -------------- | -------- | ------------------------------------------- | | invoice_id | String | INV-20251103-001 | | customer_email | String | john@example.com | | order_date | Date | 2025-01-15 | | subtotal | Number | 99.98 | | total_tax | Number | 10.00 | | grand_total | Number | 109.98 | | created_at | DateTime | 2025-11-03T08:00:00Z | 2️⃣ Import Workflow Import the provided workflow JSON file into your n8n instance. 3️⃣ Test the Workflow Use cURL or Postman to send a test CSV to your endpoint. curl -X POST \ -H "Content-Type: text/csv" \ --data-binary $'sku,quantity,customer_email,order_date\nPROD-001,2,john@example.com,2025-01-15\nPROD-002,1,jane@example.com,2025-01-15' \ https://<your-n8n-url>/webhook/process-sales 📦 Example Responses ✅ Success (HTTP 200) { "success": true, "processed_at": "2025-11-04T15:36:52.899Z", "invoice_count": 1, "invoices": { "to": "john@example.com", "subject": "Invoice INV-1762270612772-1 - Order Confirmation", "body": "Dear Customer,\n\nThank you for your order!\n\nInvoice ID: INV-1762270612772-1\nOrder Date: 1/14/2025\n\nSubtotal: $99.98\nTax: $10.00\nGrand Total: $109.98\n\nThank you for your business!\n\nBest regards,\nSales Team" }, "email_notifications": [ { "to": "jane@example.com", "subject": "Invoice INV-1762270612772-2 - Order Confirmation", "body": "Dear Customer,\n\nThank you for your order!\n\nInvoice ID: INV-1762270612772-2\nOrder Date: 1/14/2025\n\nSubtotal: $89.99\nTax: $9.00\nGrand Total: $98.99\n\nThank you for your business!\n\nBest regards,\nSales Team" } ], "message": "All invoices processed and customers notified" } ❌ Validation Error (HTTP 400) Occurs when the CSV file is missing required columns or contains invalid data. { "success": false, "message": "CSV validation failed", "error": "Validation failed: [ { \"row\": 2, \"errors\": [\"Valid email is required\"] } ]" } 🧠 How It Works Webhook receives uploaded CSV or raw text Code node parses and validates data Data table node loads product info (price, tax rate) Calculation node generates invoice totals per customer Duplicate check prevents reprocessing Data table insert saves invoices Email preparation creates personalized confirmations Webhook response returns structured JSON (200 / 400 / 409) 🔐 Requirements n8n version ≥ 1.41.0 Data tables** feature enabled Publicly accessible webhook URL (for testing) (Optional) Connect a real email node (Gmail or SMTP) to send messages 🏁 Result Highlights Full CSV → Validation → Data tables → Email → JSON Response pipeline Includes built-in structured error handling (400 / 409) 100% native n8n functionality** Perfect example of Data tables + logic-based automation for business use cases

Premium n8n Workflow: SMART AI Keyword Categorization & Content Strategy This n8n workflow transforms raw keyword data into actionable content intelligence using advanced AI categorization and clustering. It creates a comprehensive content strategy with ready-to-use titles and descriptions for your blog posts. 🚀 Features 🧠 AI-Powered Categorization Automatically sorts keywords into strategic buckets — Quick Wins, Authority Builders, Emerging Topics, Intent Signals, and Semantic Topics — for targeted content creation 🎯. 🔗 Semantic Clustering Identifies meaningful relationships between keywords to create logically grouped content clusters 🕸️. 📑 Content Blueprint Generation Creates compelling titles and descriptions for each keyword and cluster to streamline your content creation process 📝. 🌐 Hub & Spoke Strategy Builder Develops a complete site architecture plan with main hub articles and supporting spoke content 🏗️. ⚡ Airtable Integration Organizes all outputs in a structured database for seamless integration with your content workflow. 🤖 n8n AI Agents Leverages advanced AI capabilities to analyze keyword intent and potential without manual intervention. 👥 This Workflow is Perfect For: Content strategists 📊 SEO professionals 🔍 Content marketing teams 👥 Blog managers 💻 Digital publishers 📰 Website owners (E-Commerce) 🏢 Anyone using the SMART AI Keyword Research Workflow 🔄 Stop struggling with manual keyword grouping and transform your raw keyword data into a comprehensive content strategy. 👉 Get this premium workflow today! 📝 What's Included? ⚙️ n8n Workflow Template Ready-to-use workflow with AI-powered nodes for keyword analysis and categorization. 📊 Airtable Database Structure Pre-configured tables for categorized keywords, content ideas, and hub-spoke relationships. 🧩 Keyword Categorization System Automated logic to sort keywords by opportunity, competition, and relevance. 📋 Content Titles and Descriptions AI prompts to create optimized titles and descriptions for each content piece. 🌐 Hub & Spoke Mapper Logic to identify main topics and supporting content opportunities. 📚 Documentation Step-by-step instructions for importing keyword data and running the workflow. 🏆 Why Choose This Workflow? ⏱️ Save Massive Time: Automate what would take days of manual analysis and planning. 📈 Improve Content ROI: Create content that targets the right keywords in the right way. 🔄 Seamless Integration: Works perfectly with the AI Keyword Research and Blog Writing workflows available on my profile. 🏗️ Build Site Authority: Create topically relevant content clusters that boost domain expertise. 🎯 Strategic Focus: Stop guessing which keywords to target and how to organize your content. 🛠️ How It Works 1️⃣ Import the provided n8n workflow into your n8n instance 📥. 2️⃣ Connect to your Airtable base containing keyword research data ⚙️. 3️⃣ Configure the AI agents with your preferred content parameters 🤖. 4️⃣ Run the workflow to automatically categorize, cluster, and create content briefs 🔄. 5️⃣ Use the generated content strategy to guide your blogging or feed directly into the Multi-Agent Blog Writing System available on my profile 📝. Additional detailed instructions are provided in the workflow. 🏁 What You Need to Get Started 🔹 Access to n8n (self-hosted or cloud) ☁️ 🔹 An Airtable account with keyword data (ideally from the AI Keyword Research Workflow on my profile) 📊 🔹 OpenAI API credentials for the AI categorization and title generation 🔑 🔹 Basic understanding of content strategy and n8n workflows 🧠 💡 You can also connect this workflow with my SEO Keyword Research Automation using DataForSEO and Airtable and my Multi-Agent SEO Optimized Blog Writing System with Hyperlinks for E-Commerce, both available on my profile, to build a fully automated, end-to-end SEO content machine.