Laptop acting up. Warranty? No idea. Checked tracker. 14 days remaining. Filed claim. Got replacement. Built warranty tracker. Every warranty organized. Expiration alerts automatic. Zero claims missed. THE WARRANTY FORGOTTEN PROBLEM: Buy product. Get warranty. File receipt somewhere. Product breaks. Search everywhere. Warranty expired last month. Average household has 15-20 active warranties. Average person tracks zero systematically. THE DISCOVERY: Document extraction pulls warranty terms. Code calculates expiration date. Conditional alert triggers when approaching deadline. 30-day advance warning. Every warranty. No surprises. THE WORKFLOW: Google Drive trigger watches warranty folder → Download document → Document extraction pulls product details, purchase date, warranty duration, coverage terms → Code calculates expiration date and days remaining → Sheets logs to warranty tracker → IF checks if expiring within 30 days → Alert Slack when expiring soon. 7 nodes. Warranty money protected. THE EXPIRATION LOGIC: Code calculates: Purchase date + Warranty months = Expiration date. Status determined by days remaining: - Negative: Expired - Under 30: Expiring Soon (triggers alert) - Under 90: Active - Expires Soon - Over 90: Active THE CONDITIONAL ALERT: Only Expiring Soon status triggers Slack. No spam for healthy warranties. Alert when action needed. Product name, days remaining, coverage details included. Decision-ready information. THE TRANSFORMATION: Before: Warranty documents scattered. Expirations forgotten. Claims missed after products break. After: Central tracker. Proactive alerts. Zero expired warranty surprises. THE NUMBERS: 23 warranties tracked $3,200 in claims protected 4 expiring warranties alerted 3 already-expired discovered (lessons learned) Template in n8n and All workflows in Github

American Bank. 35 million documents. No organization. 275 different document types mixed together. Manual classification would take years. AI did it in 2 weeks. THE DOCUMENT NIGHTMARE: Decades of files: - Loan applications - Bank statements - Tax returns - Asset verification - Compliance filings - Historical records All in shared drives. No naming convention. No searchable index. Compliance audits = nightmare. "Find all 2018 commercial loan docs" = weeks of manual searching. THE 4-NODE WORKFLOW: 1. Scan document folders 2. Convert PDFs and images to text 3. Classify by document type (loan app, tax return, etc.) 4. Extract key metadata (date, account number, dollar amount) 5. Build searchable database THE CHALLENGE: 35 million documents = expensive if you process everything. Solution: Process in batches, prioritize by business need: - Regulatory compliance docs first (immediate audit risk) - Active account documents second - Historical archives last Total processing: 2 weeks for critical docs, 3 months for full archive. THE IMPACT: Before: - Audit request: "All 2020 mortgage applications" - Time to comply: 2-3 weeks manual search - Cost: $18,000 in staff time After: - Same request: 15 minutes database query - Cost: $0 incremental - Audit compliance time: 94% reduction THE MORTGAGE PROCESSING USE CASE: Once classified, built automated loan processing: - Applicant uploads docs - System pulls income, employment, assets - Pre-fills underwriting system - Flags missing documents Loan processing: 30 days → 3 days. THE SALES ANGLE: Don't sell "document classification." Sell "you have 35 million documents you can't find when auditors ask. I make them searchable in 2 weeks." Compliance fear > efficiency desire. 📚 All templates library in Github What business has years of documents they can't search when they need them?