Internal — Confidential March 8, 2026

AI Transformation Command Center — Deployment Guide

Version 7.0 — Enterprise Edition. A comprehensive guide for DevOps and Deployment teams.

1. Solution Overview

The AI Transformation Command Center is a full-stack platform that helps enterprise organizations discover, assess, and manage their AI transformation initiatives. It consists of three containerized services orchestrated via Docker Compose.

1.1 Architecture Summary

Service	Technology	Description
Frontend	Next.js 14 + React 18 + Tailwind	Dashboard, 8 module UIs with Chart.js visualizations
Backend	Python 3.11 + FastAPI + SQLAlchemy	REST API with 14 endpoints, OpenAI integration, PPTX export
Database	PostgreSQL 16 (Alpine)	9 tables with UUID PKs, seeded demo data, health checks

1.2 Default Port Assignments

Service	Port	URL
Frontend	3000	http://localhost:3000
Backend API	8000	http://localhost:8000
API Docs	8000	http://localhost:8000/docs
PostgreSQL	5432	localhost:5432

2. Prerequisites

Ensure the following tools are installed on the target deployment machine before proceeding.

2.1 Required Software

Docker Engine: v24.0+ (Verify: docker --version)
Docker Compose: v2.20+ (Verify: docker compose version)
Git: v2.30+ (Verify: git --version)

2.2 System Requirements

CPU: 2+ cores (4 recommended)
RAM: 4 GB minimum (8 GB recommended)
Disk: 5 GB free space for images and database volume
Network: Outbound internet access required for OpenAI API calls (if AI features enabled)

2.3 Credentials Required

OpenAI API Key (Optional): Enables AI-powered Discovery Engine, Architecture Generator, and Roadmap suggestions. Without it, the platform falls back to rule-based logic.
PostgreSQL Credentials: Preconfigured in docker-compose.yml (admin/changeme). Change these for production.

3. Project Structure

enterprise-ai-platform/
├── docker-compose.yml        # Orchestration (3 services)
├── .env.example              # Environment variable template
├── database/
│   └── init.sql              # Schema + seed data (auto-runs on first boot)
├── backend/
│   ├── Dockerfile
│   ├── requirements.txt      # Python dependencies
│   └── app/
│       ├── main.py           # FastAPI entrypoint
│       ├── config.py         # Env-based settings
│       ├── database.py       # SQLAlchemy setup
│       ├── models/           # ORM models (9 tables)
│       ├── schemas/          # Pydantic request/response models
│       ├── services/         # AI service (OpenAI + fallbacks)
│       └── api/              # Route handlers (9 routers)
└── frontend/
    ├── Dockerfile
    ├── package.json          # Node dependencies
    └── src/
        ├── pages/            # 9 page routes + _app/_document
        ├── components/       # 15 React components
        └── utils/            # API client + constants

4. Deployment Steps (Dev/Staging)

Step 1: Clone the Repository

git clone <repository-url> enterprise-ai-platform
cd enterprise-ai-platform

Step 2: Configure Environment Variables

Copy the example environment file:

cp .env.example .env

Open .env and configure:

OPENAI_API_KEY: (Optional) sk-proj-...
SECRET_KEY: Generate with openssl rand -hex 32
CORS_ORIGINS: http://localhost:3000

Step 3: Build and Start

docker compose up --build -d

This builds images, starts PostgreSQL, runs init.sql, and brings up services. First build takes ~2-3 minutes.

Step 4: Verify Deployment

# Check container status
docker compose ps

# Test health endpoint
curl http://localhost:8000/api/health
# Expected: {"status":"ok","version":"7.0"}

# Test Database
docker exec -it enterprise-ai-platform-db-1 psql -U admin -d ai_platform -c "SELECT count(*) FROM ai_projects;"
# Expected: 8

6. Production Checklist

6.1 Security Hardening

Change DB Credentials: Replace admin/changeme with strong credentials via secrets.
Secure SECRET_KEY: Never use defaults.
Restrict CORS: Set to production domain (e.g., https://ai-platform.yourcompany.com).
Close Ports: Remove port 5432 mapping for the DB service.
Disable Debug: Remove --reload from backend. Run npm run build && npm start for frontend.

6.2 Production Overrides

Create docker-compose.prod.yml to enforce security and performance settings (workers, no volumes, secrets).

docker compose -f docker-compose.yml -f docker-compose.prod.yml up --build -d

7. Monitoring & Logging

Viewing Logs

docker compose logs -f          # All services
docker compose logs -f backend  # Backend only

Health Monitoring

Poll GET /api/health. Alert on non-200 responses or timeouts > 5s.

8. Troubleshooting

Symptom	Likely Cause	Resolution
Backend fails to start	Database not ready	`docker compose restart backend`
Frontend "Failed to fetch"	URL mismatch	Verify `NEXT_PUBLIC_API_URL`. Rebuild frontend.
Generic Discovery results	No API Key	Set `OPENAI_API_KEY`. Platform uses fallback logic.

11. Support

Platform Lead: Raj Rajagobalan
DevOps Team: devops@yourcompany.com