O.R.E - AI Workforce SaaS Platform

Oniel and Ryan Enterprise: A cloud-based AI workforce SaaS platform that allows businesses, marketers, agencies, and e-commerce brands to hire and interact with a team of specialized AI employees.

🎯 Vision

Instead of using separate AI tools for content creation, strategy, video editing, marketing, and distribution, users interact with a unified system of AI agents that can work independently or collaboratively.

🏗️ Architecture

┌─────────────────────────────────────────────────────┐
│                   FastAPI Backend                   │
├─────────────────────────────────────────────────────┤
│  • Task Router (Core Decision Engine)               │
│  • Workflow Engine (Multi-step execution)           │
│  • Agent Services (Independent AI Workers)          │
│  • Job Queue System (Redis + RQ)                    │
│  • Cloud Storage Integration                        │
│  • Database Layer (SQLite → PostgreSQL)             │
└─────────────────────────────────────────────────────┘

🧠 AI Employee System (Core Agents)

1. Strategy Agent - Research & Marketing Intelligence
2. Script Agent - Content & Copywriting
3. Video Agent (Zoey) - Video production & editing
4. Voice Agent - Audio & narration generation
5. Media Agent - Asset sourcing & content support
6. Distribution Agent - Social media posting & optimization

🛠️ Tech Stack

• Backend: Python + FastAPI
• Database: SQLite (MVP) → PostgreSQL (Production)
• Job Queue: Redis + RQ
• Video Processing: FFmpeg
• Storage: Cloud storage integration

📁 Project Structure

O.R.E/
├── backend/
│   ├── app/
│   │   ├── __init__.py
│   │   ├── main.py
│   │   ├── config.py
│   │   ├── models/
│   │   ├── schemas/
│   │   ├── routes/
│   │   ├── agents/
│   │   ├── services/
│   │   └── utils/
│   ├── tests/
│   ├── requirements.txt
│   └── .env.example
├── docs/
│   ├── architecture.md
│   ├── api_design.md
│   └── deployment.md
└── .gitignore

🚀 Getting Started

Installation

# Clone repository
git clone https://github.com/anyaghamoniel/O.R.E.git
cd O.R.E

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
cd backend
pip install -r requirements.txt

# Setup environment
cp .env.example .env

Running the Backend

# Start FastAPI server
uvicorn app.main:app --reload

# In another terminal, start Redis
redis-server

# In another terminal, start RQ worker
rq worker

📚 Documentation

• Architecture
• API Design
• Deployment Guide

🔄 Development Roadmap

• Phase 1: Core Infrastructure (Task Router, Job Queue, Database)
• Phase 2: Video Agent (Zoey) - MVP
• Phase 3: Strategy Agent
• Phase 4: Script Agent
• Phase 5: Voice & Media Agents
• Phase 6: Distribution Agent
• Phase 7: Full Frontend & Dashboard
• Phase 8: Production Scaling (PostgreSQL, Celery)

📝 License

Private - O.R.E Platform

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