Workflow Templates

Price Anomaly Detection & News Alert (Marketstack + HN + DeepL + Slack) Overview This workflow monitors a stock’s closing price via Marketstack. It computes a 20-day moving average and standard deviation (±2σ). If the latest close is outside ±2σ, it flags an anomaly, fetches related headlines from Hacker News, translates them to Japanese with DeepL, and posts both original and translated text to Slack. When no anomaly is detected, it sends a concise “normal” report. How it works 1) Daily trigger at 09:00 JST 2) Marketstack: fetch EOD data 3) Code: compute mean/σ and classify (normal/high/low) 4) IF: anomaly? → yes = news path / no = normal report 5) Hacker News: search related items 6) DeepL: translate EN → JA 7) Slack: send bilingual notification Requirements Marketstack API key DeepL API key Slack OAuth2 (bot token / channel permission) Notes Edit the ticker in Get Stock Data. Adjust N (days) and k (sigma multiplier) in Calculate Deviation. Keep credentials out of HTTP nodes (use n8n Credentials).

Who is this for? Dream journaling enthusiasts** who want to visualize and record their dreams Self-improvement practitioners** interested in dream analysis and psychology Content creators** looking for unique, AI-generated dream-based content Wellness coaches and therapists** who use dream work with clients What it does Receives dream descriptions via Telegram bot commands Parses visual style selection from 8 options (cinematic, ghibli, surreal, vintage, horror, abstract, watercolor, cyberpunk) Analyzes the dream using AI to extract themes, symbols, and psychological meaning Generates optimized video prompt tailored to the selected style with audio descriptions Creates AI video with native audio using Google Veo3 (single API call) Logs to Google Sheets as a searchable dream journal Sends video + analysis back to user via Telegram How to set up Estimated setup time: 15 minutes Step 1: Create Telegram Bot Message @BotFather on Telegram Send /newbot and follow prompts Copy the API token Step 2: Get fal.ai API Key Sign up at fal.ai Generate API key from dashboard In n8n, create Header Auth credential: Name: Authorization Value: Key YOUR_FAL_API_KEY Step 3: Get OpenRouter API Key Sign up at openrouter.ai Generate API key Add to n8n as OpenRouter credential Step 4: Set up Google Sheets (Optional) Create new spreadsheet with columns: Timestamp, Username, Style, Dream, Theme, Emotion, Type, Meaning, Video URL Connect Google Sheets credential in n8n Select your document and sheet in the "Log to Google Sheets" node Step 5: Connect Credentials Add Telegram credential to all Telegram nodes Add fal.ai Header Auth to both HTTP Request nodes Add OpenRouter credential to the LLM node Requirements | Service | Purpose | Cost | |---------|---------|------| | Telegram Bot | User interface | Free | | fal.ai (Veo3) | Video + audio generation | ~$0.10-0.15/video | | OpenRouter | LLM for dream analysis | ~$0.01-0.03/request | | Google Sheets | Dream journal storage | Free | How to customize Change LLM**: Replace OpenRouter with OpenAI, Anthropic, or other providers Add styles**: Edit the STYLES object in "Parse Dream Command" node Modify analysis**: Edit system prompt in "AI Dream Analyzer Agent" node Change video model**: Replace Veo3 URL with Kling, Luma, or other fal.ai models Skip logging**: Remove or disable the Google Sheets node Commands | Command | Description | |---------|-------------| | /dream [text] | Generate video in cinematic style | | /dream [style] [text] | Generate with specific style | | /styles | Show all available styles | Example Input: /dream ghibli I was flying over a forest where the trees had glowing leaves Output: 8-second AI video with magical Ghibli-style visuals, ambient soundtrack, plus psychological analysis of flight symbolism and nature connection themes.

Quick Overview This workflow pulls commodity-related headlines from the CNBC RSS feed, filters and ranks the most relevant items, uses Google Gemini to generate an actionable commodity investment briefing, and posts the briefing to a Slack channel with error notifications if the RSS fetch or AI step fails. How it works Runs manually and reads the latest items from the CNBC News RSS feed. Extracts the key fields (title, link, description, date) and removes duplicate articles by title. Filters for commodity and macro keywords (for example oil, crude, gold, inflation), excludes blacklisted terms, and assigns a relevance score to each remaining item. Sorts the news by score, keeps the top three articles, and combines them into a single text block for analysis. Sends the combined news to Google Gemini to generate a daily briefing with key drivers, market impact, investor actions, and supporting commodity price/trend data. Formats the Gemini output and posts it to a selected Slack channel, or sends a Slack alert if the RSS feed fetch or Gemini request errors. Setup Add a Google Gemini (Google PaLM) API credential and select the model you want to use. Add a Slack OAuth credential and choose the channel where the briefing and error alerts should be posted. Confirm the CNBC RSS feed URL is correct and customize the keyword/blacklist lists and scoring logic to match the commodities you track. Replace the manual trigger with a Schedule trigger if you want the briefing to run automatically (for example daily each morning).

Quick overview This workflow runs weekly to audit your n8n workflows with OpenAI, posts improvement reports to Slack, and stores per-workflow scan preferences in an n8n Data Table that users can toggle by reacting with :x: in Slack. How it works Runs weekly on a schedule, retrieves all workflows via the n8n API, and merges them with an n8n Data Table list of workflows that are excluded from scanning. Iterates through the workflows that should be scanned and prepares a cleaned representation of each workflow (nodes, connections, and AI sub-node relationships) for analysis. Uses OpenAI to group the workflow canvas into logical sections and generates a structured overview, then creates and collision-resolves sticky notes to document the workflow before exporting the updated workflow JSON. Parses the exported workflow and uses OpenAI to produce a scored audit report with workflow-level and node-level improvement suggestions. Sends the audit summary, scores, and issues to a Slack channel as a rich block message and adds an :x: reaction to the posted message. Waits briefly and then upserts the workflow’s ID, name, scan flag, and Slack message timestamp into the n8n Data Table for tracking and future runs. Listens for Slack reaction events, and when a user adds or removes an :x: reaction on a report message, updates the Data Table to disable or re-enable scanning for the associated workflow and posts a confirmation to Slack. Setup Create an n8n API key credential and ensure the instance has permission to list workflows. Add OpenAI API credentials for the OpenAI Chat Model nodes. Add Slack OAuth credentials for both the Slack action nodes and the Slack Trigger, and set the target channel where reports and reactions are handled. Run the manual trigger once to create the “AI Workflow Improvements” n8n Data Table and confirm the workflow uses the correct table ID in the Data Table nodes. In Slack, enable event subscriptions for the Slack Trigger and configure the generated webhook so reaction_added and reaction_removed events are delivered for the selected channel. Requirements OpenAI API Key, Slack Account Additional info Need help? Contact us here or visit sailingbyte.com! Happy auditing!

How it works This workflow creates a Slack-based CRM assistant that allows users to query HubSpot data using natural language. When a user mentions the bot in Slack, the message is cleaned and processed to remove Slack-specific formatting. The workflow then retrieves and filters relevant data from HubSpot (deals, companies, and contacts). Finally, an AI agent formats the response and sends a structured reply back to Slack. Step-by-step Trigger on Slack mention** Slack Trigger – Listens for app mentions in Slack channels. Code in JavaScript – Cleans the message by removing Slack IDs and formatting. Fetch and filter CRM data** Get Deals – Retrieves deals from HubSpot. Filter Deals – Filters deals based on the user query. Get many companies – Fetches company records from HubSpot. Filter Companies – Matches companies against the query. Get Contacts – Retrieves contact data from HubSpot. Filter Contacts – Filters contacts using name-based matching. Merge – Combines filtered deals, companies, and contacts into one dataset. Generate and send AI response** AI Agent – Uses AI to format and structure the CRM data into a readable response. Google Gemini Chat Model – Provides the language model for the AI agent. Send a message – Sends the final response back to the Slack channel. Why use this? Enables instant CRM access directly from Slack without logging into HubSpot Simplifies data lookup using natural language queries Combines multiple CRM objects into a single intelligent response Improves team productivity with faster decision-making Easily customizable for additional fields, filters, or AI formatting

Quick overview This workflow runs on a schedule to check flight status against active bookings in Google Sheets, logs an IROPS audit trail, and for severe delays or cancellations uses Anthropic Claude to choose the best alternate flight from inventory and sends passengers an SMS via Twilio. How it works Runs every few minutes on a scheduled trigger. Pulls the latest FlightStatus and active Bookings data from Google Sheets via the Google Sheets API. Matches each active booking to its flight status, calculates an impact level (On Time, Minor Delay, Severe Delay, or Cancelled), and splits the results into one item per passenger. Appends a timestamped status record for every booking to the OpsLog tab in Google Sheets. For bookings marked Cancelled or Severe Delay, fetches alternate flight inventory from Google Sheets and filters to same-route, seats-available options that match the passenger’s cabin class. Sends the candidate flights and passenger context to Anthropic Claude to select the best alternative and generate a short SMS message (with a safe fallback if parsing fails). Writes the rebooking decision to the Rebookings tab in Google Sheets and sends the notification SMS to the passenger using Twilio. Setup Create an Anthropic API credential in n8n and select it for the Anthropic Claude model used to generate rebooking decisions. Add Google OAuth2 credentials (or update the HTTP Request authentication) and replace YOUR_SHEET_ID in all Google Sheets API requests. Prepare a Google Sheet with tabs and headers for FlightStatus, Bookings (with an “Active” status column), Inventory, OpsLog, and Rebookings. Add Twilio credentials (Account SID and auth, plus a Twilio phone number) and replace YOUR_TWILIO_ACCOUNT_SID, YOUR_TWILIO_PHONE_NUMBER, and the Authorization header value in the Twilio request. Adjust the schedule interval and (if needed) the delay thresholds used to classify Minor vs Severe delay before activating the workflow.

Who Is This For? This workflow is designed for Google Ads advertisers, PPC managers, and marketing teams who want to automatically monitor and optimize their search term performance. It's particularly valuable for those running brand campaigns who need to identify and eliminate wasteful ad spend on non-brand keywords. What This Workflow Does This workflow functions as an automated Google Ads performance monitoring and optimization system that: Fetches search term data from active Google Ads campaigns daily Filters out brand terms and excluded search terms automatically Analyzes performance metrics using AI to identify wasteful keywords Generates optimization recommendations for negative keyword lists Sends detailed reports through multiple communication platforms Calculates ad wastage in USD for better budget management Key Features Automated Daily Monitoring** – Runs every day at 8 AM to check campaign performance AI-Powered Analysis** – Uses multiple AI models (DeepSeek, OpenAI, xAI, Anthropic) for intelligent keyword categorization Performance Metrics Calculation** – Automatically calculates CTR, CPC, conversions, and ad wastage Multi-Channel Reporting** – Sends reports to Slack, Microsoft Teams, WhatsApp, and Discord Smart Filtering** – Automatically excludes brand terms and excluded search terms Cost Analysis** – Calculates total ad wastage in USD for budget optimization 14-Day Data Window** – Analyzes search terms from the past 14 days for comprehensive insights Requirements & Setup Google Ads API**: Required for fetching campaign and search term data AI Model APIs**: DeepSeek, OpenAI, xAI, or Anthropic for keyword analysis Communication APIs**: Slack, Microsoft Teams, WhatsApp (Rapiwa), Discord for report distribution Scheduled Trigger**: Configured to run daily at 8 AM Google Ads Manager and Client IDs**: For accessing specific campaign data How It Works Data Collection: Fetches active campaigns and extracts search term data from the past 14 days Data Processing: Cleans and aggregates metrics by search term, campaign, and ad group AI Analysis: Uses AI to categorize keywords into wasteful (zero conversions) and review-worthy (has conversions) Report Generation: Creates structured reports with recommendations and cost analysis Multi-Platform Distribution: Sends formatted reports to all configured communication channels Support & Help WhatsApp**: Chat on WhatsApp Discord**: SpaGreen Community Facebook Group**: SpaGreen Support Website**: https://spagreen.net Developer Portfolio**: Codecanyon SpaGreen

📘 Description This workflow automates guest upsell discovery and recommendation for hotels by combining Google Sheets, OpenAI, and Slack. It is designed to help hospitality teams proactively identify the single best upsell opportunity for each guest—before arrival or during the stay—without manual analysis or guesswork. The workflow runs on a fixed daily schedule and reads guest records from Google Sheets, which acts as the operational source of truth. Guests are automatically categorized based on stay status (upcoming arrivals vs. currently checked in). For each guest, relevant context such as room type, repeat status, spend level, preferences, and special occasions is prepared and passed to an AI engine. The AI deterministically recommends one high-confidence upsell (e.g., room upgrade, airport pickup, spa, dining, or experience), returns a structured JSON response, and explains the reasoning behind the recommendation. The selected upsell type is written back to the spreadsheet for tracking, and a clear, actionable Slack notification is sent to the team so they can act immediately. Any workflow failure triggers a Slack alert, ensuring reliability and operational visibility. ⚙️ What This Workflow Does (Step-by-Step) ⏰ Daily Scheduled Trigger Runs automatically every day at a fixed time. 📊 Read Guest Data from Google Sheets Fetches all guest records from the central spreadsheet. 🔀 Split by Stay Status Routes guests into two paths: before arrival or during stay. 🎯 Prepare Guest Context Extracts guest attributes (room type, spend level, preferences, occasion, stay phase). 🤖 AI Upsell Recommendation Uses OpenAI to recommend one best upsell per guest and returns structured JSON. 🧹 Parse AI Response Cleans and validates AI output to ensure reliability. 💾 Update Guest Record Writes the selected upsell type back into Google Sheets. 💬 Notify Team in Slack Posts a formatted upsell notification with reasoning for immediate action. 🚨 Error Handling → Slack Alert Sends an instant alert if any step in the workflow fails. 🧩 Prerequisites • Google Sheets OAuth2 (read/write) • OpenAI API key (GPT-4o-mini) • Slack API credentials • Self-hosted n8n recommended 💡 Key Benefits ✔ Identifies high-value upsell opportunities automatically ✔ Context-aware AI recommendations (not generic offers) ✔ Clear before-arrival vs. during-stay logic ✔ Real-time team visibility via Slack ✔ Centralized tracking in Google Sheets ✔ Built-in error monitoring 👥 Perfect For Hotels and resorts Revenue and upsell teams Front-desk and concierge teams Hospitality operators focused on guest experience and ARPU growth

Job Search Automation with Job Search Global API & Google Sheet Logging Description: Automate your job search process by querying the Job Search Global API via RapidAPI every 6 hours for a specified keyword like “Web Developer.” This workflow extracts job listings and saves them directly to Google Sheets, with alerts sent for any API failures. Workflow Overview Schedule Trigger Runs the workflow automatically every 6 hours to ensure up-to-date job listings. Set Search Term Defines the dynamic job keyword, e.g., "Web Developer," used in API requests. Fetch Job Listings Sends a POST request to the Job Search Global API (via RapidAPI) to retrieve job listings with pagination. Check API Response Validates the API response status, branching workflow on success or failure. Extract Job Data Parses the job listings array from the API response for processing. Save to Google Sheet Appends or updates job listings in Google Sheets, avoiding duplicates by matching job titles. Send Failure Notification Email Sends an alert email if the API response fails or returns an error. How to Obtain Your RapidAPI Key (Quick Steps) Go to RapidAPI Job Search Global API. Sign up or log in to your RapidAPI account. Subscribe to the API plan that suits your needs. Copy your unique X-RapidAPI-Key from the dashboard. Insert this key into your workflow’s HTTP Request node headers. How to Configure Google Sheets Create a new Google Sheet for job listings. Share the sheet with your Google Service Account email to enable API access. Use the sheet URL in the Google Sheets node within your workflow. Map columns correctly based on the job data fields. Google Sheet Columns Used | Column Name | Description | | ----------- | ----------------------------------- | | title | Job title | | url | Job posting URL | | company | Company name | | postDate | Date job was posted | | jobSource | Source of the job listing | | slug | Unique job identifier or slug | | sentiment | Sentiment analysis score (if any) | | dateAdded | Date the job was added to the sheet | | tags | Associated tags or keywords | | viewCount | Number of views for the job post | Use Cases & Benefits Automated Job Tracking:** Get fresh job listings without manual searching by automatically querying the Job Search Global API multiple times per day. Centralized Job Data:** Save and update listings in Google Sheets for easy filtering, sharing, and tracking. Failure Alerts:** Get notified immediately if API calls fail, helping maintain workflow reliability. Customizable Search:** Change keywords anytime to tailor job searches for different roles or industries. Who Is This Workflow For? Recruiters** looking to monitor job market trends in real-time. Job Seekers** who want to automate job discovery for specific roles like “Web Developer.” HR Teams** managing talent pipelines and job postings. Data Analysts** needing structured job market data for research or reporting. 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!

📘 Description: This workflow automates the incident response lifecycle — from creation to communication and archival. It instantly creates Jira tickets for new incidents, alerts the on-call Slack team, generates timeline reports, logs the status in Google Sheets, and archives documentation to Google Drive — all automatically. It helps engineering and DevOps teams respond faster, maintain audit trails, and ensure no incident details are lost, even after Slack or Jira history expires. ⚙️ What This Workflow Does (Step-by-Step) 🟢 Manual Trigger – Start the incident creation and alerting process manually on demand. 🏷️ Define Incident Metadata – Sets up standardized incident data (Service, Severity, Description) used across Jira, Slack, and Sheets for consistent processing. 🎫 Create Jira Incident Ticket – Automatically creates a Jira task with service, severity, and description fields. Returns a unique Jira key and link for tracking. ✅ Validate Jira Ticket Creation Success – Confirms the Jira ticket was successfully created before continuing. True Path: Proceeds to Slack alerts and documentation flow. False Path: Logs the failure details to Google Sheets for debugging. 🚨 Log Jira Creation Failures to Error Sheet – Records any Jira API errors, permission issues, or timeouts to an error log sheet for reliability monitoring. 🔗 Combine Incident & Jira Data – Merges incident context with Jira ticket data to ensure all details are unified for downstream notifications. 💬 Format Incident Alert for Slack – Generates a rich Slack message containing Jira key, service, severity, and description with clickable Jira links. 📢 Alert On-Call Team in Slack – Posts the formatted message directly to the #oncall Slack channel to instantly notify engineers. 📋 Generate Incident Timeline Report – Parses Slack message content to create a detailed incident timeline including timestamps, service, severity, and placeholders for postmortem tracking. 📄 Convert Timeline to Text File – Converts the generated timeline into a structured .txt file for archival and compliance. ☁️ Archive Incident Timeline to Drive – Uploads the finalized incident report to Google Drive (“Incident Reports” folder) with timestamped filenames for traceability. 📊 Log Incident to Status Tracking Sheet – Appends Jira key, service, severity, and timestamp to the “status update” Google Sheet to build a live incident dashboard and enable SLA tracking. 🧩 Prerequisites Jira account with API access Google Sheets for “status update” and “error log” tracking Slack workspace connected via API credentials Google Drive access for archival 💡 Key Benefits ✅ Instant Slack alerts for new incidents ✅ Centralized Jira ticketing and tracking ✅ Automated timeline documentation for audits ✅ Seamless Google Drive archival and status logging ✅ Reduced MTTR through faster communication 👥 Perfect For DevOps and SRE teams managing production incidents Engineering managers overseeing uptime and reliability Organizations needing automated post-incident documentation Teams focused on SLA adherence and compliance reporting

Think of this workflow as your personal news assistant that: Monitors multiple technology websites 24/7 Uses AI to read and understand each article Filters out low-quality content automatically. Saves the best articles to Notion with summaries. Sends you Telegram alerts for must-read content. Prerequisites (What You Need Before Starting) 1. Notion Account (Free) Sign up at notion.so You'll store all curated articles here 2. OpenAI Account (Paid) Sign up at platform.openai.com Cost: $0.01-0.02 per article ($15-30/month for 50 articles/day) Needed for AI content analysis 3. Telegram Account (Free) Download Telegram app Needed for instant notifications 4. RSS Feed URLs (Free) Included: TechCrunch, Dev.to, The Verge Optional: Add your own favorite tech blogs Step-by-Step Configuration STEP 1: Create Your Notion Database 1.1 Create New Database Open Notion (notion.so) Click "+ New Page" Select "Table" view Name it "Content Curator" 1.2 Add Required Properties Click "+ New Property" and add each: Title** (Rich Text) - Already exists by default URL** (URL type) Summary** (Rich Text) Category** (Select) - Add options: Technology, AI, Business, DevOps, Other Tags** (Rich Text) Sentiment** (Select) - Add options: Positive, Neutral, Negative Priority** (Number) Source** (Rich Text) Published** (Date) Added Date** (Date) Status** (Select) - Add options: New, Read, Archived 1.3 Get Database ID Open your Notion database Click "Share" button (top right) Click "Copy Link" Extract the ID from URL: URL: https://www.notion.so/28e3a42420b2801e8ef5c680e49afc2e ID: 28e3a42420b2801e8ef5c680e49afc2e Save this ID - you'll need it multiple times STEP 2: Create Notion Integration 2.1 Create Integration Go to: notion.so/my-integrations Click "+ New Integration" Name: "RSS Content Curator" Select your workspace Click "Submit" Copy the "Internal Integration Token" (starts with secret_) IMPORTANT: Save this token safely! 2.2 Connect Integration to Database Open your "Content Curator" database in Notion Click "•••" (three dots, top right) Scroll to "Add connections" Select "RSS Content Curator" Click "Confirm" STEP 3: Set Up OpenAI Go to: platform.openai.com Sign up or log in Add payment method (required) Navigate to: platform.openai.com/api-keys Click "+ Create new secret key" Name: "n8n-content-curator" Copy the key (starts with sk-) IMPORTANT: You can't see this key again - save it now! STEP 4: Create Telegram Bot 4.1 Create the Bot Open Telegram app Search for "@BotFather" Start chat with BotFather Send: /newbot Follow prompts: Bot name: "My Content Curator" Username: "my_content_curator_bot" Copy the HTTP API token Save this token 4.2 Get Your Chat ID Search for your bot in Telegram Start a chat and send any message Open in browser: https://api.telegram.org/bot<YOUR_BOT_TOKEN>/getUpdates (Replace <YOUR_BOT_TOKEN> with your actual token) Find "chat":{"id": followed by a number Copy that number (e.g., 8346316847) Save this Chat ID STEP 5: Import Workflow to n8n Log in to n8n Click "Workflows" → "Add Workflow" Click three dots (⋮) → "Import from File" Select RSS_AI_Content_Curator_Enhanced.json Click "Import" STEP 6: Configure Notion Credentials Four nodes need Notion connection: Get Existing Articles Get Old Articles (>30 days) Save to Notion Archive Old Articles For EACH node: Click the node Find "Credential to connect with" Click "Create New" Select "Notion API" Name: "My Notion Curator" Paste your Integration Token from Step 2.1 Click "Save" Update Database IDs: In each Notion node, find "Database ID" field Click refresh icon next to it Select "From list" Choose your "Content Curator" database Test: Click "Execute Node" Success = green checkmark ✓ STEP 7: Configure OpenAI Credentials Click on "AI Content Analysis" node Find "Authentication" section Under "HTTP Header Auth", click "Create New" Fill in: Name: Authorization Value: Bearer sk-YOUR_API_KEY_HERE (Replace with your actual OpenAI key from Step 3) Click "Save" STEP 8: Configure Telegram Credentials Click on "Telegram Notification" node Under "Credential to connect with", click "Create New" Select "Telegram API" Name: "My Telegram Bot" Paste Bot Token from Step 4.1 Click "Save" Update Chat ID: In "Telegram Notification" node Find "Chat ID" field Paste your Chat ID from Step 4.2 Test: Click "Execute Node" STEP 9: Test the Workflow Manual Test Run Verify all nodes show green (no errors) Click "Execute Workflow" (top right) Watch nodes light up in sequence Check for red error nodes If all green: Open Notion - should see new articles Check Telegram - may see notification if high-priority article found Expected Results: Workflow fetches from 3 RSS feeds Removes duplicate articles Checks which are new (not already in Notion) AI analyzes each article (summary, category, priority) Articles with priority ≥60 saved to Notion High-priority articles trigger Telegram notification STEP 10: Activate Automatic Execution Replace Manual Trigger Click "Manual Trigger" node Press Delete Click "+" to add node Search "Schedule Trigger" Select it Configure Schedule Choose one: Every 4 hours:** More updates, higher cost Every 6 hours:** Balanced (recommended) Every 12 hours:** Lower cost Daily at specific time:** Minimal cost Example for every 6 hours: Mode: "Every X" Value: 6 Unit: Hours Activate Click toggle switch (top right) Should turn green: "Active" Workflow now runs automatically!

Enterprise Legal Vault: AI Classification & Multi-Jurisdictional Security 🎯 Description This enterprise-grade legal document management system provides end-to-end automation for securing, classifying, and managing the lifecycle of sensitive documents. It is designed to handle high-stakes data across multiple jurisdictions (GDPR, CCPA, HIPAA) with AI-powered intelligence. ✨ What This Workflow Does Intelligent Intake & Deduplication - Monitors Google Drive, Email, and Webhooks. It uses SHA-256 fingerprinting to ensure every document is unique and to prevent redundant processing. AI-Powered Analysis Engine - Utilizes OpenAI/Claude to classify documents (NDA, MSA, Employment Agreements), detect jurisdiction, and assign a composite Risk Score (1-100). Dynamic Security Enforcement - Translates business rules from Airtable into technical enforcement using the HTML to PDF (Lock) node: Ultra-High Risk (90+): AES-256 encryption with disabled Print, Copy, and Modify permissions. High Risk (50-89): AES-128 encryption with dynamic recipient-specific watermarking. Public Filings: Timestamped watermarking with no encryption. Lifecycle & Retention Automation - Automatically calculates retention expiry dates based on legal requirements. It sets Google Calendar renewal reminders at 90, 60, and 30-day intervals. Intelligent Distribution Matrix - Verified: Attached to HubSpot Deals and synced to Dropbox client folders. Review: Flagged items are sent to a manual review queue with a Slack preview. Failed: Isolated in a Quarantine folder with incident logging in Airtable. 💡 Key Features Jurisdictional Logic:** Automatically adapts security and retention rules based on regional laws fetched from Airtable. Forensic Watermarking:** Embeds tracking data (User ID, Timestamp) to deter and identify data leaks. Fail-Safe Quarantine:** Prevents unverified or risky documents from ever entering the primary company storage. 📦 Requirements HTML to PDF Node* - Essential for tiered *Lock** operations. Airtable** - Acts as the central "Business Rules Engine." Google Drive & HubSpot** - For storage and CRM synchronization. OpenAI/Claude API** - For document classification and risk assessment. 🚀 Benefits ✅ Zero Manual Security Setup - Documents are locked according to corporate policy the moment they are uploaded. ✅ Regulatory Compliance - Meets strict GDPR "Right to be Forgotten" and data localization standards automatically. ✅ Proactive Risk Management - High-liability clauses and auto-renewals are flagged instantly to the legal team. Tags: #legal #compliance #pdf-lock #encryption #gdpr #sec-ops #hubspot #airtable Category: Legal & Compliance Difficulty: Advanced