Accountant friend drowning in tax documents every January. Asked if automation could help organize client paperwork. Built tax document organizer using PDF Vector. Changed their tax season. THE CLIENT PROBLEM: CPA with 45 clients. Tax season: Clients email W-2s, 1099s, receipts. Everything arrives in inbox chaos. Manual process: Download documents. Read to identify form type. Create folders. File by category. Update tracking spreadsheet. 12-15 hours weekly just organizing. Not even doing tax prep yet. WHAT I BUILT: Workflow monitoring email. Tax document arrives, PDF Vector extracts form type, tax year, taxpayer info, amounts. Categorizes automatically. Files to Drive folders. Updates spreadsheet. Email → PDF Vector Extract → Categorize → Drive → Checklist. Seven nodes powered by PDF Vector extraction. Handles any tax form format. W-2 from employer A different than employer B. PDF Vector extracts consistently. Extracts structured data: Form type, tax year, taxpayer name/SSN, income amounts, deduction amounts, totals. Schema ensures all required fields captured. Perfect for tax accuracy. THE FIRST DOCUMENT: Tested with actual W-2. 30 seconds later: Form identified. Tax year extracted. Taxpayer captured. Amounts extracted. Filed correctly. Spreadsheet updated. Accountant: "It just read the entire W-2 and organized everything? Incredible." PROCESSING MULTIPLE: Client sends W-2, 1099-INT, mortgage statement. Workflow splits attachments. Processes each separately. All three organized in 90 seconds. THE ACCOUNTANT IMPACT: 45 clients × 5 documents = 225 documents. Before: 12-15 hours weekly organizing. After: 30 minutes reviewing folders. Saves 11.5 hours weekly during tax season. 46 hours monthly. Accountant does billable tax prep instead of filing. Testimonial: "Paid for itself first week. Can take more clients without hiring help." THE EXPANSION: Started with individual tax clients. Accountant wants small business version for quarterly documents. Same PDF Vector approach. Additional revenue.

Clinic administrator frustrated with new patient intake data entry. Asked if automation could help. Built patient intake processor using PDF Vector. Changed their onboarding. THE CLIENT PROBLEM: Family practice. 35 new patients monthly. Each submits intake form with demographics, insurance, emergency contacts, medications, allergies, medical history. Manual process: Download form. Read through. Type everything into system. Check completeness. Email welcome or request missing info. 15 minutes per patient. 8.75 hours monthly on intake data entry. WHAT I BUILT: Workflow monitoring email for intake forms. PDF Vector extracts patient name, DOB, address, phone, email, insurance provider, policy number, emergency contact with name/phone/relationship, medications, allergies, medical history. Adds to Google Sheets database automatically. Validates required fields. Sends welcome email if complete or requests missing information. Email → PDF Vector Extract → Database → Validate → Email Patient. Seven nodes powered by PDF Vector extraction. WHY PDF VECTOR: Handles any intake form format. Handwritten forms, typed PDFs, scanned images. PDF Vector extracts consistently. Extracts structured healthcare data: Patient demographics, insurance details, contact information, medical arrays (medications, allergies). Schema-based extraction ensures all fields captured. Critical for healthcare compliance. THE FIRST FORM: Tested with actual form. 30 seconds: Patient name extracted. DOB, address, phone, email captured. Insurance extracted. Emergency contact with relationship captured. 3 medications, 2 allergies extracted. Added to database. Welcome email sent. Administrator: "It read the entire form and added everything to our system? Exactly what we need." PROCESSING MONTHLY: 35 new patients monthly submit forms via email. By month end: All 35 patients extracted, added to database, welcomed or contacted for completion. Review time: 10 minutes monthly spot-checking. Before: 8.75 hours monthly manual data entry.

Scaling company. Growing headcount. Onboarding process breaking down. Different departments. Different requirements. Manual coordination failing. Built automated onboarding system with department-specific workflows. THE CLIENT'S SITUATION: Rapid growth phase. 12 new hires in 3 months. Engineering, Sales, Marketing, Operations. Each department needs different setup. HR maintaining master spreadsheet. Task list generic. Doesn't account for department differences. IT receiving email requests. Facilities getting separate messages. Manager coordinating independently. Results inconsistent. Engineer missing development access. Sales rep without CRM login. Marketing coordinator lacking design software. First week productivity zero while waiting for access. Cross-department visibility none. HR doesn't know IT status. IT doesn't know Facilities progress. Manager asking everyone individually for updates. Time consuming. Error prone. THE AUTOMATION WORKFLOW: 8-node system using Google Drive monitoring, PDF Vector document extraction, dynamic checklist generation, Google Sheets database, Gmail manager notifications, and Slack team alerts. Drive trigger watches HR onboarding folder. New employee document detected automatically. System downloads and processes. PDF Vector extracts employee data - name, contact info, position, department, manager, start date, benefits, accommodations. Checklist engine generates role-based tasks. Base tasks: email, equipment, workspace, payroll, benefits, background check, welcome, orientation, buddy, security. Department tasks added automatically. Due dates calculated from start date. Background check 10 days before, equipment 7 days before, desk 3 days before. Urgency analyzer tracks status. Readiness score: 100 minus penalties for overdue/urgent tasks. Google Sheets database logs complete employee records with full tracking history. Manager email provides comprehensive onboarding summary with action items. Slack sends urgent alerts or team welcome announcements.

E-commerce client. 380 orders monthly. Treating all customers identically. Built automated order processor with VIP segmentation. THE CLIENT'S CHALLENGE: Manual order processing. Download PDF. Type details. Check inventory. Validate credit. Select carrier. 35 minutes each. No customer tier awareness. $500K lifetime VIP waits same 2 days as $500 first-time buyer. Rush deliveries queued with standard. Credit checks inconsistent. Problems mounting: - 42 duplicate orders shipped ($127K) - 67 credit limit violations ($182K at risk) - 89 VIP service failures (complaints) - Inventory checks miss stock-outs regularly THE AUTOMATION: 10-node workflow with tier-based intelligence: Gmail Trigger → Extract Order → PDF Vector Segmentation → Duplicate Check → Multi-Warehouse Inventory → Credit Validation → 7-Factor Fraud → Priority Scoring →Smart Carrier → [Auto-Fulfill] OR [Manual Review] CUSTOMER SEGMENTATION DATABASE: Platinum tier ($500K+ lifetime): Same-day processing, free express shipping, 15% discount, $50K credit limit Gold tier ($250K+): 1-day processing, free ground shipping, 10% discount, $100K credit limit Silver/Bronze/New: Standard 2-day processing, standard rates DUPLICATE DETECTION: Fingerprint: Customer name + PO number Check: Historical order database Result: Zero duplicates processed since deployment 100-POINT PRIORITY SYSTEM: VIP status: +50 points (platinum/gold) Rush delivery ≤3 days: +40 points High value >$25K: +30 points All in stock: +10 points Critical: Same-day High: 1-day Standard: 2-day MULTI-WAREHOUSE INVENTORY: Three warehouses: US-EAST, US-WEST, US-CENTRAL Geographic routing by customer state. Primary warehouse checked first. Falls back to secondary if primary out of stock. Identifies split shipments automatically. 7-FACTOR FRAUD DETECTION: 1. High value order >$50K 2. Large item count >20 items 3. New customer + large order 4. Pricing calculation mismatch 5. New shipping address + large value 6. Price variance 100%+

Legal client. 47 vendor contracts monthly. Manual review consuming 376 hours. Built automated contract analyzer. THE CLIENT'S MANUAL PROCESS: Contracts arriving. Legal downloads PDFs. Reads documents. Extracts terms into spreadsheet. Identifies renewal clauses. Checks auto-renewal. Calculates notice deadlines. Creates reminders. Reviews liability provisions. Searches for cap language. Notes indemnification. Checks IP ownership. Inspects data privacy. Scores compliance subjectively. Checks critical clauses - liability cap, termination rights, IP provisions, data privacy. Classification based on judgment. Tracks obligations manually. Deliverables, payments, renewals, insurance. Manual calendar. Routes for approval informally. Legal director for high value. General counsel for high risk. Criteria inconsistent. 8 hours per contract. 47 monthly. 376 hours consumed. Audit problems - 18 auto-renewal deadlines missed ($284K). 23 contracts missing critical clauses. 31 obligations missed ($52K penalties). 67% accuracy. THE AUTOMATION: 8-node workflow: Google Drive Trigger → Download Contract → PDF Vector Extract → Red Flag Detection → Compliance Scoring → Smart Alert Engine → Database Log → Risk Router → [Critical #legal] OR [Standard #contracts] EXTRACTION: Parties, type, dates, value, currency, payment terms/schedule, renewal clause, auto-renewal, renewal notice, termination notice, penalties, liability cap, indemnification, IP ownership, data privacy, governing law, arbitration, force majeure, SLA, audit rights, insurance, obligations RED FLAG DETECTION: Analyzes risks - unlimited liability, auto-renewal traps, evergreen terms, missing clauses, one-sided indemnification, unusual jurisdiction. Critical risk score 0-100. COMPLIANCE SCORING: Objective 0-100 score checking 10 provisions: liability cap, governing law, termination clause, renewal terms, payment terms, defined duration, IP provisions, data privacy, force majeure, indemnification. Risk level: critical (<50), high (50-70), medium (70-85), low (85+).