Automate regulatory compliance monitoring with ScrapeGraphAI and email alerts
How it works This workflow automatically monitors government regulatory changes and provides comprehensive compliance tracking and executive alerts. Key Steps Scheduled Monitoring - Runs daily at 9 AM to check for new regulatory changes from government sources. AI-Powered Scraping - Uses ScrapeGraphAI to extract regulatory information from Federal Register and government websites. Impact Assessment - Analyzes each regulation for business impact, risk factors, and compliance requirements. Compliance Tracking - Creates detailed tracking records with assigned teams, deadlines, and action items. Executive Alerts - Sends prioritized alerts to relevant teams based on impact level and urgency. Set up steps Setup time: 10-15 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key for web scraping capabilities. Set up email connections - Configure email service to send executive alerts to compliance and legal teams. Customize monitoring targets - Update the government website URLs to monitor specific agencies or regulatory bodies. Adjust alert recipients - Configure email distribution lists for different impact levels (Critical, High, Medium, Low). Set up compliance tracking - Integrate with your project management system for task assignment and progress tracking. Key Features Automated Impact Assessment - Uses AI to evaluate regulatory impact on your business sectors Priority-Based Alerts - Sends urgent notifications for critical regulations requiring immediate attention Compliance Task Generation - Automatically creates compliance checklists and action items Team Assignment - Routes regulations to appropriate teams based on impact level Deadline Tracking - Monitors comment deadlines, effective dates, and review timelines
By vinci-king-01Automate bank statement and invoice reconciliation with GPT and Google Sheets
🟢 Manual Trigger Workflow starts manually to initiate the reconciliation process on demand. 📄 Fetch Invoices & Bank Statements Retrieves invoice data and bank statement data from Google Sheets for comparison. 🔀 Merge Data Combines both datasets into a single structured dataset for processing. 🧩 Format Payload for AI Function node prepares and structures the merged data into a clean JSON payload for AI analysis. 🤖 AI Reconciliation AI Agent analyzes the invoice and bank statement data to identify matches, discrepancies, and reconciled entries. 🧮 Parse AI Output Parses the AI response into a structured format suitable for adding back to Google Sheets. 📊 Update Sheets Adds the reconciled data and reconciliation results into the target Google Sheet for recordkeeping. 🧾 Prerequisites ✅ OpenAI API Credentials Required for the AI Reconciliation node to process and match transactions. Add your OpenAI API key in n8n → Credentials → OpenAI. ✅ Google Sheets Credentials Needed to read invoice and bank statement data and to write reconciled results. Add credentials in n8n → Credentials → Google Sheets. ✅ Google Sheets Setup The connected spreadsheet must contain the following tabs: Invoices – for invoice data Bank_Statement – for bank transaction data Reconciled_Data – for storing the AI-processed reconciliation output ✅ Tab Structure & Required Headers Invoices Sheet Columns: Invoice_ID Invoice_Date Customer_Name Amount Status Bank_Statement Sheet Columns: Transaction_ID Transaction_Date Description Debit/Credit Amount Reconciled_Data Sheet Columns: Invoice_ID Transaction_ID Matched_Status Remarks Confidence_Score ⚙️ n8n Environment Setup Ensure all nodes are connected correctly and the workflow has permission to access the required sheets. Test each fetch and write operation before running the full workflow.
By Chintan Prajapati