Workflow Templates

This guide walks you through setting up an AI-driven workflow to automate flight and hotel reservation processes using a conversational travel booking system. The workflow accepts booking requests, processes them via APIs, and sends confirmations, enabling a seamless travel booking experience. What’s the Goal? Automatically accept and process booking requests for flights and hotels via HTTP POST. Use AI to understand natural language requests and route them to appropriate data processors. Search for flights and hotels using external APIs and process booking confirmations. Send confirmation emails and return structured booking data to users. Enable an automated system for efficient travel reservations. By the end, you’ll have a self-running system that handles travel bookings effortlessly. Why Does It Matter? Manual booking processes are time-consuming and prone to errors. This workflow offers: Zero Human Error**: AI ensures accurate request parsing and booking processing. Time-Saving Automation**: Automates the entire booking lifecycle, boosting efficiency. Seamless Confirmation**: Sends automated emails and responses without manual intervention. Enhanced User Experience**: Provides a conversational interface for bookings. Think of it as your reliable travel booking assistant that keeps the process smooth and efficient. How It Works Here’s the step-by-step flow of the automation: Step 1: Trigger the Workflow Webhook Trigger**: Accepts incoming booking requests via HTTP POST, initiating the workflow. Step 2: Parse the Request AI Request Parser**: Uses AI to understand natural language booking requests (e.g., flight or hotel) and extracts relevant details. Step 3: Route Booking Type Booking Type Router**: Determines whether the request is for a flight or hotel and routes it to the respective data processor. Step 4: Process Flight Data Flight Data Processor**: Handles flight-specific data and prepares it for the search API. Step 5: Search Flight API Flight Search API**: Searches for available flights based on parameters (e.g., https://api.aviationstack.com) and returns results. Step 6: Process Hotel Data Hotel Data Processor**: Handles hotel-specific data and prepares it for the search API. Step 7: Search Hotel API Hotel Search API**: Searches for available hotels based on parameters (e.g., https://api.booking.com) and returns results. Step 8: Process Flight Booking Flight Booking Processor**: Processes flight bookings and generates confirmation details. Step 9: Process Hotel Booking Hotel Booking Processor**: Processes hotel bookings and generates confirmation details. Step 10: Generate Confirmation Message Confirmation Message Generator**: Creates structured confirmation messages for the user. Step 11: Send Confirmation Email Send Confirmation Email**: Sends booking confirmation via email to the user. Step 12: Send Response Send Response**: Returns structured booking data to the user, completing the workflow. How to Use the Workflow? Importing the workflow in n8n is a straightforward process. Follow these steps to import the Conversational Travel Booker workflow: Download the Workflow: Obtain the workflow file (e.g., JSON export from n8n). Open n8n: Log in to your n8n instance. Import Workflow: Navigate to the workflows section, click "Import," and upload the workflow file. Configure Nodes: Adjust settings (e.g., API keys, webhook URLs) as needed. Execute Workflow: Test and activate the workflow to start processing bookings. Requirements n8n account and instance setup. Access to flight and hotel search APIs (e.g., Aviationstack, Booking.com). Email service integration for sending confirmations. Webhook URL for receiving booking requests. Customizing this Workflow Modify the AI Request Parser to handle additional languages or booking types. Update API endpoints in Flight Search API and Hotel Search API nodes to match your preferred providers. Adjust the Send Confirmation Email node to include custom email templates or additional recipients. Schedule the Webhook Trigger to align with your business hours or demand peaks.

Who is this for? For developers and organizations that need to convert PPTX files to PDF. What problem is this workflow solving? The file format conversion problem. What this workflow does Downloads the PPTX file from the web. Converts the PPTX file to PDF. Stores the PDF file in the local file system. How to customize this workflow to your needs Open the HTTP Request node. Adjust the URL parameter (all endpoints can be found here). Add your secret to the Query Auth account parameter. Please create a ConvertAPI account to get an authentication secret. Optionally, additional Body Parameters can be added for the converter.

This workflow allows you to send position updates of the ISS every minute to a topic in MQTT using the MQTT node. Cron node: The Cron node will trigger the workflow every minute. HTTP Request node: This node will make a GET request to the API https://api.wheretheiss.at/v1/satellites/25544/positions to fetch the position of the ISS. This information gets passed on to the next node in the workflow. Set node: We will use the Set node to ensure that only the data that we set in this node gets passed on to the next nodes in the workflow. AWS SQS: This node will send the data from the previous node to the iss-position topic. If you have created a topic with a different one, you can use that topic instead.

BACKGROUND Malaysia's Inland Revenue (LHDN) provides an API to get the tax id number for a business entity, based on a given Business Registration number (BRN or SSM), or NRIC (MyKad). PROBLEM However, the API only allows one search at a time. SOLUTION This free workflow lets you do a batch search to get TIN for multiple SSM or NRIC. This is useful if you need to prepare your internal DB for e-invoicing PRE-REQUISITES 1) Get your connection client id and client secret from myhasil.gov.my website 2) Prepare your Google Sheet containing a list of SSM and NRIC you want to get the TIN 3) Create N8N credential to connect to your google sheet above SUPPORT Questions? Ask alex at halfborg dot com

Bearer Token Validation This n8n template helps you manage and validate tokens easily using: n8n as your backend workflow engine Airtable as your lightweight token store 🚀 What It Does Stores user tokens securely in Airtable with expiry or usage metadata. Validates incoming tokens in your workflows (e.g., webhook APIs). Rejects invalid or expired tokens automatically for security. Can be extended to generate, rotate, or revoke tokens for user management. How It Works Webhook node receives requests with a Bearer header. Airtable Query looks up the provided token. Validation Logic (Code node): Checks if the token exists. Verifies expiry or usage limits if configured. Returns success if valid, or error if error with describing the issue. Note: This is the simplest way to do auth, just for simplification Why Use This No need for a full backend to manage secure token validation. Clean, modular, and ready for your SaaS workflows. Enjoy building secure automations with n8n + Airtable! 🚀 Built by: Nazmy

Google Maps Email Scraper System Most lead generation tools charge $2–$5 per lead and lock you into expensive subscriptions. This workflow lets you scrape unlimited business emails from Google Maps for free — no paid APIs required. Benefits Zero API costs – scrape data directly from Google Maps Unlimited leads – extract thousands of emails per day Geographic targeting – search by city, region, or business type Complete automation – from search to clean email list Built-in data cleaning – removes duplicates & invalid entries How It Works Reads search queries from a Google Sheet (e.g., "Calgary dentist") Sends HTTP requests to Google Maps and scrapes business listings Extracts website URLs with custom JavaScript regex Visits each site, scrapes HTML, and finds email addresses Cleans and validates data Exports organized lead list back to Google Sheets Who Is This For B2B sales teams generating leads for outreach Marketing agencies building client lead databases Local businesses researching competitors & partners Real estate professionals analyzing target neighborhoods Franchise developers scouting new markets Setup Create a Google Sheet with two tabs: “searches” & “emails” Add search queries to the “searches” tab (one per row) Connect Google Sheets OAuth credentials in n8n Configure HTTP request nodes with SSL ignore enabled Add custom JavaScript regex code for URL and email extraction ROI & Monetization $0 per lead vs. $2–$5 from paid tools Generate 1,000+ leads per day without hitting API limits Sell lead lists or offer as a $500–$2,000 per niche/location service Perfect upsell for agencies offering outreach or local SEO Strategy Insights In the YouTube walkthrough, I show how to: Write custom JavaScript + regex for clean URL extraction Build a robust loop system with error handling & rate limiting Avoid IP blocking with batching & delays Sell lead generation as a high-margin recurring service Automate outreach to monetize the leads you scrape Check Out My Channel For more advanced AI automation systems that generate real business results, check out my YouTube channel where I share the exact strategies I use to build automation agencies, sell high-value services, and scale to $20k+ monthly revenue.

Knowledge RAG & AI Chat Agent: Google Drive to Qdrant Description This workflow transforms a Google Drive folder into an intelligent, searchable knowledge base and provides a chat agent to query it. It’s composed of two distinct flows: An ingestion pipeline to process documents. A live chat agent that uses RAG (Retrieval-Augmented Generation) and optional web search to answer user questions. This system fully automates the creation of a “Chat with your docs” solution and enhances it with external web-searching capabilities. Quick Implementation Steps Import the workflow JSON into your n8n instance. Set up credentials for Google Drive, Mistral AI, OpenAI, and Qdrant. Open the Web Search node and add your Tavily AI API key to the Authorization header. In the Google Drive (List Files) node, set the Folder ID you want to ingest. Run the workflow manually once to populate your Qdrant database (Flow 1). Activate the workflow to enable the chat trigger (Flow 2). Copy the public webhook URL from the When chat message received node and open it in a new tab to start chatting. What It Does The workflow is divided into two primary functions: 1. Knowledge Base Ingestion (Manual Trigger) This flow populates your vector database. Scans Google Drive:** Lists all files from a specified folder. Processes Files Individually:** Downloads each file. Extracts Text via OCR:* Uses *Mistral AI OCR API** for text extraction from PDFs, images, etc. Generates Smart Metadata:** A Mistral LLM assigns metadata like document_type, project, and assigned_to. Chunks & Embeds:* Text is cleaned, chunked, and embedded via *OpenAI’s text-embedding-3-small** model. Stores in Qdrant:** Text chunks, embeddings, and metadata are stored in a Qdrant collection (docaiauto). 2. AI Chat Agent (Chat Trigger) This flow powers the conversational interface. Handles User Queries:** Triggered when a user sends a chat message. Internal RAG Retrieval:* Searches *Qdrant Vector Store** first for answers. Web Search Fallback:* If unavailable internally, the agent offers to perform a *Tavily AI web search**. Contextual Responses:** Combines internal and external info for comprehensive answers. Who's It For Ideal for: Teams building internal AI knowledge bases from Google Drive. Developers creating AI-powered support, research, or onboarding bots. Organizations implementing RAG pipelines. Anyone making unstructured Google Drive documents searchable via chat. Requirements n8n instance** (self-hosted or cloud). Google Drive Credentials** (to list and download files). Mistral AI API Key** (for OCR & metadata extraction). OpenAI API Key** (for embeddings and chat LLM). Qdrant instance** (cloud or self-hosted). Tavily AI API Key** (for web search). How It Works The workflow runs two independent flows in parallel: Flow 1: Ingestion Pipeline (Manual Trigger) List Files: Fetch files from Google Drive using the Folder ID. Loop & Download: Each file is processed one by one. OCR Processing: Upload file to Mistral Retrieve signed URL Extract text using Mistral DOC OCR Metadata Extraction: Analyze text using a Mistral LLM. Text Cleaning & Chunking: Split into 1000-character chunks. Embeddings Creation: Use OpenAI embeddings. Vector Insertion: Push chunks + metadata into Qdrant. Flow 2: AI Chat Agent (Chat Trigger) Chat Trigger: Starts when a chat message is received. AI Agent: Uses OpenAI + Simple Memory to process context. RAG Retrieval: Queries Qdrant for related data. Decision Logic: Found → Form answer. Not found → Ask if user wants web search. Web Search: Performs Tavily web lookup. Final Response: Synthesizes internal + external info. How To Set Up 1. Import the Workflow Upload the provided JSON into your n8n instance. 2. Configure Credentials Create and assign: Google Drive** → Google Drive nodes Mistral AI** → Upload, Signed URL, DOC OCR, Cloud Chat Model OpenAI** → Embeddings + Chat Model nodes Qdrant** → Vector Store nodes 3. Add Tavily API Key Open Web Search node → Parameters → Headers Add your key under Authorization (e.g., tvly-xxxx). 4. Node Configuration Google Drive (List Files):** Set Folder ID. Qdrant Nodes:** Ensure same collection name (docaiauto). 5. Run Ingestion (Flow 1) Click Test workflow to populate Qdrant with your Drive documents. 6. Activate Chat (Flow 2) Toggle the workflow ON to enable real-time chat. 7. Test Open the webhook URL and start chatting! How To Customize Change LLMs:** Swap models in OpenAI or Mistral nodes (e.g., GPT-4o, Claude 3). Modify Prompts:** Edit the system message in ai chat agent to alter tone or logic. Chunking Strategy:** Adjust chunkSize and chunkOverlap in the Code node. Different Sources:** Replace Google Drive with AWS S3, Local Folder, etc. Automate Updates:* Add a *Cron** node for scheduled ingestion. Validation:** Add post-processing steps after metadata extraction. Expand Tools:** Add more functional nodes like Google Calendar or Calculator. Use Case Examples Internal HR Bot:** Answer HR-related queries from stored policy docs. Tech Support Assistant:** Retrieve troubleshooting steps for products. Research Assistant:** Summarize and compare market reports. Project Management Bot:** Query document ownership or project status. Troubleshooting Guide | Issue | Possible Solution | |------------|------------------------| | Chat agent doesn’t respond | Check OpenAI API key and model availability (e.g., gpt-4.1-mini). | | Known documents not found | Ensure ingestion flow ran and both Qdrant nodes use same collection name. | | OCR node fails | Verify Mistral API key and input file integrity. | | Web search not triggered | Re-check Tavily API key in Web Search node headers. | | Incorrect metadata | Tune Information Extractor prompt or use a stronger Mistral model. | Need Help or More Workflows? Want to customize this workflow for your business or integrate it with your existing tools? Our team at Digital Biz Tech can tailor it precisely to your use case from automation logic to AI-powered enhancements. 💡 We can help you set it up for free — from connecting credentials to deploying it live. Contact: shilpa.raju@digitalbiz.tech Website: https://www.digitalbiz.tech LinkedIn: https://www.linkedin.com/company/digital-biz-tech/ You can also DM us on LinkedIn for any help.

This n8n workflow provides a comprehensive solution for user authentication and management, leveraging Airtable as the backend database. It includes flows for user sign-up and login, aswell as the sample crud operations retrieving user details, and updating user information. Youtube Video of me explaining the flow: https://www.youtube.com/watch?v=gKcGfyq3dPM How it Works User Sign-Up Flow Receives POST request: A webhook listens for POST requests containing new user details (email, first name, last name, password). Checks for existing email: The workflow queries Airtable to see if the submitted email already exists. Handles email in use: If the email is found, it responds with {"response": "email in use"}. Creates new user: If the email is unique, the password is SHA256 hashed (Base64 encoded), and the user's information (including the hashed password) is stored in Airtable. A successful response of {"response": "success"} is then sent. User Login Flow Receives POST request: A webhook listens for POST requests with user email and password for login. Verifies user existence: It checks Airtable for a user with the provided email. If no user is found, it responds with a failure message ("wrong email"). Compares passwords: If a user is found, the submitted password is hashed (SHA256, Base64 encoded) and compared with the stored hashed password in Airtable. Responds with JWT or error: If passwords match, a JWT token containing the user's ID and email is issued. If they don't match, a "wrong password" response is sent. Flows for a Logged-In User These flows require a JWT-authenticated request. Get User Details:** Webhook (GET): Receives a JWT-authenticated request. Airtable (Read): Fetches the current user’s record using the jwtPayload.id. Set Node ("Specify Current Details"): Maps fields like "First Name," "Last Name," "Email," and "Date" from Airtable to a standard output format. Update User Details:** Webhook (POST): Receives updated user data (email, name, password). Airtable (Upsert): Updates the record matching jwtPayload.id using the submitted fields. Set Node ("Specify New Details"): Outputs the updated data in a standard format. Set Up Steps (Approx. 5 Minutes) Step 1: Set up your Airtable Base and Table You'll need an Airtable Base and a table to store your user data. Ensure your table has at least the following columns: Email** (Single Line Text) First Name** (Single Line Text) Last Name** (Single Line Text) Password** (Single Line Text - this will store the hashed password) Date** (Date - optional, for user sign-up date) Step 2: Obtain an Airtable Personal Access Token Go to the Airtable website and log in to your account. Navigate to your personal access token page (usually found under your developer settings or by searching for "personal access tokens"). Click "Create new token." Give your token a name (e.g., "n8n User Management"). Grant necessary permissions: Scope: data.records:read, data.records:write for the specific base you will be using. Base: Select the Airtable base where your user management table resides. Generate the token and copy it immediately. You won't be able to see it again. Store it securely. Step 3: Create a JWT Auth Credential in n8n In your n8n instance, go to "Credentials" (usually found in the left-hand sidebar). Click "New Credential" and search for "JWT Auth". Give the credential a name (e.g., "UserAuthJWT"). For the "Signing Secret," enter a strong, random string of characters. This secret will be used to sign and verify your JWT tokens. Keep this secret highly confidential. Save the credential. Customization Options This workflow is designed to be highly adaptable: Database Integration**: Easily switch from Airtable to other databases like PostgreSQL, MySQL, MongoDB, or even Google Sheets by replacing the Airtable nodes with the appropriate database nodes in n8n. Authentication Methods**: Extend the authentication to include multi-factor authentication (MFA), social logins (Google, Facebook), or integrate with existing identity providers (IdP) by adding additional nodes. User Profile Fields**: Add or remove user profile fields (e.g., phone number, address, user roles) by adjusting the Airtable table columns and the Set nodes in the workflow. Notification System**: Integrate notification systems (e.g., email, SMS) for events like new user sign-ups, password resets, or account changes. Admin Panel**: Build an admin panel using n8n to manage users directly, including functionalities for adding, deleting, or updating user records, and resetting passwords. This workflow provides a solid foundation for building robust user management systems, adaptable to a wide range of applications and security requirements. Need Assistance or Customization? Do you have specific integrations in mind, or are you looking to add more user management features to this workflow? If you need help setting this up, or want to adapt it for a unique use case, don't hesitate to reach out! You can contact me directly at nanabrownsnr@gmail.com. I'd be glad to assist you.

What does this template do? This workflow sets a small "lock" value in Redis so that only one copy of a long job can run at the same time. If another trigger fires while the job is still busy, the workflow sees the lock, stops early, and throws a clear error. This protects your data and keeps you from hitting rate limits. Because the workflow also stores simple progress flags ("working", "loading", "finishing"), you can poll the current status and show live progress for very long jobs. Use Case Great when the same workflow can be called many times in parallel (for example by webhooks, cron jobs, or nested Execute Workflow calls) and you need an "only run once at a time" guarantee without building a full queue system. What the Workflow Does ⚡ Starts through Execute Workflow Trigger called by another workflow 🔄 A Switch sends the run to Get, Set, or Unset actions 💾 Redis reads or writes a key named process_status_<key> with a time‑to‑live (default 600 s) 🚦 If nodes check the key and decide to continue or stop ⏱️ Wait nodes stand in for the slow part of your job (replace these with your real work) 📈 Updates the key with human‑readable progress values that another workflow can fetch with action = get 🏁 When done, the lock is removed so the next run can start Apps & Services Used Redis Core n8n nodes (Switch, If, Set, Wait, Stop and Error) Pre‑requisites A Redis server that n8n can reach Redis credentials stored in n8n A second workflow that calls this one and sends: action set to get, set, or unset key set to a unique name for the job Optional timeout in seconds Customization Tips Increase or decrease the TTL in the Set Timeout node to match how long your job usually runs Add or rename status values ("working", "loading", "finishing", and so on) to show finer progress Replace Stop and Error with a Slack or email alert, or even push the extra trigger into a queue if you prefer waiting instead of failing Use different Redis keys if you need separate locks for different tasks Build a small "status endpoint" workflow that calls this one with action = get to display real‑time progress to users Additional Use Cases 🛑 Telegram callback spam filter If a Telegram bot sends many identical callbacks in a burst, call this workflow first to place a lock. Only the first callback will proceed; the rest will exit cleanly until the lock clears. This keeps your bot from flooding downstream APIs. 🧩 External API rate‑limit protection Run heavy API syncs one after the other so parallel calls do not break vendor rate limits. 🔔 Maintenance window lock Block scheduled maintenance tasks from overlapping, making sure each window finishes before the next starts.

Overview Transform your customer support operations with an intelligent WhatsApp automation system that handles text, voice, and image messages across multiple languages. This comprehensive solution uses advanced AI to provide instant, accurate responses by accessing your company's knowledge base, while maintaining conversation context and supporting both English and Roman Urdu communications. Perfect for businesses serving diverse markets who need 24/7 customer support without the overhead costs. Key Benefits 🤖 Multi-Modal AI Processing Handle text messages, voice notes, and images seamlessly. The system automatically transcribes audio, analyzes images, and processes all content types through a single intelligent pipeline. 🌍 True Multilingual Support Native support for English and Roman Urdu with intelligent language detection and matching responses. The AI automatically detects the customer's language and responds accordingly, making it perfect for South Asian markets. 📚 Dynamic Knowledge Base Integration Real-time access to your Google Docs knowledge base ensures customers always receive current, accurate information about your products and services. No more outdated responses or manual updates needed. 💭 Conversation Memory & Context Advanced memory system maintains conversation history for natural, contextual interactions. Customers can have flowing conversations without repeating information, improving satisfaction rates. ⚡ Instant Response Times Automated responses within seconds of receiving messages, dramatically improving customer satisfaction and reducing response time from hours to seconds. 🔄 Zero Manual Intervention Fully automated system that works 24/7 without human oversight. Handles inquiries, provides information, and maintains professional communication standards automatically. 📊 Scalable Architecture Built on enterprise-grade n8n platform with robust error handling and retry mechanisms. Can handle thousands of concurrent conversations without performance degradation. 💰 Cost-Effective Operations Replace expensive customer support teams with intelligent automation. Reduce operational costs by up to 80% while improving response quality and availability. How It Works Phase 1: Message Reception & Classification The system begins with a WhatsApp webhook trigger that captures all incoming messages in real-time. An intelligent switch node immediately analyzes each message to determine its content type - whether it's a text message, voice note, or image with optional caption. This classification is crucial as each media type requires different processing approaches to extract meaningful information. Phase 2: Advanced Media Processing For voice messages, the system retrieves the audio file URL, downloads the content using authenticated requests, and processes it through OpenAI's Whisper transcription service to convert speech to text. Image messages follow a similar pattern - the system downloads the image and uses GPT-4 Vision to analyze and describe the visual content in detail. Text messages are processed directly, while all media types are ultimately converted to standardized text format for consistent AI processing. Phase 3: Intelligent Response Generation The processed content is fed into a sophisticated AI agent powered by Claude Sonnet 4 via OpenRouter. This agent operates with a comprehensive system prompt that defines its role as a professional customer support representative with specific instructions for tone, language handling, and response protocols. The agent has access to a Google Docs tool that allows it to retrieve real-time information from your company's knowledge base. Phase 4: Contextual Memory Management A memory buffer system maintains conversation history for each unique phone number, allowing for natural, flowing conversations where the AI remembers previous interactions and can reference earlier parts of the conversation. This creates a more human-like experience and reduces customer frustration from having to repeat information. Phase 5: Response Delivery Generated responses are automatically sent back to the customer's WhatsApp number using the WhatsApp Business API, completing the conversation loop. The system maintains proper formatting and ensures message delivery confirmation. Required Setup & Database Requirements API Credentials Needed: WhatsApp Business API**: For receiving and sending messages OpenAI API**: For audio transcription and image analysis OpenRouter API**: For Claude Sonnet 4 language model access Google Docs API**: For knowledge base integration n8n Cloud/Self-hosted instance**: For workflow execution Knowledge Base Setup: Google Docs Document**: Structured company information document Document Permissions**: Shared with the Google service account Content Organization**: FAQ format with clear sections for products, services, pricing, and contact information WhatsApp Configuration: Business Phone Number**: Verified WhatsApp Business account Webhook URL**: Configured to point to n8n webhook endpoint Message Templates**: Pre-approved for business communications Business Use Cases E-commerce Support: Handle product inquiries, order status checks, and return policies across multiple languages, perfect for businesses serving diverse customer bases. Service Business Automation: Appointment scheduling, service explanations, and pricing inquiries for consultancies, agencies, and professional services. Restaurant & Food Industry: Menu inquiries, order modifications, and delivery status updates with support for local language preferences. Real Estate: Property inquiries, showing appointments, and market information with ability to process property images sent by clients. Healthcare & Wellness: Appointment booking, service explanations, and general inquiries while maintaining professional communication standards. Education & Training: Course information, enrollment processes, and student support with multilingual capabilities for international programs. Revenue Potential Direct Cost Savings: $3,000-8,000/month in customer support staff salaries Increased Conversion: 25-40% improvement in lead response rates due to instant replies Extended Availability: 24/7 operation captures international and after-hours inquiries worth $2,000-5,000/month additional revenue Scalability: Handle 10x more inquiries without proportional cost increases Customer Satisfaction: Improved response times lead to 15-30% increase in customer retention ROI Timeline: Typical payback period of 2-3 months with ongoing monthly savings of $4,000-12,000 depending on business size. Difficulty Level & Build Time Complexity: Intermediate to Advanced (7/10) Estimated Build Time: 4-6 hours for experienced n8n users Setup Time: 2-3 hours for API configurations and testing Maintenance: Minimal - primarily updating knowledge base content Skills Required: n8n workflow building experience API credential management WhatsApp Business API familiarity Basic understanding of AI language models Detailed Setup Steps 1. API Account Setup (60 minutes) Create and configure accounts for WhatsApp Business, OpenAI, OpenRouter, and Google Cloud Platform. Obtain all necessary API keys and configure proper permissions for each service. 2. n8n Credential Configuration (30 minutes) Add all API credentials to your n8n instance using the credential manager. Test each connection to ensure proper authentication and access permissions. 3. WhatsApp Business Integration (45 minutes) Configure your WhatsApp Business account with webhook URLs pointing to your n8n instance. Set up phone number verification and message template approvals. 4. Knowledge Base Creation (90 minutes) Structure your Google Docs knowledge base with comprehensive information about your business. Include FAQs, product details, pricing, and contact information in an organized format. 5. Workflow Import & Testing (60 minutes) Import the n8n workflow, configure all node parameters with your specific credentials and settings, then conduct thorough testing with different message types and languages. 6. Production Deployment (30 minutes) Deploy the workflow to production, monitor initial performance, and fine-tune system prompts based on real customer interactions. Advanced Customization Options Custom Language Support: Extend beyond English and Roman Urdu by modifying the system prompt and adding language detection for additional languages like Arabic, Hindi, or French. Integration Expansions: Connect additional data sources like CRM systems, databases, or e-commerce platforms to provide more comprehensive customer information. Advanced Analytics: Add logging nodes to track conversation metrics, response times, and customer satisfaction scores for continuous improvement. Multi-Channel Support: Extend the system to handle Telegram, Facebook Messenger, or other messaging platforms using similar processing logic. Escalation Protocols: Implement human handoff triggers for complex queries that require personal attention, with automatic notification systems for support teams. Custom AI Models: Swap Claude Sonnet 4 for other models like GPT-4, Gemini, or open-source alternatives based on your specific needs and budget requirements. This automation system represents the future of customer support - intelligent, scalable, and incredibly cost-effective while maintaining the personal touch that customers expect from quality businesses.

WordPress Blog to Google Sheets Sync Posts • Categories • Tags • Media 🧩 Overview This n8n workflow automatically syncs your WordPress website content — including posts, categories, tags, and media — into Google Sheets. It helps automate content reporting, SEO analysis, and data backups. The workflow can run on schedule or on demand via a webhook. 💡 Use cases Maintain a live database of blog posts in Google Sheets. Create dashboards in Google Data Studio or Looker Studio. Track new articles for newsletters or social media scheduling. Backup all WordPress content and media outside of your CMS. ⚙️ Prerequisites Before importing the workflow, ensure you have: A WordPress website with the REST API enabled (default in WP 4.7+). Authentication: either Application Passwords or Basic Auth credentials. A Google Sheet with the following tabs: Posts Categories Tags Media The following credentials configured in n8n: HTTP Basic Auth (for WordPress) Google Sheets OAuth2 🚀 Setup instructions Import the workflow into your n8n instance. Replace all example WordPress API URLs with your domain, for example: https://yourdomain.com/wp-json/wp/v2/ Connect your HTTP Basic Auth credentials (WordPress username + Application Password). Connect your Google Sheets OAuth2 account. Update the spreadsheet ID in each Google Sheets node with your own. Adjust the Schedule Trigger (e.g. run daily at 2:00 AM). Run once manually to verify data sync. 🧠 Workflow structure | Section | Description | |----------|--------------| | Schedule / Webhook Trigger | Starts the workflow manually or automatically | | Variables & Loop Vars | Initialize pagination for REST API requests | | Get Posts → Split Out → Update Posts | Fetch and update all WordPress posts | | Get Categories → Update Categories | Sync WordPress categories | | Get Tags → Update Tags | Sync WordPress tags | | Get Media → Split Out → Update Media | Sync media library (images, videos, etc.) | | IF Loops | Handles pagination logic until all items are retrieved | ⚠️ Notes & Limitations Works with standard WordPress REST API endpoints only. Custom post types require editing endpoint URLs. The per_page value defaults to 10; increase for faster syncs. For large sites, consider increasing n8n memory or adding execution logs. Avoid running the workflow too frequently to prevent API rate limits. 🎥 Video Tutorial A step-by-step setup guide is available here: 👉 https://www.youtube.com/watch?v=czSMWyD6f-0 Please subscribe to my YouTube channel to support me: 👉 https://www.youtube.com/@gregfrolovpersonal 👨‍💻 Author Created by: Grigory Frolov SEO & Automation Specialist — helping businesses integrate WordPress, AI, and data tools with n8n. 🧾 License This workflow is provided under the MIT License. Feel free to use, modify, and share improvements with the community.

This workflow can be used to save all of your workflows in: a raw state (as a json file in Dropbox) an Airtable base, in a pre-designed format. It runs periodically (currently, every 30 minutes) and either updates (if already existing in Airtable) or creates a new record in Airtable for each workflow. Here's the Airtable base to give you an idea: View Airtable base Note: This workflows uses the "http://localhost:5678/rest" API which the UI editor uses but is still not officially supported. Hence, it may suffer breaking changes at some point in the future and the workflow might become dysfunctional then.