by TreyDong
How it works • Automatically detects when new pages are created in your Notion workspace • Uses AI to generate contextually relevant icons based on page titles for perfect visual representation • Fetches random high-quality cover images from Unsplash to add visual appeal to each page • Seamlessly integrates with your existing Notion workflow without manual intervention Set up steps • Connect your Notion workspace using API credentials - takes about 5 minutes to configure • Set up AI service integration for intelligent icon generation based on page titles • Configure Unsplash API access for random cover image fetching • Configure webhook triggers to monitor new page creation events • Test the workflow with a sample page to ensure proper functionality • Keep detailed setup instructions and troubleshooting tips in the workflow notes for future reference This template helps streamline your Notion workspace by automatically beautifying new pages with AI-generated icons and stunning Unsplash covers, saving you time while maintaining a visually appealing and professional appearance across your knowledge base.
by Don Jayamaha Jr
📰 This AI-powered agent performs real-time sentiment analysis on Tesla (TSLA) news to support trading decisions. It aggregates headlines from 5 trusted sources and uses DeepSeek Chat to classify sentiment and generate structured summaries. This tool is a critical sub-agent in the broader Tesla Quant Trading AI Agent system. ⚠️ Not standalone — this agent is designed to be executed by the Tesla Quant Trading AI Agent. ⚙️ Requires: DeepSeek Chat API Key 🔌 Workflow Role This tool processes Tesla-related news and produces output like: { "sentiment": "bullish", "summary": "Tesla stock rallied today after strong delivery numbers and Cybertruck updates. Analysts remain optimistic.", "topHeadlines": [ "Tesla beats Q2 delivery forecast – Yahoo Finance", "Cybertruck ramps up in Texas – Electrek", "Berlin Gigafactory expands battery production – CleanTechnica" ] } Its output feeds directly into the master trading agent’s final trade report. 📰 News Sources Used This agent collects real-time headlines from: Google News (filtered by “Tesla” or “TSLA”) Yahoo Finance (TSLA-specific feed) Electrek (Tesla archive) CleanTechnica (Tesla sustainability news) TeslaNorth (app/product release updates) These five tools are always queried together to ensure market-wide signal coverage. 🤖 What the Agent Does Pulls headlines from all 5 Tesla-specific RSS feeds Uses DeepSeek Chat to: Analyze narrative tone (bullish / bearish / neutral) Identify macro/financial drivers Generate a 2–3 sentence summary Return top 3–5 headlines Outputs structured JSON for downstream use 🛠️ Setup Instructions 1. Install & Name Import this file and name it: Tesla_News_and_Sentiment_Analyst_Tool 2. Add DeepSeek API Credentials Go to: Credentials → Add New → DeepSeek API Save as: DeepSeek account 3. Internet Access Required Ensure RSS feeds can fetch live headlines Works best with a cloud-hosted n8n instance or tunnel-enabled local install 4. Must Be Triggered by Parent Triggered via Execute Workflow by the Tesla Quant Trading AI Agent Requires these inputs: message: optional query context sessionId: passed to maintain short-term memory across executions 🧠 Agent Architecture | Node Name | Function | | ---------------------------------- | ------------------------------------------------ | | DeepSeek Chat Model | Performs AI-based sentiment analysis | | Tesla News and Sentiment Analyst | Combines results, formats output in strict JSON | | Simple Memory | Stores session-level context (short-term memory) | | 5x RSS nodes | Aggregate Tesla news from trusted media outlets | 📌 Sticky Notes Included 🟢 Trigger from Parent Workflow – Executed only by main TSLA agent 🟠 News Feeds Overview – Lists and explains each of the 5 feeds 🧠 DeepSeek Chat Notes – Describes LLM behavior and parsing role 🔵 Short-Term Memory – Buffers sentiment context during user session 📘 Sentiment Analyst Agent – Summarizes key responsibilities 📎 Licensing & Attribution © 2025 Treasurium Capital Limited Company This architecture, workflow structure, and prompt design are licensed for educational and operational use only. Commercial resale or rebranding prohibited without authorization. 🔗 Creator: Don Jayamaha 🔗 Templates: https://n8n.io/creators/don-the-gem-dealer/ 🚀 Power your TSLA trading with AI-driven sentiment—built with DeepSeek Chat and 5 trusted news sources. This tool is required by the Tesla Quant Trading AI Agent.
by Flavio Angeleu
WhatsApp Flows Encrypted Data Exchange Workflow Summary This workflow enables secure end-to-end encrypted data exchange with WhatsApp Flows for interactive applications inside Whatsapp. It implements the WhatsApp Business Encryption protocol using RSA for key exchange and AES-GCM for payload encryption, providing a secure channel for sensitive data transmission while interfacing with WhatsApp's Business API. This follows the official WhatsApp Business Encryption specifications to establish an encrypted GraphQL-powered data exchange channel between your business and the WhatsApp consumer client. How It Works Encryption Flow Webhook Reception: Receives encrypted data from WhatsApp containing: encrypted_flow_data: The AES-encrypted payload encrypted_aes_key: The RSA-encrypted AES key initial_vector: Initialization vector for AES decryption Decryption Process: The workflow decrypts the AES key using an RSA private key Then uses this AES key to decrypt the payload data The inverted IV is used for response encryption Data Processing: The workflow parses the decrypted JSON data Routes requests based on the screen parameter. Response Generation: Generates appropriate response data based on the request type Encrypts the response using the same AES key and inverted IV Returns the base64-encoded encrypted response Key Components Webhook Endpoint**: Entry point for encrypted WhatsApp requests Decryption Pipeline**: RSA and AES decryption components Business Logic Router**: Screen-based routing for different functionality Encryption Pipeline**: Secure response encryption How to Use Deploy the Workflow: Import the workflow JSON into your n8n instance Set Up WhatsApp Integration: Configure your WhatsApp Business API to send requests to your n8n webhook URL Ensure your WhatsApp integration is set up to encrypt data using the public key pair of the private key used in this workflow Test the Flow: Send an encrypted test message from WhatsApp to verify connectivity Check if appointment data is being retrieved correctly Validate that seat selection is functioning as expected Production Use: Monitor the workflow performance in production Set up error notification if needed Requirements Authentication Keys RSA Private Key: Required for decrypting the AES key (included in the workflow) WhatsApp Business Public Key: Must be registered with the WhatsApp Business API PostgreSQL Credentials: For accessing appointment data from the database WhatsApp Business Encryption Setup As specified in the WhatsApp Business Encryption documentation: Generate a 2048-bit RSA Key Pair: The private key remains with your business (used in this workflow) The public key is shared with WhatsApp Register the Public Key with WhatsApp: Use the WhatsApp Cloud API to register your public key Set up the public key using the /v17.0/{WhatsApp-Business-Account-ID}/whatsapp_business_encryption endpoint Key Registration API Call: POST /v17.0/{WhatsApp-Business-Account-ID}/whatsapp_business_encryption { "business_public_key": "YOUR_PUBLIC_KEY" } Verification: Verify your public key is registered using a GET request to the same endpoint Ensure the key status is "active"
by Davide
🤖📞 This workflow automates the process of calling customers to remind them of their booking reservations using AI-generated messages and a Twilio phone number. It can easily be adapted for other venues. Key Benefits Time-Saving Automation**: Eliminates the need for manual calls by staff, saving hours per week. Human-like AI Messages**: Uses a custom language model to generate polite, natural phone messages tailored to each customer. Multi-Channel Integration**: Google Sheets for reservation tracking. Twilio for automated calling. OpenRouter (or other LLMs) for generating speech content. Error Reduction**: Ensures all customers receive reminders exactly on the reservation day, minimizing no-shows. Scalable**: Easily adapts to growing reservation lists and more complex message logic. Suitable** for restaurants, hairdressers, offices and any other business How It Works Trigger: The workflow can be triggered manually (via "When clicking ‘Execute workflow’) or automatically at 11 AM daily (via Schedule Trigger). Data Fetch: Retrieves today’s reservations from a Google Sheet, filtering rows where DATE = today and CALLED is empty. AI-Generated Call Script: For each reservation, the Secretary Agent (powered by OpenRouter’s Grok-4) generates a phone script using the guest’s name, time, and party size. Twilio Call: The script is sent to Twilio, which calls the guest’s phone number (from the sheet) and reads the message aloud using text-to-speech. Update & Loop: Marks the reservation as called (CALLED = "x") in the sheet and waits 2 minutes between calls to avoid rate limits. Set Up Steps Twilio Configuration: Sign up for Twilio, buy a phone number, and: Enable text-to-speech (set language to Italian). Configure geo permissions for the target country. Add credentials to the Twilio node (sender number in From field). Google Sheets Setup: Clone the Google Sheet template and ensure: Phone numbers include the international prefix (without "+"). Columns: DATE, TIME, NAME, N. PEOPLE, PHONE, CALLED. OpenRouter API: Connect the OpenRouter Chat Model node to your account (using Grok-4 or another model). Deploy: Activate the workflow and test with manual execution. Note: The workflow is currently inactive (active: false). Enable it after setup. Need help customizing? Contact me for consulting and support or add me on Linkedin.
by Dvir Sharon
📰 Publish Latest News on X and Other Social Media Platforms Using Keyword A comprehensive n8n automation that fetches the latest news based on keywords, generates AI-powered social media content, and automatically publishes to X (Twitter) with complete tracking and notification systems. 📋 Overview This workflow provides a professional news publishing solution that automatically discovers breaking news, creates engaging social media content using AI, and publishes to X (Twitter) with comprehensive tracking. Perfect for news organizations, content creators, social media managers, and businesses wanting to stay current with automated news sharing. The system uses BrightData's Google News dataset, OpenAI's GPT-4o for content generation, and multi-platform integration for complete automation. ⭐ Key Features 📝 Form-Based Input**: Clean web form for keyword and country submission 📰 Real-Time News Fetching**: BrightData Google News integration for latest articles 🤖 AI Content Generation**: GPT-4o powered tweet creation with hashtags 📱 Auto X Publishing**: Direct posting to X (Twitter) with URL tracking 📊 Complete Tracking**: Google Sheets logging of all published content 🔔 Email Notifications**: Success alerts with tweet links 🌍 Multi-Country Support**: Localized news for US, India, UK, Australia ⚡ Status Monitoring**: Real-time progress tracking with retry logic 🛡 Error Handling**: Robust error management and validation 🔄 Loop Management**: Intelligent waiting for news processing completion 🎯 What This Workflow Does Input: News Name**: Keyword or topic for news search (required) Country**: Target country for localized news (dropdown: US/IN/GB/AU) Processing: Form Submission: Captures news keyword and target country News Triggering: Initiates BrightData Google News scraping job Status Monitoring: Checks scraping progress with intelligent retry loop Data Retrieval: Fetches latest news articles when ready AI Content Creation: Generates engaging tweet content using GPT-4o Social Publishing: Posts content to X (Twitter) automatically URL Generation: Creates direct tweet links for tracking Data Logging: Saves content and URLs to Google Sheets Email Notification: Sends success confirmation with tweet link Completion: Workflow ends with full audit trail 📋 Output Data Points | Field | Description | Example | | :------------ | :---------------------------------- | :----------------------------------------------------------------------------------------------------- | | TweetMessage | AI-generated social media content | "Breaking: AI revolution transforming healthcare with 40% efficiency gains. New study shows promising results in patient care automation. #AI #Healthcare #Innovation #TechNews #US" | | TweetURL | Direct link to published tweet | https://twitter.com/i/web/status/1234567890123456789 | 🛠️ Setup Instructions Prerequisites: n8n instance (self-hosted or cloud) X (Twitter) account with API v2 access OpenAI account with GPT-4o access Gmail account for notifications Google account with Sheets access BrightData account with Google News dataset access Basic understanding of social media automation Step 1: Import the Workflow Copy the JSON workflow code from the provided file. In n8n, click "+ Add workflow". Select "Import from JSON". Paste the workflow code and click "Import". The workflow will appear with all nodes properly connected. Step 2: Configure API Credentials X (Twitter) API Setup: Create X Developer Account at developer.twitter.com. Create new app and generate API keys. In n8n: Credentials → + Add credential → Twitter OAuth2 API. Add your Twitter API credentials: API Key API Secret Key Bearer Token Access Token Access Token Secret Test the connection with a sample tweet. OpenAI API Configuration: Get API key from platform.openai.com. Ensure GPT-4o model access is available. In n8n: Credentials → + Add credential → OpenAI API. Add your OpenAI API key. Verify model access in the "OpenAI Chat Model" node. Gmail Integration: Create "Gmail OAuth2" credential. Follow OAuth setup process. Grant email sending permissions. Test with sample email. BrightData News API: The workflow uses pre-configured token: 5662edde-6735-4c5d-a6c6-693043a5a9a5. Dataset ID: gd_lnsxoxzi1omrwnka5r (Google News). Verify access to Google News dataset. Test API connection. Google Sheets Integration: Create "Google Sheets OAuth2 API" credential. Complete OAuth authentication. Grant read/write permissions. Test connection. Step 3: Configure Google Sheets Integration Create Google Sheets Structure: Sheet Name: "Publish Latest News on Social Media Platforms Using Keyword" Tab: "Data" (default) Columns: Tweet Message: AI-generated content posted to X Tweet URL: Direct link to published tweet Sheet Configuration: Create new Google Sheet or use existing one. Add the required column headers. Copy Sheet ID from URL: https://docs.google.com/spreadsheets/d/SHEET_ID_HERE/edit. Current configured Sheet ID: 1koxNrwdeuaSBdREuKc7JQh3d9blEk0sQDJ8VgVLjPOo. Update Workflow Settings: Open "Google Sheets" node. Replace Document ID with your Sheet ID. Select your Google Sheets credential. Choose "Data" sheet/tab. Verify column mapping is correct. Step 4: Configure Form Interface Form Settings: Open "On form submission" node. Form configuration: Title: "News Publisher" Description: "publish latest news to direct social media" Fields: News Name (text, required) Country (dropdown: US, IN, GB, AU, required) Webhook URL: Copy webhook URL from form trigger node. Current webhook ID: 8d320705-688c-4150-a393-cf899d2bbb52. Test form accessibility and submission. Step 5: Configure Email Notifications Gmail Setup: Open "Gmail" node. Update recipient email: raushan@iwantonlinemarketing.com. Email template includes: Success confirmation Direct tweet link Professional formatting Test email delivery. Step 6: Test the Workflow Sample Test Data: Use these examples for testing: | News Name | Country | Expected Results | | :-------------------- | :------ | :------------------------------------------------- | | artificial intelligence | US | Latest AI news with US-specific hashtags | | cricket world cup | IN | Sports news with India-focused content | | brexit update | GB | UK political news with British hashtags | | bushfire news | AU | Australian environmental news | Testing Process: Activate the workflow (toggle switch). Navigate to the webhook form URL. Submit test data. Monitor execution progress: News fetching (30-60 seconds) AI content generation (10-15 seconds) X publishing (5-10 seconds) Sheet update and email (5 seconds) Verify results in all platforms. 📖 Usage Guide Using the Form Interface Navigate to the webhook URL provided by the form trigger. Enter news keyword or topic (e.g., "climate change", "stock market", "technology"). Select target country from dropdown. Click submit and wait for processing. Check email for success notification with tweet link. Example Inputs to Test | News Name | Country | Expected | | :-------------------------------- | :------ | :----------------------------------------------------- | | "artificial intelligence breakthrough" | "US" | Latest AI developments with tech hashtags | | "football premier league" | "GB" | UK football news with sports hashtags | | "stock market updates" | "IN" | Indian market news with finance hashtags | | "hollywood movies" | "AU" | Entertainment news with Australian perspective | Country-Specific Considerations United States (US)**: Focus on national news and global impact. Hashtags: #USA, #American, #Breaking, #News. Time zone considerations for optimal posting. India (IN)**: Emphasis on regional relevance. Hashtags: #India, #Indian, #News, #Breaking. Cultural context in content generation. United Kingdom (GB)**: British perspective and terminology. Hashtags: #UK, #British, #News, #Breaking. Focus on European context. Australia (AU)**: Australian angle and regional focus. Hashtags: #Australia, #Australian, #News, #Breaking. Pacific region context. 📊 Reading the Results Google Sheets Data The output sheet contains: Complete tweet content with hashtags and formatting. Direct tweet URLs for easy access and sharing. Chronological record of all published content. Audit trail for content management. Email Notifications Success emails include: Confirmation that content was published. Direct link to view the tweet. Professional formatting for easy reference. X (Twitter) Posts Published content features: AI-optimized messaging within 260 character limit. Relevant hashtags based on topic and country. Engaging format designed for social media. Professional tone suitable for news sharing. 🔧 Customization Options Expanding Social Media Platforms Add more platforms to the publishing workflow: // Add LinkedIn publishing { "node": "LinkedIn", "type": "n8n-nodes-base.linkedin", "parameters": { "text": "={{ $json.output }}", "additionalFields": {} } } // Add Facebook posting { "node": "Facebook", "type": "n8n-nodes-base.facebook", "parameters": { "pageId": "YOUR_PAGE_ID", "message": "={{ $json.output }}" } }
by Richard Uren
This template extracts all customers from shopify using GraphQL and the shopify admin API and sync them into a Baserow table. Setup Notes Update the Endpoint in GraphQL node to reflect your Shopify store. In Baserow create a shopify database with a customer table in Baserow. Create columns in the Baserow customer table for first_name, last_name, and email. It takes about 1 second per row to insert.
by ist00dent
This n8n template allows you to instantly generate QR codes from any text or URL by simply sending a webhook request. It's a versatile tool for creating dynamic QR codes for various purposes, from marketing campaigns to event registrations, directly integrated into your automated workflows. 🔧 How it works Receive Data Webhook: This node acts as the entry point for the workflow. It listens for incoming POST requests and expects a JSON body with a data property containing the text or URL you want to encode into the QR code. Generate QR Code: This node makes an HTTP GET request to the QR Server API (api.qrserver.com) to generate the QR code image. The content from your webhook is passed as the data parameter to the API. Respond with QR Code: This node sends the response from the QR Server API back to the service that initiated the webhook. The QR Server API directly returns the image data, so your webhook response will be the QR code image itself. 👤 Who is it for? This workflow is ideal for: Marketers: Generate QR codes for product links, event registrations, or promotional materials on the fly. Developers: Integrate QR code generation into applications, websites, or internal tools. Event Organizers: Create dynamic QR codes for ticketing, information access, or check-ins. Businesses: Streamline processes requiring physical-to-digital transitions, like menu access or contact sharing. Automation Enthusiasts: Add QR code generation capabilities to any workflow. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "data": "https://www.yourwebsite.com/your-specific-page-or-text-to-encode" } The workflow will return the QR code image directly in the response. ⚙️ Setup Instructions Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Receive Data Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /generate-qr). Customize QR Code (Optional): Double-click the Generate QR Code node. You can adjust the size parameter in the URL (e.g., size=200x200 for a larger QR code) or add other parameters supported by the QR Server API (e.g., bgcolor, color, qzone). Activate Workflow: Save and activate the workflow. 📝 Tips Handling the Image Output: Since the QR Server API directly returns the image, the webhook response will be the image data. Depending on your use case, you might want to: Save to File/Cloud: Insert a node (e.g., Write Binary File, Amazon S3, Google Drive) after Generate QR Code to save the image to a file system or cloud storage. Embed in HTML/Email: If you're building an HTML response or sending an email, you might need to convert the image data to a Base64 string or provide a URL to a saved image. Error Handling: Enhance workflow robustness by adding an Error Trigger node. This allows you to catch any issues during QR code generation and set up notifications or logging. Dynamic Size/Color: You can extend the Receive Data Webhook to accept parameters for size, color, or bgcolor in the incoming JSON. Then, dynamically pass these to the url of the Generate QR Code node to create highly customizable QR codes. Input Validation: For more advanced use cases, you could add a Function node after the webhook to validate the incoming data to ensure it's in a valid format (e.g., a URL).
by Richard Uren
Task Read a list of customers from a GoogleSheet and create them in Shopify using Shopify's Admin API (GraphQL). Why ? Generate test users for development stores. Migrate customers from other platforms. Easy intro to Shopify's GraphQL API. Setup Setting up Google Sheets access Follow the instructions in the N8N Docs for granting Oauth2 access to Google services. You'll need to grant API access to Google Sheets and Google Drive (to list available sheets). Setting up Shopify access Shopify's Admin API uses 'Header Auth' with a key of X-Shopify-Access-Token and a value of your shopify access token which starts with shpat_ . How to generate a Shopify Access Token To generate a Shopify Access Token create an app, grant the app the necessary scopes, then generate a token. From inside a store do the following : click Settings (nav link) click Apps and sales channels (nav link) click Develop Apps (button) click Create App (button) give the app a name click configure Admin API Scopes (button) at a minimum grant read_customers and write_customers scope. Grant additional scopes if you plan on accessing other parts of the API. click save To generate the token click install app (button) click install on the dialog that pops up (button) click 'reveal token once' (button) copy the token into a password vault or somewhere secure. Template Updates To test this out you'll need to make the following changes : 1) Create a header credential where the key is X-Shopify-Access-Token and the value is your Shopify Access Token (it starts with shpat_ 2) In the GraphQL node change the endpoint URL to your store. Something like https://{your store goes here}.myshopify.com/admin/api/2025-04/graphql.json Google Sheet Structure Columns can be in any order, because the rows will be mapped to fields in a json object. N8N will treat the first row in the sheet as a column name, so at a minimum use the column names below in row 1 of your sheet. first_name : Any string last_name : Any string email : Valid email mobile_phone : International mobile phone format with no spaces eg. +61414708406 (Shopify will reject anything else). Example CSV "first_name","last_name","email","mobile_phone" "Bob","Smith","bob@example.com","+61414999999"
by Rajeet Nair
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Description This workflow automatically collects daily trending topics from Twitter and YouTube, filters them for relevance, and uses an AI model (such as Mistral Cloud or another OpenAI-compatible API) to generate engaging social media hashtags. The final results, including source platform and date, are saved into a connected Google Sheet for easy access, tracking, or team collaboration. Ideal for content creators, marketers, and social media managers, this automation eliminates the manual effort of trend research and hashtag writing by combining real-time scraping with LLM-powered generation. The result is a scalable, daily strategy tool to stay aligned with what’s trending across major platforms. How It Works Daily Trigger Starts the workflow automatically on a daily schedule. Trend Scraping Scrapes current trending content from Twitter and YouTube using the Crawl and Scrape community node. Filtering & Slicing Removes irrelevant or duplicate entries and limits each platform’s list to top-performing trends. Merge Trends Combines Twitter and YouTube trends into a single dataset. AI Hashtag Generation Sends each trend topic to an AI model to generate relevant hashtags. Output to Google Sheets Loops through AI results and writes them to a Google Sheet, including trend, platform, hashtags, and timestamp. Setup Instructions Estimated time: 10–15 minutes Prerequisites A self-hosted instance of n8n (required for community nodes) API key for Mistral Cloud or any OpenAI-compatible LLM Google Sheets account connected via OAuth2 credentials Twitter and YouTube trend URLs (or scraping logic for target regions) Template Image: Example: Crawl and Scrape Node for Twitter Trends You can use the following configuration in the Crawl and Scrape node to extract Twitter trends from Trends24) { "parameters": { "url": "https://trends24.in/", "selectors": [ { "label": "Twitter Trends", "selector": ".trend-card__list li a", "type": "text" } ] }, "name": "Scrape Twitter Trends", "type": "n8n-nodes-crawl-and-scrape.crawlAndScrape", "typeVersion": 1, "position": [300, 200] } Google Sheet Column Format Column A: Generated Hashtags
by Tharwat Mohamed
Document-Aware WhatsApp AI Bot for Customer Support Google Docs-Powered WhatsApp Support Agent 24/7 WhatsApp AI Assistant with Live Knowledge from Google Docs 📝Description Template Smart WhatsApp AI Assistant Using Google Docs Help customers instantly on WhatsApp using a smart AI assistant that reads your company’s internal knowledge from a Google Doc in real time. Built for clubs, restaurants, agencies, or any business where clients ask questions based on a policy, FAQ, or services document. ⚙️ How it works Users send free-form questions to your WhatsApp Business number (e.g. “What are the gym rules?” or “Are you open today?”) The bot automatically reads your company’s internal Google Doc (policy, schedule, etc.) It merges the document content with today’s date and the user’s question to craft a custom AI prompt The AI (Gemini or ChatGPT) then replies back on WhatsApp using natural, helpful language All conversations are logged to Google Sheets for reporting or audit > 💡Bonus: The AI even understands dates inside the document and compares them to today’s date — e.g. if your document says “Closed May 25 for 30 days,” it will say “We're currently closed until June 24. 🧰 Set up steps Connect your WhatsApp Cloud API account (Meta) Add your Google account and grant access to the Doc containing your company info Choose your AI model (ChatGPT/OpenAI or Gemini) Paste your document ID into the Google Docs node Connect your WhatsApp webhook to Meta (only takes 5 minutes) Done — start receiving and answering customer questions! > 📄 Works best with free-tier OpenAI/Gemini, Google Docs, and Meta's Cloud API (no phone required). Everything is modular, extensible, and low-code. 🔄 Customization Tips Change the Google Doc anytime to update answers — no retraining needed Add your logo and business name in the AI agent’s “System Prompt” Add fallback routes like “Escalate to human” if the bot can't help Clone for multiple brands by duplicating the workflow and swapping in new docs 🤝 Need Help Setting It Up? If you'd like help connecting your WhatsApp Business API, setting up Google Docs access, or customizing this AI assistant for your business or clients… 📩 I offer setup, branding, and customization services: WhatsApp Cloud API setup & verification Google OAuth & Doc structure guidance AI model configuration (OpenAI / Gemini) Branding & prompt tone customization Logging, reporting, and escalation logic Just send a message via: Email: tharwat.elsayed2000@gmail.com WhatsApp: +20 106 180 3236
by Airtop
Automating Company Data Enrichment and HubSpot Integration Use Case This automation enriches company data based on email domain and LinkedIn profile, calculates an ICP (Ideal Customer Profile) score, and updates the corresponding company record in HubSpot. It’s ideal for onboarding, qualification, and CRM enrichment. What This Automation Does Input Parameters Contact email**: Used to derive the company domain. Company domain**: Primary web domain of the company. Company LinkedIn* *(optional): LinkedIn URL for enrichment accuracy. Airtop Profile (connected to LinkedIn)**: An authenticated Airtop Profile. What It Outputs Full company profile (name, tagline, website, headquarters) Employee count ICP score based on AI/tech profile, scale, agency type, and location Updates/creates record in HubSpot with all enriched attributes How It Works Input Validation: Filters out non-corporate domains like Gmail, Yahoo, or .edu. Enrichment Trigger: Launches Airtop workflows to extract and analyze data from LinkedIn and calculate the ICP score. Data Mapping: Compiles structured fields including: Overview, location (city, state, country) Company website and domain LinkedIn URL, employee count ICP score HubSpot Sync: Sends all the enriched fields to the designated HubSpot object for upsertion. Setup Requirements Airtop API Key Airtop Profile with active LinkedIn authentication HubSpot integration enabled for object updates Next Steps Use in Webforms**: Trigger this on signup to auto-populate CRM records. Enrich Manually Entered Contacts**: Use with list-based workflows for batch enrichment. Sync to Other CRMs**: Replace HubSpot step with Salesforce, Pipedrive, etc. for flexible integration. Read more about comapny data enrichment
by Jay Hartley
What this template does This workflow uses the Amadeus API, every day to check for bargain flights for an itinerary and price target of your choice. It then automatically emails you once it found a match. Setup Create an api account on https://developers.amadeus.com/ In Amadeus Flight Search, connect to Oauth2 API: -- Grant Type - Client Credentials -- Access Token URL - https://test.api.amadeus.com/v1/security/oauth2/token -- Client ID/Secret - from your account Set your details in Gmail Set your desired Origin/Destination airports in FromTo Set the dates ahead you wish to search in Get Dates (default is 7 days and 14 days) Set the price target in Under Price How to test it After completing the setup steps above, just hit 'Test workflow'!