Workflow Templates

📤 Search Products from Facebook Ads on Amazon Once connected, this automation automatically scrapes Facebook ads from a specific Facebook Ad Library URL and searches for that same product on Amazon. Can be useful for Amazon FBA or dropshipping. 🔨 Setup This automation workflow is connected with two Apify scrapers. Make sure to connect the two scrapers mentioned in the blue and orange box, with their specific API endpoints. 👋 Need Help? If you need further help, or want a specific automation to be built for you, feel free to contact me via richard@advetica-systems.com.

How it works This workflow automates the generation of ad-ready product images by combining product and influencer photos with AI styling. It runs on a scheduled trigger, fetches data from Google Sheets, and retrieves product and influencer images from Google Drive. The images are processed with OpenAI and OpenRouter to generate enhanced visuals, which are then saved back to Google Drive. Finally, the result is logged into Google Sheets with a ready-to-publish status. Step-by-step 1. Trigger & Data preparation Schedule Trigger** – Runs workflow automatically on a set schedule. Google Sheets (Get the Raw)** – Retrieves today’s product and model URLs. Google Drive (Download Product Image)** – Downloads the product image. Google Drive (Download Influencer Image)** – Downloads the influencer image. Extract from File (Binary → Base64)** – Converts both product and model images for AI processing. 2. AI analysis & image generation OpenAI (Analyze Image)** – Creates an ad-focused visual description (lighting, mood, styling). HTTP Request (OpenRouter Gemini)** – Generates an AI-enhanced image combining product + influencer. Code Node (Cleanup)** – Cleans base64 output to remove extra prefixes. Convert to File** – Transforms AI output into a proper image file. 3. Save & update Google Drive (Upload Image)** – Uploads generated ad image to target folder. Google Sheets (Append/Update Row)** – Stores the Drive link and updates publish status. Why use this? Automates the entire ad image creation process without manual design work. Ensures product visuals are consistent, styled, and ad-ready. Saves final creatives in Google Drive for easy access and sharing. Keeps campaign tracking organized by updating Google Sheets automatically. Scales daily ad production efficiently for multiple products or campaigns.

AI Website Scraper & Company Intelligence Description This workflow automates the process of transforming any website URL into a structured, intelligent company profile. It's triggered by a form, allowing a user to submit a website and choose between a "basic" or "deep" scrape. The workflow extracts key information (mission, services, contacts, SEO keywords), stores it in a structured Supabase database, and archives a full JSON backup to Google Drive. It also features a secondary AI agent that automatically finds and saves competitors for each company, building a rich, interconnected database of company intelligence. Quick Implementation Steps Import the Workflow: Import the provided JSON file into your n8n instance. Install Custom Community Node: You must install the community node from: 👉 https://www.npmjs.com/package/n8n-nodes-crawl-and-scrape FIRECRAWL N8N Documentation 👉 https://docs.firecrawl.dev/developer-guides/workflow-automation/n8n Install Additional Nodes: n8n-nodes-crawl-and-scrape and n8n-nodes-mcp fire crawl mcp . Set up Credentials: Create credentials in n8n for FIRE CRAWL API,Supabase, Mistral AI, and Google Drive. Configure API Key (CRITICAL): Open the Web Search tool node. Go to Parameters → Headers and replace the hardcoded Tavily AI API key with your own. Configure Supabase Nodes: Assign your Supabase credential to all Supabase nodes. Ensure table names (e.g., companies, competitors) match your schema. Configure Google Drive Nodes: Assign your Google Drive credential to the Google Drive2 and save to Google Drive1 nodes. Select the correct Folder ID. Activate Workflow: Turn on the workflow and open the Webhook URL in the “On form submission” node to access the form. What It Does Form Trigger Captures user input: “Website URL” and “Scraping Type” (basic or deep). Scraping Router A Switch node routes the flow: Deep Scraping →** AI-based MCP Firecrawler agent. Basic Scraping →** Crawlee node. Deep Scraping (Firecrawl AI Agent) Uses Firecrawl and Tavily Web Search. Extracts a detailed JSON profile: mission, services, contacts, SEO keywords, etc. Basic Scraping (Crawlee) Uses Crawl and Scrape node to collect raw text. A Mistral-based AI extractor structures the data into JSON. Data Storage Stores structured data in Supabase tables (companies, company_basicprofiles). Archives a full JSON backup to Google Drive. Automated Competitor Analysis Runs after a deep scrape. Uses Tavily web search to find competitors (e.g., from Crunchbase). Saves competitor data to Supabase, linked by company_id. Who's It For Sales & Marketing Teams:** Enrich leads with deep company info. Market Researchers:** Build structured, searchable company databases. B2B Data Providers:** Automate company intelligence collection. Developers:** Use as a base for RAG or enrichment pipelines. Requirements n8n instance** (self-hosted or cloud) Supabase Account:** With tables like companies, competitors, social_links, etc. Mistral AI API Key** Google Drive Credentials** Tavily AI API Key** (Optional) Custom Nodes: n8n-nodes-crawl-and-scrape How It Works Flow Summary Form Trigger: Captures “Website URL” and “Scraping Type”. Switch Node: deep → MCP Firecrawler (AI Agent). basic → Crawl and Scrape node. Scraping & Extraction: Deep path: Firecrawler → JSON structure. Basic path: Crawlee → Mistral extractor → JSON. Storage: Save JSON to Supabase. Archive in Google Drive. Competitor Analysis (Deep Only): Finds competitors via Tavily. Saves to Supabase competitors table. End: Finishes with a No Operation node. How To Set Up Import workflow JSON. Install community nodes (especially n8n-nodes-crawl-and-scrape from npm). Configure credentials (Supabase, Mistral AI, Google Drive). Add your Tavily API key. Connect Supabase and Drive nodes properly. Fix disconnected “basic” path if needed. Activate workflow. Test via the webhook form URL. How To Customize Change LLMs:** Swap Mistral for OpenAI or Claude. Edit Scraper Prompts:** Modify system prompts in AI agent nodes. Change Extraction Schema:** Update JSON Schema in extractor nodes. Fix Relational Tables:** Add Items node before Supabase inserts for arrays (social links, keywords). Enhance Automation:** Add email/slack notifications, or replace form trigger with a Google Sheets trigger. Add-ons Automated Trigger:** Run on new sheet rows. Notifications:** Email or Slack alerts after completion. RAG Integration:** Use the Supabase database as a chatbot knowledge source. Use Case Examples Sales Lead Enrichment:** Instantly get company + competitor data from a URL. Market Research:** Collect and compare companies in a niche. B2B Database Creation:** Build a proprietary company dataset. WORKFLOW IMAGE Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|-----------| | Form Trigger 404 | Workflow not active | Activate the workflow | | Web Search Tool fails | Missing Tavily API key | Replace the placeholder key | | FIRECRAWLER / find competitor fails | Missing MCP node | Install n8n-nodes-mcp | | Basic scrape does nothing | Switch node path disconnected | Reconnect “basic” output | | Supabase node error | Wrong table/column names | Match schema exactly | 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. Contact: shilpa.raju@digitalbiz.tech For more such offerings, visit us: https://www.digitalbiz.tech

Website Leads to Voice Demo and Scheduling Creator: Summer Chang AI Booking Agent Setup Guide Overview This automation turns your website into an active booking agent. When someone fills out your form, it automatically: Adds their information to Notion AI researches their business from their website Calls them immediately with a personalized pitch Updates Notion with call results Total setup time: 30-45 minutes What You Need Before starting, create accounts and gather these: n8n account (cloud or self-hosted) Notion account - Free plan works duplicate my notion template OpenRouter API key - Get from openrouter.ai Vapi account - Get from vapi.ai Create an AI assistant Set up a phone number Copy your API key, Assistant ID, and Phone Number ID How It Works The Complete Flow Visitor fills form on your website Form submission creates new record in Notion with Status = "New" Notion Trigger detects new record (checks every minute) Main Workflow executes: Fetches lead's website AI analyzes their business Updates Notion with analysis Makes Vapi call with personalized intro Call happens between your AI agent and the lead When call ends, Vapi sends webhook to n8n Webhook Workflow executes: Fetches call details from Vapi AI generates call summary Updates Notion with results and recording

Build a PDF to Vector RAG System: Mistral OCR, Weaviate Database and MCP Server A comprehensive RAG (Retrieval-Augmented Generation) workflow that transforms PDF documents into searchable vector embeddings using advanced AI technologies. 🚀 Features PDF Document Processing**: Upload and extract text from PDF files using Mistral's OCR capabilities Vector Database Storage**: Store document embeddings in Weaviate vector database for efficient retrieval AI-Powered Search**: Search through documents using semantic similarity with Cohere embeddings MCP Server Integration**: Expose the knowledge base as an AI tool through MCP (Model Context Protocol) Document Metadata**: Basic document metadata including filename, content, source, and upload timestamp Text Chunking**: Automatic text splitting for optimal vector storage and retrieval 🛠️ Technologies Used Mistral AI**: OCR and text extraction from PDF documents Weaviate**: Vector database for storing and retrieving document embeddings Cohere**: Multilingual embeddings and reranking for improved search accuracy MCP (Model Context Protocol)**: AI tool integration for external AI workflows n8n**: Workflow automation and orchestration 📋 Prerequisites Before using this template, you'll need to set up the following credentials: Mistral Cloud API: For PDF text extraction Weaviate API: For vector database operations Cohere API: For embeddings and reranking HTTP Header Auth: For MCP server authentication 🔧 Setup Instructions Import the template into your n8n instance Configure credentials for all required services Set up Weaviate collection named "KnowledgeDocuments" Configure webhook paths for the MCP server and form trigger Test the workflow by uploading a PDF document 📊 Workflow Overview PDF Upload → Text Extraction → Document Processing → Vector Storage → AI Search ↓ ↓ ↓ ↓ ↓ Form Trigger → Mistral OCR → Prepare Metadata → Weaviate DB → MCP Server 🎯 Use Cases Knowledge Base Management**: Create searchable repositories of company documents Research Documentation**: Process and search through research papers and reports Legal Document Search**: Index and search through legal documents and contracts Technical Documentation**: Make technical manuals and guides searchable Academic Literature**: Process and search through academic papers and publications ⚠️ Important Notes Model Consistency**: Use the same embedding model for both storage and retrieval Collection Management**: Ensure your Weaviate collection is properly configured API Limits**: Be aware of rate limits for Mistral, Cohere, and Weaviate APIs Document Size**: Consider chunking large documents for optimal processing 🔗 Related Resources n8n Documentation Weaviate Documentation Mistral AI Documentation Cohere Documentation MCP Protocol Documentation 📝 License This template is provided as-is for educational and commercial use.

This template demonstrates how to build an AI-powered name generator that creates realistic names perfect for UX/UI designers, developers, and content creators. Use cases: User persona creation, mockup development, prototype testing, customer testimonials, team member listings, app interface examples, website content, accessibility testing, and any scenario requiring realistic placeholder names. How it works AI-Powered Generation:** Uses any LLM to generate names based on your specifications Customizable Parameters:** Accepts gender preferences, name count, and optional reference names for style matching UX/UI Optimized:** Names are specifically chosen to work well in design mockups and prototypes Smart Formatting:** Returns clean JSON arrays ready for integration with design tools and applications Reference Matching:** Can generate names similar in style to a provided reference name How to set up Replace "Dummy API" credentials with your preferred language model API key Update webhook path and authentication as needed for your application Test with different parameters: gender (masculine/feminine/neutral), count (1-20), reference_name (optional) Integrate webhook URL with your design tools, Bubble apps, or other platforms Requirements LLM API access (OpenAI, Claude, or other language model) n8n instance (cloud or self-hosted) Platform capable of making HTTP POST requests API Usage POST to webhook with JSON body: { "gender": "masculine", "count": 5, "reference_name": "Alex Chen" // optional } Response: { "success": true, "names": ["Marcus Johnson", "David Kim", "Sofia Rodriguez", "Chen Wei", "James Wilson"], "count": 5 } How to customize Modify AI prompt for specific naming styles or regions Add additional parameters (age, profession, cultural background) Connect to databases for persistent name storage Integrate with design tools APIs (Figma, Sketch, Adobe XD) Create batch processing for large mockup projects

Who’s it for Remote and distributed teams that schedule across time zones and want to avoid meetings landing on public holidays—PMs, CS/AM teams, and ops leads who own cross-regional calendars. What it does / How it works The workflow checks next week’s Google Calendar events, compares event dates against public holidays for selected country codes, and produces a single Slack digest with any conflicts plus suggested alternative dates. Core steps: Workflow Configuration (Set) → Fetch Public Holidays (via a public holiday API such as Calendarific/Nager.Date) → Get Next Week Calendar Events (Google Calendar) → Detect Holiday Conflicts (compare dates) → Generate Reschedule Suggestions (find nearest business day that isn’t a holiday/weekend) → Format Slack Digest → Post Slack Digest. How to set up Open Workflow Configuration (Set) and edit: countryCodes, calendarId, slackChannel, nextWeekStart, nextWeekEnd. Connect your own Google Calendar and Slack credentials in n8n (no hardcoded keys). (Optional) Adjust the Trigger to run daily or only on Mondays. Requirements n8n (Cloud or self-hosted) Google Calendar read access to the target calendar Slack app with permission to post to the chosen channel A public-holiday API (no secrets needed for Nager.Date; Calendarific requires an API key) How to customize the workflow Time window: Change nextWeekStart/End to scan a different period. Holiday sources: Add or swap APIs; merge multiple regions. Suggestion logic: Tweak the look-ahead window or rules (e.g., skip Fridays). Output: Post per-calendar messages, DM owners, or create tentative reschedule events automatically.

Split Test AI Prompts Using Supabase & Langchain Agent This workflow allows you to A/B test different prompts for an AI chatbot powered by Langchain and OpenAI. It uses Supabase to persist session state and randomly assigns users to either a baseline or alternative prompt, ensuring consistent prompt usage across the conversation. 🧠 Use Case Prompt optimization is crucial for maximizing the performance of AI assistants. This workflow helps you run controlled experiments on different prompt versions, giving you a reliable way to compare performance over time. ⚙️ How It Works When a message is received, the system checks whether the session already exists in the Supabase table. If not, it randomly assigns the session to either the baseline or alternative prompt. The selected prompt is passed into a Langchain Agent using the OpenAI Chat Model. Postgres is used as chat memory for multi-turn conversation support. 🧪 Features Randomized A/B split test per session Supabase database for session persistence Langchain Agent + OpenAI GPT-4o integration PostgreSQL memory for maintaining chat context Fully documented with sticky notes 🛠️ Setup Instructions Create a Supabase table named split_test_sessions with the following columns: session_id (text) show_alternative (boolean) Add credentials for: Supabase OpenAI PostgreSQL (for chat memory) Modify the "Define Path Values" node to set your baseline and alternative prompts. Activate the workflow. Send messages to test both prompt paths in action. 🔄 Next Steps Add tracking for conversions or feedback scores to compare outcomes. Modify the prompt content or model settings (e.g. temperature, model version). Expand to multi-variant tests beyond A/B. 📚 Learn More How This Workflow Uses Supabase + OpenAI for Prompt Testing

WooCommerce New Category Alert via WhatsApp Using Rapiwa API This n8n automation listens for the creation of a new WooCommerce product category, fetches all WooCommerce customers, cleans and formats their phone numbers, verifies them using the Rapiwa WhatsApp validation API, sends a WhatsApp message to verified numbers with the new category info, and logs each interaction into a Google Sheet (separately for verified and unverified customers). Who this is for You have a WooCommerce store and want to: Send a promotional message when a new product category is added, Verify customer WhatsApp numbers in bulk, Keep a clear log in Google Sheets of which numbers are verified or not. What it does (high level) Webhook is triggered when a new WooCommerce category is created. Fetches all WooCommerce customers via API. Limits processing to the first 10 customers (for performance/testing). Cleans phone numbers (removes +, spaces, and non-digits). Verifies each number via Rapiwa WhatsApp Verify API. If verified: sends WhatsApp message with new category info, logs as Verification = verified, Status = sent. If not verified: logs as Verification = unverified, Status = not sent. Processes users in batches with delays to avoid rate limiting. How it works (step-by-step) Trigger**: Webhook node is triggered by WooCommerce category creation. Format Data**: Category details (name, slug, description) are parsed. Get Customers**: Fetch all WooCommerce customers using the WooCommerce API. Limit**: Only the first 10 are processed. Loop & Clean**: Loop over each customer, clean phone numbers and extract info. Verify Number**: Send HTTP POST to https://app.rapiwa.com/api/verify-whatsapp. Decision Node**: Use If node to check if exists == true. Send Message**: If verified, send WhatsApp message with category details. Append to Sheet**: Log verified and unverified customers separately in Google Sheets. Wait + Batch Control**: Use Wait and SplitInBatches nodes to control flow and prevent throttling. Example verify body (HTTP Request node): { "number": "{{ $json['WhatsApp No'] }}" } Customization ideas Send images, videos, or template messages if supported by Rapiwa. Personalize messages using name or category data. Increase delay or reduce batch size to minimize risk of rate limits. Add a second sheet to log full API responses for debugging and auditing. Best practices Test on small batches before scaling. Only send messages to users who opted in. Store API credentials securely using n8n’s credentials manager. Ensure your Google Sheet column headers match exactly with what's expected. Key Improvements Made Clarified the trigger source as a Webhook from WooCommerce category creation. Fixed inconsistency in the "What it does" section (originally referenced reading from Google Sheets, but your workflow starts from WooCommerce, not Sheets). Standardized terminology to match n8n nodes: Webhook, Loop, HTTP Request, etc. Aligned the flow exactly with your nodes: Webhook → Format → Get Customers → Limit → Loop → Clean → Verify → If → Send/Log → Wait → Repeat Useful Links Dashboard:** https://app.rapiwa.com Official Website:** https://rapiwa.com Documentation:** https://docs.rapiwa.com Support WhatsApp Support: Chat Now Discord: Join SpaGreen Community Facebook Group: SpaGreen Support Website: https://spagreen.net Developer Portfolio: Codecanyon SpaGreen

AI NETWORK DIAGRAM PROMPT GENERATOR Template Description This workflow automates the creation of network diagram prompts using AI. It retrieves Layer-2 topology data from AWX, parses device relationships, and generates a clean, structured prompt ready for Lucidchart’s AI diagram generator. How It Works The workflow triggers an AWX Job Template that runs commands such as show cdp neighbors detail. After the job completes, n8n fetches the stdout, extracts neighbor relationships through a JavaScript parser, and sends the structured data to an LLM (Gemini). The LLM transforms the topology into a formatted prompt you can paste directly into Lucidchart to instantly generate a visual network diagram. Setup Steps Configure AWX: Ensure your Job Template runs the required network commands and produces stdout. Obtain your AWX base URL, credentials, and Job Template ID. Add Credentials in n8n: Create AWX API credentials. Add Google Gemini credentials for the LLM node. Update Workflow Nodes: Insert your AWX URL and Job Template ID in the “Launch Job” node. Verify endpoints in the “Job Status” and “Job Stdout” nodes. Run the workflow: After execution, copy the generated Lucidchart prompt and paste it into Lucidchart’s AI to produce the network diagram.

Who is this for? Crypto traders, researchers, and investors who want to identify trending market narratives and sector rotations before they become mainstream news. What it does Automatically detects which crypto sectors are gaining momentum by analyzing top gainers, groups tokens by narrative (AI, DeFi, Meme, Gaming, RWA, etc.), uses Gemini AI to research why each sector is pumping, and delivers a comprehensive digest to Discord. ✅ Identifies Emerging Narratives! — Automatically detects sector-wide pumps and researches the catalysts driving them. How it works Triggers on schedule (configurable - default: hourly) Fetches top 200 gainers sorted by 24h performance from CoinMarketCap Filters tokens with strict criteria: >40% gain, >$10M market cap, >$1M volume Groups tokens into sectors using CoinMarketCap tags (AI, DeFi, Meme, Gaming, Layer1, Layer2, DePIN, RWA, Infrastructure) Creates research prompts for sectors with 2+ pumping tokens Gemini AI analyzes each sector for catalysts, news, and sustainability Generates formatted narrative digest with token performance and AI insights Splits long reports and sends to Discord (handles 2000 char limit) Set up steps Get a CoinMarketCap API key from CoinMarketCap (free tier: 10K credits/month) Get a Google Gemini API key from Google AI Studio Create a Discord webhook in your server (Server Settings → Integrations → Webhooks) Connect CMC API key as Header Auth credential (Header Name: X-CMC_PRO_API_KEY) to the Fetch Top 200 Gainers from CMC node Connect Gemini credentials to the Gemini Sector Research node Connect Discord webhook to the Send to Discord node Optionally adjust filter thresholds in the Filter Top Gainers node (MIN_PERCENT_CHANGE, MIN_MARKET_CAP, MIN_VOLUME) Setup time: ~10 minutes

📊 Description Streamline AI-focused SEO research by automatically analyzing URLs stored in Google Sheets, extracting semantic signals from each webpage, and generating high-quality topic clusters for AI discovery. 🤖🔍 This automation fetches URLs weekly, scrapes headings (H1–H6), extracts entities, keywords, topics, and summaries using GPT-4o-mini, and classifies each page into clusters and subclusters optimized for LLM search visibility. It also generates internal linking suggestions for better topical authority and writes all results back into Google Sheets. Perfect for content strategists, SEO teams, and AI-search optimization workflows. 📈🧩 🔁 What This Template Does 1️⃣ Triggers weekly to process URLs stored in Google Sheets. 📅 2️⃣ Fetches all URL records from the configured sheet. 📥 3️⃣ Processes URLs in batches to avoid API overload. 🔁 4️⃣ Extracts webpage HTML and pulls semantic headings (H1–H6). 📰 5️⃣ Sends headings + URL context to GPT-4o-mini for structured extraction of: — title — entities — keywords — topics — summary 6️⃣ Generates high-level cluster + subcluster labels for each page. 🧠 7️⃣ Recommends 3–5 internal linking URLs to strengthen topical authority. 🔗 8️⃣ Updates Google Sheets with all extracted fields + status flags. 📊 9️⃣ Repeats the process until all URLs are analyzed. 🔄 ⭐ Key Benefits ✅ Automates topical clustering for AI search optimization ✅ Extracts entities, keywords, and topics with high semantic accuracy ✅ Strengthens internal linking strategies using AI suggestions ✅ Eliminates manual scraping and analysis work ✅ Enables scalable content audits for large URL datasets ✅ Enhances visibility in AI-driven search systems and answer engines 🧩 Features Google Sheets integration for input + output HTML parsing for H1–H6 extraction GPT-4o-mini structured JSON extraction Topic clustering engine (cluster & subcluster classification) Internal linking recommendation generator Batch processing for large URL datasets Status-based updating in Google Sheets 🔐 Requirements Google Sheets OAuth2 credentials OpenAI API key (GPT-4o-mini) Publicly accessible URLs (or authenticated HTML if applicable) n8n with LangChain nodes enabled 🎯 Target Audience SEO teams performing semantic clustering at scale Content strategists creating AI-ready topic maps Agencies optimizing large client URL collections AI-search consultants building structured content libraries Technical marketers needing automated content analysis