NEW VIDEO: Full AI Video Automation Workflow for Local Businesses Just dropped a complete breakdown of the video automation system I'm selling to chiropractors. What's inside: → The entire n8n workflow, node by node → How the AI segments scripts and matches B-roll automatically → Why image-first video generation beats text-to-video → The prompting strategy that took $50 to figure out → Cost breakdown per video (under $5) → How I price it ($27 / $47 / $67 per month tiers) → The client portal where users manage campaigns Tools used: n8n, Claude Opus 4.5, ElevenLabs, Minimax, Kling 2.6 Pro, HeyGen, FAL.ai, Shotstack Watch here: https://youtu.be/j6S7m_FS2x0 Drop your questions below — especially if you want me to go deeper on the prompting.

New vendor. 15-page privacy policy. Legal review takes 2 weeks. We need to sign this week. Built GDPR scanner. Policy scored 42%. Three gaps flagged. Remediation requested before signing. THE COMPLIANCE REVIEW BOTTLENECK: Every vendor needs privacy review. Legal team backlogged. Policies written in legalese. Required elements buried in paragraphs. Signed contract. Discovered GDPR gap. Six months of remediation. THE DISCOVERY: Document extraction checks all GDPR requirements. Code calculates compliance score. Gaps identified automatically. Systematic verification. Same checklist every time. Nothing missed. THE WORKFLOW: Google Drive trigger watches policies folder → Download document → Document extraction checks data controller, DPO contact, user rights, legal bases, international transfers → Code calculates compliance score and identifies gaps → Sheets logs scan results → IF checks if not compliant → Alert Slack with specific gaps. 7 nodes. Vendor compliance automated. THE COMPLIANCE SCORING: Code checks 6 required user rights: Access, Rectification, Erasure, Portability, Objection, Withdraw Consent. Score starts at 100%. Deducts 10% per gap: - Missing DPO contact - No legal basis - No breach notification - International transfers without safeguards - Missing user rights THE STATUS THRESHOLDS: - 80% and above: Compliant - 50-79%: Needs Attention - Under 50%: Non-Compliant Conditional alert only for non-compliant policies. Specific gaps listed. THE TRANSFORMATION: Before: 2-4 hours per policy for manual review. Gaps discovered after contract signed. Inconsistent checking. After: 45 seconds with compliance score. Issues flagged before relationship begins. THE NUMBERS: 23 policies scanned last month 8 non-compliant policies caught 14 missing user rights identified 2 hours → 45 seconds per review Template in n8n and All workflows in Github

In this video I'm going to be teaching you how I'd make money with AI in 2026, if I had to start over from scratch. This will be the most actionable video you've ever seen about making money with AI. I'll breakdown everything, and fitting it all into this easy to learn 24 minute guide. Hope you enjoy!

Added 2 nodes to community template. Posted as free download. Healthcare IT consultant DM'd: "Can I deploy this to my clinic clients commercially?" He deployed to 6 clinics. I get paid for all of them. $720/month recurring. THE B2B2C DISCOVERY: Built patient intake form automation. Posted to n8n community forum. Expected: Maybe some GitHub stars and feedback. Got: Message from consultant serving 15 healthcare clinics. "This is exactly what my clients need. Can I use it commercially?" THE DEAL STRUCTURE: He becomes authorized reseller: - Deploys my template to his clinic clients - Handles all client customization (forms, fields, branding) - Manages client relationships and support - I provide template updates and technical escalation support THE ECONOMICS: My pricing to consultant: - $600 setup per clinic - $120/month per clinic His pricing to clinics: - $1,800 setup per clinic - $300/month per clinic His margin: - $1,200 per clinic setup - $180/month per clinic ongoing EVERYONE WINS: - Clinics: Get automation they desperately need - Consultant: New revenue stream from existing clients (no acquisition cost) - Me: Scale without sales effort or client management CURRENT NUMBERS: - Clinics deployed: 6 (3 more in pipeline) - My monthly recurring: $720 - Setup revenue collected: $3,600 - My time after initial template: 4 hours total - His total client base: 15 clinics THE MULTIPLIER MATH: If half his clinics deploy (7-8 clinics): - My monthly recurring: $960-$1,080 - From ONE consultant relationship And he's already referring other healthcare IT consultants in his network. HOW TO FIND MULTIPLIER PARTNERS: Look for consultants who: - Serve 10+ similar clients (healthcare IT, accounting tech, legal tech) - Have relationships but lack automation expertise - Want new revenue streams from existing clients You have automation. They have distribution. WHAT MAKES TEMPLATES REUSABLE: Good B2B2C templates: - Solve common problem across industry (patient intake, invoice processing)

Finance team categorizing expenses manually. Every receipt. Every transaction. Someone reads merchant name. Decides category. Types it in. Built 8-node workflow. 2,400 expenses last quarter. Zero manual sorting. AI handles categorization. THE CATEGORIZATION NIGHTMARE: Is Uber travel or transportation? Is that Amazon purchase office supplies or equipment? Starbucks - meals or client entertainment? Every person categorizes differently. Audit comes. Categories inconsistent. Explanation needed for every decision. THE DISCOVERY: Document extraction returns category as enum. AI picks from predefined list. Same logic every time. But AI isn't perfect. Added merchant keyword fallback. Uber always maps to Travel. Starbucks always maps to Meals. Consistency wins. THE WORKFLOW: Google Drive trigger watches receipts folder → Download expense document → Document extraction pulls merchant, amount, date, category → Code processes and applies keyword fallback → Sheets logs to expense tracker → IF checks threshold → Over $500 triggers Slack approval → Under $500 confirms logged. 8 nodes. Categorization automated. THE SMART CATEGORIZATION: JSON Schema includes category enum: Travel, Meals, Office Supplies, Software, Equipment, Marketing, Professional Services, Utilities, Other. AI picks best match. Code validates against merchant keywords. Known merchants get consistent categories regardless of AI interpretation. THE APPROVAL ROUTING: Threshold-based logic. Anything over $500 requires manager approval. Slack notification with full details. Everything else auto-logged. No more $3,000 "office supplies" purchases slipping through. Manager sees it immediately. THE TRANSFORMATION: Before: 15 minutes per expense report reviewing categories. Arguments about what counts as what. Inconsistent across team. After: Zero time categorizing. Consistent logic. Manager only reviews high-value items. THE NUMBERS: 2,400 expenses processed last quarter 9 category types automated $500 approval threshold