Engineering Research Platform
Engineering AI for Everyday Life
OMEGA Project is an independent AI engineering research platform created by Neil Smith, a Senior Security Architecture & Governance professional with over 20 years' experience designing secure cloud, identity and infrastructure solutions across regulated industries.
The project investigates how artificial intelligence can be designed, secured and embedded into everyday life through practical, modular and responsible engineering. Research is ongoing. Findings are documented. Understanding is the objective.
| Platform | OMEGA Core v0.5 |
| Status | Active Research |
| Models | — |
| Phase | GAIPS Lab — Phase 5 |
| Focus | AI Security |
| Maintainer | Neil Smith |
| Last sync | awaiting data |
Research Question
How can artificial intelligence be securely engineered and embedded into everyday life through practical, modular and responsible engineering?
Every component of OMEGA Project — the platform, the research, the documentation — exists to answer this question through evidence rather than assumption. The sections below each represent one dimension of that investigation.
Platform Architecture
OMEGA Core's architecture changes fast enough that a diagram embedded here would go stale within weeks — the full, current diagram lives on its own page instead. At a glance, it's five layers:
AI Runtime
Local model inference via Ollama. No data leaves the network.
Frontends
Open WebUI, SillyTavern and LibreChat, behind a single Authentik login.
OMEGA Control
Status, Model Builder and frontend start/stop — isolated from the Docker socket by design.
Platform Infrastructure
Gitea, Authentik, Technitium DNS and npmplus, self-hosted on Proxmox.
Public Site
This site — Astro, S3 and CloudFront, deployed on every push to main.
Research Programmes
Platform Engineering
In ProgressInvestigates how AI infrastructure can be built securely and maintainably. Can open-weight models be operated responsibly using standard engineering practices?
Security & Trust
In ProgressInvestigates the attack surface of AI systems. How can LLMs be threatened, how can those threats be identified, and what controls meaningfully reduce risk?
Knowledge & Retrieval
In ProgressInvestigates how AI systems can be grounded in accurate, controlled knowledge. What are the security implications of retrieval-augmented generation pipelines?
Home Integration
In ProgressInvestigates how AI capability can be embedded into everyday domestic environments through controlled APIs and responsible, observable integration patterns.
Voice Interaction
PlannedWill investigate how natural speech interfaces can be built that are practical, reliable and secure at the household level without requiring cloud dependency.
Agents & Automation
PlannedWill investigate where autonomous AI agents genuinely add value and what security controls are required to operate them safely in a real-world environment.
Roadmap
| Phase | Name | Scope | Status |
|---|---|---|---|
| 0–4 | Foundation | Infrastructure, Docker, APIs, Observability, Git governance | Complete |
| 5 | GAIPS Lab | AI security research across 8 GIAC GAIPS exam domains | In Progress |
| 6 | Intelligence Layer | RAG pipelines, vector knowledge base, document ingestion | Planned |
| 7 | Integration | Voice interfaces, Home Assistant integration, agentic workflows | Planned |