n8n AI Operating Model Audit Platform

Enterprise-grade platform for automating AI Operating Model audits using n8n workflows. Generates consultant-grade reports with financial analysis, ROI calculations, and implementation roadmaps.

🎯 Overview

This repository provides a complete infrastructure and workflow solution for running AI Operating Model audits at scale. Built on n8n, it combines data collection, AI analysis, and comprehensive report generation to deliver consulting-quality deliverables at a fraction of the cost.

Key Features

• 🚀 Multiple Deployment Options - Docker Compose, Kubernetes, or Caddy reverse proxy
• 📊 Pre-built Workflow Templates - Production-ready audit workflows (Standard & Premium)
• 🔗 Multi-source Integration - Google Sheets, Airtable, Google Drive, Slack, Supabase
• 🤖 AI-Powered Analysis - GPT-4 driven report generation with cost optimization
• 💰 Cost Efficient - $0.006-$0.99 per audit vs $15K-$50K consulting fees
• ⚡ Performance Optimized - Parallel execution, 50% faster than sequential approaches
• 🛡️ Production Ready - Error handling, data validation, comprehensive logging

📋 Table of Contents

• Quick Start
• Workflows
• Deployment Options
• Prerequisites
• Configuration
• Documentation
• Cost Analysis
• Architecture
• Contributing
• License

🚀 Quick Start

1. Choose Your Deployment

# Option 1: Docker Compose with PostgreSQL (Recommended)
cd docker-compose/withPostgres
cp .env.example .env
# Edit .env with your credentials
docker-compose up -d

# Option 2: Kubernetes
cd kubernetes
kubectl apply -f n8n-deployment.yaml

# Option 3: Caddy Reverse Proxy with SSL
cd docker-caddy
cp .env.example .env
# Edit .env with your domain
docker-compose up -d

2. Import Workflow

1. Access n8n at http://localhost:5678 (or your configured domain)
2. Navigate to Workflows → Add Workflow → Import from File
3. Select one of the workflows from the workflows/ directory:
   • improved_ai_operating_model_workflow.json (Standard - $0.21/audit)
   • workflow_premium_google_sheets.json (Premium - $0.99/audit)

3. Configure Credentials

Set up the following credentials in n8n:

• ✅ Google Drive OAuth2
• ✅ Google Sheets OAuth2
• ✅ Airtable API Token (optional, for Airtable version)
• ✅ OpenAI API Key
• ✅ Supabase API Key
• ✅ Slack OAuth2

4. Run Your First Audit

1. Click Execute Workflow
2. Execution completes in ~70 seconds
3. Check outputs:
   • Airtable/Google Sheets: Client record created
   • Google Drive: Report uploaded
   • Slack: Notification sent

📖 Detailed Guide: See docs/QUICK_START.md for step-by-step instructions.

📦 Workflows

Available Workflows

Workflow	Use Case	Model	Cost/Audit	Output
Standard	Internal audits, testing	GPT-4o-mini	$0.006	1,500 words
Improved V4	Production audits	GPT-4o-mini	$0.21	3,000 words
Premium Google Sheets	Client deliverables	GPT-4o	$0.99	6,000-8,000 words
Financial Deep-Dive	CFO-grade analysis	GPT-4o	$1.20	8,000+ words
Lead Generation	Sales automation	Groq	$0.05	Email campaigns

Workflow Comparison

Standard vs Premium:

Feature	Standard	Premium
Sections	4	8
Tables	0-1	6+ detailed tables
Word Count	~1,500	6,000-8,000
Financial Analysis	Basic ROI	TCO, NPV, IRR, Cash Flow
Implementation Plan	High-level	4-phase roadmap with deliverables
Risk Assessment	Mentioned	Risk matrix with mitigation strategies

📚 Full Catalog: See workflows/README.md

🏗️ Deployment Options

1. Docker Compose with PostgreSQL (Recommended)

Best for: Production use, persistent data storage

cd docker-compose/withPostgres
docker-compose up -d

Features:

• PostgreSQL database for workflow persistence
• Volume mounting for data backup
• Health checks
• Auto-restart on failure

2. Docker Compose with Worker

Best for: High-volume workloads, parallel execution

cd docker-compose/withPostgresAndWorker
docker-compose up -d

Features:

• Separate worker container for job execution
• Horizontal scaling capability
• Load distribution

3. Kubernetes

Best for: Enterprise deployments, multi-tenant environments

cd kubernetes
kubectl apply -f n8n-deployment.yaml

Features:

• High availability
• Auto-scaling
• Resource management
• Service mesh integration

4. Caddy with SSL

Best for: Public-facing deployments with automatic SSL

cd docker-caddy
docker-compose up -d

Features:

• Automatic Let's Encrypt certificates
• Reverse proxy with HTTP/2
• Zero-config SSL/TLS

✅ Prerequisites

Required

• Docker 20.10+ and Docker Compose 2.0+
• n8n v1.0+ (included in Docker images)
• OpenAI API Key with billing enabled
• Google Cloud Project with APIs enabled:
  • Google Drive API
  • Google Sheets API
• 4GB RAM minimum (8GB recommended for Premium workflows)

Optional

• Airtable Account (for Airtable-based workflows)
• Supabase Project (for pattern learning/storage)
• Slack Workspace (for notifications)
• Kubernetes Cluster (for K8s deployment)

⚙️ Configuration

Environment Variables

Each deployment option uses a .env file for configuration:

# Copy example file
cp .env.example .env

# Edit with your values
nano .env

Key Variables:

# Database
POSTGRES_USER=your_user
POSTGRES_PASSWORD=your_secure_password
POSTGRES_DB=n8n

# n8n
ENCRYPTION_KEY=your_encryption_key  # Generate: openssl rand -base64 32

# Domain (for SSL deployments)
DOMAIN_NAME=n8n.yourdomain.com
SSL_EMAIL=admin@yourdomain.com

# Timezone
GENERIC_TIMEZONE=America/New_York

Google Sheets Setup

1. Create a Google Sheets document with these sheets:

   • RACI_Matrix - Process ownership data
   • Tool_Inventory - Technology stack
   • KPI_Snapshot - Performance metrics
   • Client_Models - Results storage

2. Update sheet IDs in the "Set Client Config" node

📖 Detailed Guide: See docs/GOOGLE_SHEETS_SETUP_GUIDE.md

📚 Documentation

Getting Started

• Quick Start Guide - 5-minute setup
• Google Sheets Setup - Data source configuration
• Workflow Improvements Guide - Optimization tips

Technical Deep-Dives

• Architecture Comparison - V3 vs V4 design
• Cost Analysis - Detailed cost breakdown
• Premium Workflow README - Enterprise features
• Premium Report Specification - Output format details

Enhancement Roadmaps

• Consultant Grade Enhancements - Future improvements
• Google Drive Trigger Spec - Automation plans
• Session Summary - Development history

Code Utilities

• Data Cleaner V3 - Data normalization code
• Environment Guard Fix - n8n compatibility fix
• Update Premium Prompts - Prompt management script

💰 Cost Analysis

Per-Audit Costs

Workflow Version	Input Tokens	Output Tokens	Cost	Value
Standard	8,500	2,000	$0.006	$5K-$10K
Improved V4	18,500	4,000	$0.21	$10K-$20K
Premium	35,000	12,000	$0.99	$15K-$50K
Financial Deep-Dive	45,000	15,000	$1.20	$25K-$75K

Monthly Costs (10 Audits)

• Standard: $0.06/month
• Improved V4: $2.10/month
• Premium: $9.90/month
• Mix (7 Standard + 3 Premium): $3.00/month

ROI: 99.998% cost reduction vs traditional consulting

📊 Detailed Breakdown: See docs/COST_ANALYSIS.md

🏛️ Architecture

Workflow Architecture (V4)

┌─────────────────────────────────────────────┐
│ Trigger Layer + Utilities                   │
│ Environment validation, shared functions    │
└─────────────────────────────────────────────┘
              ↓
┌─────────────────────────────────────────────┐
│ Data Collection (Parallel)                  │
│ Google Drive, Sheets, Airtable             │
└─────────────────────────────────────────────┘
              ↓
┌─────────────────────────────────────────────┐
│ Analysis Layer (Parallel + Validation)      │
│ Data cleaning, inefficiency analysis        │
└─────────────────────────────────────────────┘
              ↓
┌─────────────────────────────────────────────┐
│ Design Layer                                │
│ AI architecture, ROI simulation             │
└─────────────────────────────────────────────┘
              ↓
┌─────────────────────────────────────────────┐
│ Report Generation (Parallel) ⚡             │
│ 4 GPT-4 calls in parallel                  │
│ 69% faster than sequential                 │
└─────────────────────────────────────────────┘
              ↓
┌─────────────────────────────────────────────┐
│ Output & Learning Layer                     │
│ Storage, notifications, pattern learning    │
└─────────────────────────────────────────────┘

Key Improvements (V3 → V4)

• ⚡ 50% faster execution (131s → 65s)
• 💰 40% cost reduction ($0.35 → $0.21)
• 🧩 34% fewer nodes (65 → 43)
• 🛡️ Comprehensive error handling
• ✅ Data validation gates
• 📊 Quality scoring

📖 Full Details: See docs/ARCHITECTURE_COMPARISON.md

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

How to Contribute

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Areas for Contribution

• 📝 New workflow templates
• 🔧 Infrastructure improvements
• 📚 Documentation enhancements
• 🐛 Bug fixes
• ✨ Feature requests

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built with n8n - Fair-code workflow automation
• Powered by OpenAI GPT-4 - AI analysis and report generation
• Infrastructure inspired by n8n-io/n8n-hosting

📞 Support

• 📖 Documentation: Check the docs/ folder
• 🐛 Issues: GitHub Issues
• 💬 Discussions: GitHub Discussions

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