Automatic media download from WhatsApp Business messages with HTTP storage
This workflow listens for incoming WhatsApp messages that contain media (e.g., images) and automatically downloads the media file using WhatsApp's private media URL. The trigger node activates when a WhatsApp message with media is received. The media ID is extracted from the message payload. A private media URL is retrieved using the media ID. The media file is downloaded using an authenticated HTTP request. Ideal for: Archiving WhatsApp media to external systems. Triggering further automations based on received media. Integrating with cloud storage like Google Drive, Dropbox, or Amazon S3. Set up steps Connect your WhatsApp Business API account. Add HTTP credentials for downloading media via private URL. Set up the webhook in your WhatsApp Business account. Extend the workflow as needed for your use case (e.g., file storage, alerts).
By Usman LiaqatSmart job search: resume scoring & tailoring with OpenAI, Apify, and Airtable
Who is this for? This workflow is designed for job seekers who want to automate their job application research and resume optimization. It's ideal for professionals who want to match their CVs to new job postings daily, improving the chance of landing interviews without manual work. Use case Problem: Manually searching for jobs, matching resumes, and updating application records is time-consuming and inefficient. Use Case: Automatically fetches new job listings based on user preferences, scores them against the user's existing CV, generates a revamped CV tailored for each job, and stores everything neatly into an Airtable database for easy tracking. What this workflow does? Fetches user job preferences from Google Sheets daily. Searches for jobs matching those preferences using Apify’s scraping. Filters job posts that are fresh (posted within 24-48 hours). Scores each job against the user’s current CV using an OpenAI agent. Generates a revamped CV tailored to each job. Stores the job listing, compatibility score, match reason, and revamped CV into Airtable for future use. API Credentials Required Google Sheets API Credentials — for reading user-defined job preferences. Apify API Key — to scrape job postings (e.g., Indeed Scraper Actor). OpenAI API Key — for AI scoring and CV enhancement. Airtable API Key — for job listing and tracking. Setup Google Sheets: Store your job preferences (like titles, locations, etc.). Apify API: Set up a scraper for LinkedIn, Indeed, or other job boards. OpenAI API: Provide access to a GPT model (ideally GPT-4 Turbo) to handle CV scoring and revamping. Airtable: Create two tables: One for archived jobs (old jobs >48 hours). One for current processed jobs with AI scores and revamped CVs. Columns for Airtable: jobtitle,company,location,dateposted,job_type,description,link,compatibilityScore,matcReason,revampedCV,newCompatibilityScore,newMatchReason. n8n: Deploy the full workflow with nodes for triggers, loops, API calls, parsing, and storage. How to customize it for your needs Edit Job Preferences: Add or update the fields in Google Sheets (Columns: jobtitle, joblocation) to search. Fine-tune AI Prompts: Adjust the scoring criteria (e.g., favor remote roles, leadership experience, certifications). Customize CV Style: Configure the AI to generate shorter, more detailed, or industry-specific resumes. Change Storage Destination: Replace Airtable with Notion, Google Sheets, a CRM system, or even send yourself Slack updates. Expand Job Sources: Easily swap the job scraper to pull listings from your favorite niche job boards. Why Use This Template? Saves 10+ hours/week on manual job search. Instantly tailor CVs to each application. Centralizes all data across Google Sheets and Airtable. Flexible — customize AI prompts, scoring logic, or expand to multiple users! Need Assistance? For setup guidance, customization, or business inquiries, Email: phoenixaiagentsolutions@gmail.com
By Ashish Kumar SwainSummarize private equity & M&A news from RSS feeds to Gmail with GPT-4
Who’s it for This template is for professionals, students, and investors who want a simple daily finance briefing. It is useful for anyone who follows private equity, mergers & acquisitions, and general market news but prefers short summaries instead of reading long articles. How it works The workflow runs twice a day using a schedule trigger (default 09:00 and 15:00). It pulls articles from three RSS feeds: NYT Private Equity, DealLawyers M&A, and Yahoo Finance. The items are merged and limited to the five most recent stories. A code node formats them into a clean block of text. An AI Agent rewrites each article into a short, engaging 5–6 sentence summary. The results are delivered directly to your inbox via Gmail. How to set up Add your Gmail credential and replace {{RECIPIENT_EMAIL}} with your email. Insert your OpenAI API key. (Optional) Replace the RSS feed URLs with your preferred sources. Adjust the schedule times if needed. Requirements n8n v1.112+ Gmail credential OpenAI API key How to customize You can add more feeds, increase the number of articles, or translate summaries into another language. You can also deliver the summaries to Slack, Notion, or Google Sheets instead of email.
By Ali MuthanaGenerate daily stock buy/sell signals using technical indicators and Google Sheets
📊 Description This automation calculates commonly used technical indicators for selected stocks and presents the results in a simple, structured dashboard. It removes the need for manual chart analysis by automatically fetching price data, calculating indicators, and generating clear Buy, Sell, or Neutral signals. The workflow is designed to run daily and provides a consistent technical snapshot for each tracked stock. It is suitable for traders and analysts who want a repeatable and transparent way to monitor technical conditions without relying on manual tools. ⚙️ What This Template Does Runs automatically on a daily schedule Processes a predefined list of stock symbols Fetches recent daily price data from a market data API Calculates RSI, Moving Averages, and MACD Applies rule-based logic to generate Buy, Sell, or Neutral signals Stores indicator values and signals in Google Sheets ✅ Key Benefits Eliminates manual technical analysis Uses standard, widely accepted indicators Produces clear and easy-to-interpret signals Keeps all results in a single dashboard Easy to customize and extend 🧩 Features Daily scheduled execution Historical price data integration RSI (14-period) calculation Moving Averages (SMA 20 and SMA 50) MACD (12, 26, 9) calculation Rule-based Buy / Sell / Neutral classification Google Sheets dashboard output Built-in data validation checks 🔐 Requirements To use this workflow, you will need: A market data API key (Alpha Vantage or similar) A Google Sheets account for storing results Google Sheets credentials configured in n8n An active n8n instance (cloud or self-hosted) 🎯 Target Audience Stock traders and investors Technical analysts Finance and research teams Automation builders working with market data 🛠 Customization Options Update the stock list to track different symbols Adjust indicator periods or thresholds Modify Buy / Sell signal rules Change the schedule frequency Extend the dashboard with additional indicators
By Rahul JoshiAnalyze contract risk from Google Drive with OpenAI and log to Gmail & Sheets
How it works This workflow automates end-to-end contract analysis when a new file is uploaded to Google Drive. It downloads the contract, extracts its content, and uses AI to analyze legal terms, obligations, and risks. Based on the assessed risk level, it notifies stakeholders and logs structured results into Google Sheets for audit and compliance. Step-by-step Step 1: Contract ingestion and AI analysis Google Drive Trigger – Monitors a specific folder for newly uploaded contract files. Download file – Downloads the uploaded contract from Google Drive. Extract Text From Downloaded File – Extracts readable text or prepares raw content for complex files. AI Contract Analysis – Analyzes legal, commercial, and financial clauses using AI. Format AI Output – Parses and structures the AI response into clean, usable fields. Step 2: Risk alerts and audit logging Alert Teams Automatically – Evaluates risk level and checks for significant risks. Send a message (Risk Alert) – Sends a detailed alert email for medium-risk contracts. Send a message (Info Only) – Sends an informational email when no action is required. Get The Data To Save In Google Sheet (Alert Path) – Prepares alert-related contract data. Get The Data To Save In Google Sheet (Info Path) – Prepares non-alert contract data. Append row in sheet – Stores contract details, risks, and timestamps in Google Sheets. Why use this? Eliminates manual contract screening and repetitive reviews. Detects explicit and inferred risks consistently using AI. Automatically alerts teams only when attention is required. Creates a centralized audit log for compliance and reporting. Scales contract analysis without increasing legal workload.
By Avkash KakdiyaDigitize business cards to Notion database with Gemini Vision OCR
🧩 Summary Easily digitize and organize your business cards! This workflow allows you to upload a business card image, automatically extract contact information using Google Gemini’s OCR & vision model, and save the structured data into a Notion database — no manual typing required. Perfect for teams or individuals who want to centralize client contact info in Notion after networking events or meetings. --- ⚙️ How it works Form Submission Upload a business card image (.jpg, .png, or .jpeg) through an n8n form. Optionally select a category (e.g., Partner, Client, Vendor). AI-Powered OCR (Google Gemini) The uploaded image is sent to Google Gemini Vision for intelligent text recognition and entity extraction. Gemini returns structured text data such as: json { "Name": "Jung Hyun Park", "Position": "Head of Development", "Phone": "021231234", "Mobile": "0101231234", "Email": "abc@dc.com", "Company": "TOV", "Address": "6F, Donga Building, 212, Yeoksam-ro, Gangnam-gu, Seoul", "Website": "www.tov.com" } JSON Parsing & Cleanup The text response from Gemini is cleaned and parsed into a valid JSON object using a Code node. Save to Notion The parsed data is automatically inserted into your Notion database (Customer Business Cards). Fields such as Name, Email, Phone, Address, and Company are mapped to Notion properties. --- 🧠 Used Nodes Form Trigger – Captures uploaded business card and category input Google Gemini (Vision) – Extracts contact details from the image Code – Parses Gemini’s output into structured JSON Notion – Saves extracted contact info to your Notion database --- 📦 Integrations | Service | Purpose | Node Type | |----------|----------|-----------| | Google Gemini (PaLM) | Image-to-text extraction (OCR + structured entity parsing) | @n8n/n8n-nodes-langchain.googleGemini | | Notion | Contact data storage | n8n-nodes-base.notion | --- 🧰 Requirements A connected Google Gemini (PaLM) API credential A Notion integration with edit access to your database --- 🚀 Example Use Cases Digitize stacks of collected business cards after a conference Auto-save new partner contacts to your CRM database in Notion Build a searchable Notion-based contact directory Combine with Notion filters or rollups to manage client relationships --- 💡 Tips You can easily extend this workflow by adding an email notification node to confirm successful uploads. For multilingual cards, Gemini Vision handles mixed-language text recognition well. Adjust Gemini model (gemini-1.5-flash or gemini-1.5-pro) based on your accuracy vs. speed needs. --- 🧾 Template Metadata | Field | Value | |-------|--------| | Category | AI + Notion + OCR | | Difficulty | Beginner–Intermediate | | Trigger Type | Form Submission | | Use Case | Automate business card digitization | | Works with | Google Gemini, Notion |
By JinPark