Workflow Templates

Primer workflow for OpenAI models: ChatGPT, DALLE-2, Whisper This workflow contains 5 examples on how to work with OpenAI API. Transcribe voice into text via Whisper model (disabled, please put your own mp3 file with voice) The old way of using OpenAI conversational model via text-davinci-003 Examples 1.x. Simple ChatGPT calls. Text completion and text edit Example 2. Provide system and user content into ChatGPT Examples 3.x. Create system / user / assistanc content via Code Node. Promtp chaining technique example Example 4. Generate code via ChatGPT Example 5. Return multiple answers. Useful for providing picking the most relevant reply IMPORTANT! Do not run the whole workflow, it's rather slow Better execute the last node of each branch or simply disconnect branches that are not needed

Overview This n8n workflow is a modular AI analyst system that provides real-time insights from CoinMarketCap’s centralized and decentralized data sources. Using GPT-based AI, the system interprets natural language questions about the crypto market and delegates them to specialized agent workflows. It supports Telegram chat input and returns structured results such as coin quotes, DEX liquidity, exchange info, and community sentiment—all integrated from the CoinMarketCap API ecosystem. Prerequisites a. OpenAI or Gemini account (via GPT-4o-mini or equivalent LLM). b. Telegram Bot API token (for message input/output). c. Valid CoinMarketCap API key. 📦 Required subflows: CoinMarketCap_Crypto_Agent_Tool CoinMarketCap_Exchange_and_Community_Agent_Tool CoinMarketCap_DEXScan_Agent_Tool d. All tools must be installed and configured before use. Each one acts as a specialized endpoint wrapper for CoinMarketCap APIs. How It Works Telegram Input Users send a query to the bot (e.g. “Top DEX pairs on Ethereum”). Session Memory & Agent Brain Session is tracked via chat.id GPT-4o-mini interprets the query, routes to sub-agents Sub-Agent Workflows Crypto Agent: prices, rankings, conversions Exchange Agent: community sentiment, exchange token holdings DEX Agent: OHLCV data, liquidity pools, trades Multi-Agent Coordination AI can combine queries across tools (e.g., get token ID → fetch quote → analyze liquidity) Ensures valid parameters and avoids API errors Telegram Output Final analysis is sent back to the user as a formatted message. Troubleshooting Tips Error Code Meaning Fix 400 Bad request Check symbol/slug/ID validity 401 Unauthorized Verify CoinMarketCap API key 429 Rate limit exceeded Throttle or upgrade API tier 500 Server error Retry with backoff or report to CMC Example Telegram Queries “Show me top 5 coins by market cap” “Get price of ETH on Uniswap and Binance” “How much liquidity is in SOL-USDC pair?” “Fear & Greed Index and trending tokens” SEO Tags (ẩn hoặc ghi chú riêng): coinmarketcap, n8n crypto analyst, crypto ai telegram bot, dex liquidity, CMC price tracker, gpt-4o crypto market, token sentiment dashboard, fear and greed index

Description This workflow automatically monitors online forums for specific keywords, topics, or competitor mentions. It helps you stay on top of relevant discussions without manually checking multiple forums throughout the day. Overview This workflow automatically monitors selected forums for new posts, keywords, or competitor activity. It uses Bright Data to scrape forum content and can notify you or save results to a spreadsheet or other service. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping forum content without getting blocked. (Optional) Google Sheets/Discord/Telegram:** For notifications or data storage. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Notifications (Optional): Configure notification/storage nodes as needed. Customize: Specify the forums and keywords to monitor. Use Cases Brand Monitoring:** Stay updated on mentions of your brand or product. Competitor Tracking:** Monitor competitor activity in your industry forums. Community Managers:** Get alerts for new threads or topics. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #forums #brightdata #webscraping #monitoring #forummonitoring #brandmentions #competitortracking #keywordtracking #n8nworkflow #workflow #nocode #communitymanagement #onlineforums #discussionboards #brandawareness #marketresearch #socialmediamonitoring #contentmonitoring #reputationmanagement #digitalmarketing #businessintelligence #onlinediscussions #competitoranalysis

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically monitors keyword rankings across search engines to track SEO performance and identify optimization opportunities. It saves you time by eliminating the need to manually check keyword positions and provides comprehensive ranking data for strategic SEO decision making. Overview This workflow automatically scrapes search engine results pages (SERPs) to track keyword rankings, competitor positions, and search features. It uses Bright Data to access search results without restrictions and AI to intelligently parse ranking data, track changes, and identify SEO opportunities. Tools Used n8n**: The automation platform that orchestrates the workflow Bright Data**: For scraping search engine results without being blocked OpenAI**: AI agent for intelligent ranking analysis and SEO insights Google Sheets**: For storing keyword ranking data and tracking changes How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Bright Data: Add your Bright Data credentials to the MCP Client node Set Up OpenAI: Configure your OpenAI API credentials Configure Google Sheets: Connect your Google Sheets account and set up your ranking tracking spreadsheet Customize: Define target keywords and ranking monitoring parameters Use Cases SEO Teams**: Track keyword performance and identify ranking improvements Content Marketing**: Monitor content ranking success and optimization needs Competitive Analysis**: Track competitor keyword rankings and strategies Digital Marketing**: Measure organic search performance and ROI Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #keywordrankings #seo #searchrankings #brightdata #webscraping #seotools #n8nworkflow #workflow #nocode #ranktracking #keywordmonitoring #seoautomation #searchmarketing #organicseo #seoresearch #rankinganalysis #keywordanalysis #searchengines #seomonitoring #digitalmarketing #serp #keywordtracking #seoanalytics #searchoptimization #rankingreports #keywordresearch #seoinsights #searchperformance

Who this is for This workflow is designed for Finance teams, accounting professionals, and automation engineers. Use Case: Automates processing of invoice submissions received via JotForm. Core Function:** Extracts structured data such as: Invoice number Client information Totals and tax amounts Line items or services Key Benefit:** Eliminates manual data entry, saving time and reducing human error. Automation Goal:** Streamline document handling with AI-powered PDF parsing and structured output generation. Ideal users include: Accounting or finance teams handling form-based invoice uploads Automation specialists using n8n for document processing Developers integrating invoice data into Google Sheets or CRMs What problem this workflow solves Manually extracting structured data from invoice PDFs submitted through JotForm is time-consuming, error-prone, and repetitive. This workflow solves that by: Automatically receiving the PDF through JotForm’s webhook Extracting structured fields (invoice number, company, client, line items, totals, etc.) using GPT-4-mini Saving the extracted data directly to Google Sheets Writing structured JSON data to disk for archival or further processing What this workflow does Webhook Trigger (JotForm → n8n) JotForm submission sends invoice data and attachment link to n8n. Parse Submission & Extract Metadata Extracts submission metadata (form ID, user details, invoice number, file link, etc.) using the Information Extractor node. Download PDF Attachment Fetches the uploaded PDF from JotForm’s secure file URL via the HTTP Request node, authenticated using a JotForm API key. Store & Process File Saves the invoice to disk and prepares it for AI processing. Extract Invoice Text Content Uses the Extract from File node to parse text from the PDF document. AI-Powered Structured Extraction (OpenAI GPT-4.1-mini) Sends the extracted text to a LangChain LLM Chain with a Structured Output Parser, ensuring consistent JSON output aligned with a defined schema. Save Extracted Data Writes structured JSON to disk Appends parsed results to Google Sheets for easy reporting Setup Instructions Prerequisites A JotForm account with a form containing an invoice PDF upload field You may build the invoice Jotform by leveraging the Jotform Templates A Google Sheets account with a connected spreadsheet OpenAI** n8n running locally or on a server with public webhook access (e.g. via loca.lt, ngrok, or n8n.cloud) Make sure to get the Jotform API Key via the Jotform Account API Key Steps Import the provided JSON into n8n Go to n8n → Workflows → Import from File/Clipboard Paste the provided JSON definition Configure Webhook Copy the webhook URL from the Webhook node Paste it into your JotForm’s Settings → Integrations → Webhook URL Set API Keys & Credentials Ensure the Jotform API key has been setup to download the Jotform PDF document Ensure your Google Sheets and OpenAI credentials are connected Test Submission Submit your JotForm with an invoice PDF n8n workflow will trigger automatically Check Outputs Open your Google Sheet to see structured invoice entries Check the disk folder (e.g., C:\Invoices) for JSON exports How to customize this workflow Change AI Model** Use the OpenAI Chat Model for Structured Data node. → Replace gpt-4.1-mini with gemini-1.5-pro or any other LLM node of your choice. Adjust Output Schema** Modify the Structured Output Parser node. → Edit the JSON schema to match your desired output fields and format. Save to a Different Location** In the Write the Structured Invoice to Disk node, → Update the file path pattern (e.g. /data/invoices/{{invoiceId}}.json). Log to a Database Instead of Google Sheets** Replace the Append or Update Row in Sheet node → with a MySQL or PostgreSQL node for database logging. Add Notifications** Extend the workflow by adding Slack or Email nodes → to send alerts when a new invoice extraction is completed. Summary The Structured Invoice Data Extraction from JotForm PDFs via Google Gemini, Converts JotForm-uploaded invoice PDFs into structured financial data automatically. Key Features: No manual parsing fully automated Works with any invoice layout via AI Saves structured results to Google Sheets + JSON file Extensible for CRMs, QuickBooks, or ERP sync

Reimbursements used to be a headache. Employees submitted receipts through emails, managers got stuck in approval chains, and finance teams spent hours checking for duplicates, updating sheets, and sending follow-up emails. So, we automated it. Using n8n, we built a smart Employee Reimbursement Workflow that does everything… in just a few clicks. Here’s how it works.] When an employee uploads a receipt, the workflow first checks for duplicates. If the file is new, it’s uploaded to Google Drive instantly. Next, a unique tracking ID is generated—no manual typing, no mistakes. Then, all the details are logged in Google Sheets in real time, ready for records. And finally, the Finance team gets an email notification with everything they need to process the payment—no chasing, no missing info. The impact? We’ve cut processing time by over 70%, reduced errors to nearly zero, and made the entire process stress-free for employees and finance alike. This isn’t just automation—it’s giving people their time back.

This n8n workflow dynamically generates a realistic sample dataset based on a single topic you provide. It uses OpenAI (via LangChain) and n8n’s built-in nodes to: Generate structured JSON data for 5 columns with 3–5 values each Flatten that data into a single text blob Infer meaningful column names via a second AI call Pivot, split, merge, and rename columns automatically Output a clean, labeled dataset ready for export or further processing ⚙️ Prerequisites OpenAI API Key Visit: https://platform.openai.com/account/api-keys Create a new key In n8n: Credentials → New → OpenAI API, paste key, name it “OpenAi account” LangChain nodes enabled in your n8n instance 🥇 Step 1: Set Up OpenAI Credential Go to OpenAI API Keys Create and copy your key In n8n: Credentials → New → OpenAI API → paste key as “OpenAi account” 🥈 Step 2: Manual Trigger Add Manual Trigger to start the workflow 🥉 Step 3: Set Topic Add a Set node named Set Topic to Search Field: Topic = n8n use cases (or any topic you choose) ✨ Step 4: Generate Structured Data LangChain Agent** node Generate Random Data Connect to OpenAI Chat Model1 and Tool: Inject Creativity1 System prompt: instruct AI to output 5 columns of realistic values in JSON 🔧 Step 5: Parse AI Output Structured Output Parser** to validate JSON 🔄 Step 6: Flatten Data Code** node Outpt all Data to One Field Joins all values into a comma-separated string for column naming 🧠 Step 7: Generate Column Names LangChain Agent** Generate Column Names Connect to OpenAI Chat Model2 Prompt: infer 5 column names from the string 🔢 Step 8: Pivot Names Row Code** node Pivot Column Names transforms array into { column1: name1, … } 🪓 Step 9: Split Columns 5 SplitOut nodes to break each array back into rows per column 🔗 Step 10: Merge Rows Merge** node Merge Columns together using combineByPosition 🏷️ Step 11: Rename Columns Set** node Rename Columns assigns the AI-generated names to each column 🔗 Step 12: Final Output Merge** Append Column Names combines data and header row 🏁 Done! You now have a fully AI-driven, labeled dataset generated from a single topic—no external services needed. Easily extend by adding a Google Sheets or HTTP node to export. 📬 Need Help or Want to Customize This? 📧 robert@ynteractive.com 🔗 LinkedIn

A next-generation AI-powered DeFi health monitor that tracks wallet positions across Aave V3 using GPT-4o and LangChain. It delivers human-readable reports via Telegram and Gmail, triggered on schedule or manually. Built for professionals monitoring multiple DeFi wallets. 🧩 System Components | Component | Role | | --------------------------------- | ------------------------------------------------------------- | | ✅ Scheduler | Triggers the workflow periodically | | ✅ Google Sheets Wallet Loader | Loads all monitored wallet addresses | | ✅ Set Variables | Injects dynamic wallet + date | | ✅ AAVE Portfolio AI Agent | GPT-4o + LangChain AI that generates human-readable summaries | | ✅ Moralis API Nodes (3) | Collect Aave V3 supply/borrow/collateral data | | ✅ OpenAI Chat Model (gpt-4o-mini) | Interprets on-chain data and explains it | | ✅ Telegram Delivery | Sends summary to Telegram chat | | ✅ Gmail Email Sender | Sends full HTML report to email | | ✅ HTML Formatter | Beautifies AI output into email structure | ⚙️ How It Works Scheduled or manual trigger Pulls wallet addresses from Google Sheets For each wallet: Pulls Aave data from Moralis GPT-4o AI generates report Sends summary to Telegram Sends full HTML report via Gmail 🛠 Installation Steps 1. Import the Workflow Upload AAVE_Portfolio_Professional_AI_Agent.json to your n8n instance. 2. Connect These Credentials | Service | Required Credential Type | | -------- | ---------------------------- | | Moralis | HTTP Header Auth (X-API-Key) | | OpenAI | GPT-4o via OpenAI API Key | | Telegram | Telegram Bot API Token | | Gmail | Gmail OAuth2 Credential | 3. Create Google Sheet Column name must be: wallet_address Add wallet addresses you want monitored 📬 Output Format Telegram Message Example 📊 Aave DeFi Health Report Wallet: 0xABC...123 Date: 2025-05-21 ▪️ Pool: Aave Ethereum USDC • Supply: $10,040 • Borrowed: $5,500 • Health Factor: 3.43 • Liquidation Risk: No Email Report Full HTML + plain text versions Auto-generated date + styled per wallet Includes notes and threshold warnings 🧠 Smart Features GPT-4o generates clear human summaries Monitors multiple wallets in one run Flags liquidation risk dynamically Logs daily performance snapshots 💡 Customization Ideas Add Telegram slash command /aave <wallet> Expand to monitor Compound, Lido, or Uniswap Export to Notion, Slack, or Data Studio 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and report formatting are intellectual property protected. No unauthorized rebranding, redistribution, or resale permitted. 🔗 For support or licensing inquiries: LinkedIn – Don Jayamaha 🚀 Track all your Aave DeFi positions using AI—delivered via Telegram + Gmail. Perfect for funds, traders, and DeFi power users. 🎥 Watch the Live Demo:

🖼️ Image-to-Image AI Generator from Google Sheets with Google Drive Upload ✅ Use Case Automatically generate AI images from prompts listed in a Google Sheet, upload the images to Google Drive, and log the result back into the sheet. Uses the image-to-image-gpt API for fast, customizable generation. 💡 Problem It Solves Manual image generation workflows are inefficient and error-prone. Creative and content teams often have to: Manually paste prompts into image generation tools Save images locally Upload to Google Drive Paste the link back into tracking spreadsheets This automation removes all that friction—turning one spreadsheet into a complete image creation pipeline. 🌟 Benefits 🔁 Fully automated image generation 📤 Direct uploads to Google Drive 🧾 Image links and timestamps logged in Google Sheets ⚠️ Built-in error logging for API failures 🧩 Modular and easily extensible 📊 Keeps a historical log of successes and errors 🧩 Workflow Overview | Node | Description | |------|-------------| | 1. Manual Trigger | Starts the workflow when executed manually | | 2. Google Sheets2 | Reads all rows from the input Google Sheet | | 3. Loop Over Items | Processes one row (prompt) at a time | | 4. If2 | Filters only rows where Prompt is not empty and drive path is empty | | 5. HTTP Request1 | Calls the image-to-image-gpt API with the prompt | | 6. If1 (Error Handling) | If an error exists in the API response, route to logging | | 7. Google Sheets4 (Error Log) | Appends error details to a log sheet for review | | 8. Code1 | Decodes the base64 image returned by the API | | 9. Google Drive1 | Uploads the image to a selected Google Drive folder | | 10. Google Sheets1 (Write Back) | Updates the original row with the image drive path and timestamp | | 11. Wait | Delays the next prompt to prevent hitting API rate limits | 🛠 Tech Stack n8n** (no-code automation) Google Sheets** (data input/output) Google Drive** (image storage) image-to-image-gpt API via RapidAPI JavaScript (in Code node)** for base64 processing 📝 Sheet Format Your Google Sheet should include the following columns: | Column | Purpose | |----------------|----------------------------------| | Prompt | The AI prompt to send to the API | | Image url | (Optional) Initial image URL | | drive path | Updated with Drive link by flow | | Generated Date | Auto-filled by the workflow | | Base64 | Stores raw or error data | 🚀 How to Use Import this workflow into your n8n instance Set up Google Sheets and Google Drive service credentials Add your RapidAPI key in the HTTP Request node headers Use the image-to-image-gpt endpoint in the HTTP request Configure the Google Sheet and Drive folder in the respective nodes Execute manually or add a Cron node for scheduling 📌 Example Applications 🛍 eCommerce: Auto-generate product mockups 🧵 Fashion/Design: Visualize styles or fabrics from prompts ✍️ Blogging/Content: Auto-generate header images from titles 📣 Marketing: Generate ad banners from text 🧪 Tips You can add a Cron node if you want this to run on a schedule Use a separate tab/sheet for logging failed prompts Extend the flow by adding: Email notifications Slack alerts File name templating Create your free n8n account and set up the workflow in just a few minutes using the link below: 👉 Start Automating with n8n Save time, stay consistent, and grow your LinkedIn presence effortlessly!

Workflow Overview This workflow automatically fetches the latest "Ask HN: Who is hiring?" posts from Hacker News, extracts individual job listings, cleans the raw text, converts them into structured job listings using Google Gemini AI, and saves them into Airtable. Components It’s a full end-to-end automation system combining: Algolia API** for HN data Text cleaning** Gemini AI (via LangChain)** for parsing job descriptions Structured JSON extraction** Airtable integration** to store the final data 🎯 Use Cases Automatically build a job board from HN posts Track startup hiring trends Feed remote job alerts into a CRM or Slack Enrich a hiring intelligence database 🔧 Nodes & Services Used HTTP Request (Algolia + Firebase API) SplitOut, Set, Filter, Function, Limit Google Gemini (via LangChain integration) Output Parser Structured Airtable (API token required) 📌 Credentials Required Google Gemini (PaLM/Gemini API) Airtable Personal Access Token Algolia Application ID & API Key (via Header Auth) 📦 Tags hacker-news, jobs, airtable, ai, gemini, automation, hn, langchain, workflow Screenshots

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.

AI-Powered Viral Video Factory 🚀 This workflow automates the entire process of creating short, cinematic, fact-based videos ready for social media. It takes a single concept, generates a script and visuals, creates video clips, adds a voiceover, and assembles a final video, which is then uploaded directly to your Google Drive. It's perfect for content creators and marketing agencies looking to scale video production with minimal manual effort. How It Works 🎬 Generate a Viral Idea 💡: The workflow begins with the Create New Idea1 (OpenAI) node, which generates a viral-ready video concept, including a punchy title, hashtags, and a brief description based on a core theme (e.g., space, black holes). This idea is then logged in a Google Sheet. Create a Cinematic Script & Voiceover 📜: An OpenAI node (Generating scenes1) creates a detailed 12-scene script, outlining the visuals for a 60-second video. The script text for all scenes is combined and prepared for voiceover generation by another OpenAI node (Generate Voiceover). Generate Scene-by-Scene Visuals ✨: The workflow loops through each of the 12 scenes to create an animated clip: Image Generation: An HTTP Request node sends the scene's prompt to the fal-ai/flux model to create a photorealistic still image. Animation Prompting: The Video Prompts1 (OpenAI Vision) node analyzes the generated image and creates a new, specific prompt to animate it cinematically. Image-to-Video: Another HTTP Request node uses the fal-ai/kling-video model to turn the still image into a 5-second animated video clip based on the new animation prompt. Assemble the Final Video 🎞️: Stitch Clips: Once all 12 clips are generated, the Merge Clips node uses the fal-ai/ffmpeg-api to concatenate them into a single, seamless 60-second video. Add Audio: The Combine Voice and Video node then layers the AI-generated voiceover onto the stitched video. Deliver to Google Drive 📂: Finally, the completed video is converted from a URL to a file and automatically uploaded to your specified Google Drive folder for easy access and publishing. Key Technologies Used n8n**: For orchestrating the entire automated workflow. OpenAI (GPT-4.1 & GPT-4o)**: For idea generation, scriptwriting, voiceover, and vision analysis. Fal.ai**: For high-performance, API-based image generation (Flux), video animation (Kling), and video processing (FFMPEG API). Google Drive & Sheets**: For logging ideas and storing the final video output. Setup Instructions Add Credentials: In n8n, add your OpenAI API key. Connect your Google account for Google Sheets and Google Drive access. You will need a Fal.ai API Key. Configure Fal.ai API Key: Crucially, you must replace the placeholder API key in all HTTP Request nodes that call the fal.run URL. Find the Authorization header in each of these nodes and replace the existing key with your own Key YOUR_FAL_AI_KEY_HERE. Nodes to update: Create Images1, Get Images1, Create Video1, Get Video1, Merge Clips, Get Final video, Combine Voice and Video. Configure OpenAI Nodes: Select each OpenAI node (e.g., Create New Idea1, Generating scenes1) and choose your OpenAI credential. You can customize the main prompt in the Create New Idea1 node to change the theme of the videos you want to generate. Configure Google Sheets & Drive: In the Organise idea, caption etc1 node, select your Google Sheets credential and specify the Spreadsheet and Sheet ID you want to use for logging ideas. In the Upload file to drive node, select your Google Drive credential and choose the destination folder for your final videos.