🚀 Private AI Compute Infrastructure – Live Backend Deployment
We designed and deployed a secure, containerized, multi-GPU AI compute environment
that is now fully operational on the backend.
Core architecture includes
- Secure Nginx reverse-proxy gateway (SSL / TLS termination)
- Authentication-controlled access layer
- Docker-based service deployment
- Portainer container management interface
- Dedicated AI compute servers with dual RTX 6000 GPUs
- ComfyUI image pipelines
- A1111 Stable Diffusion instances
- Open-WebUI with Ollama backend for LLM inference
- 10Gb network fabric (fiber + DAC copper links)
- Private LAN segmentation and firewall isolation
- Modular, scalable topology designed for orchestration frameworks
All backend AI services are live and containerized, allowing rapid deployment, isolation, scaling,
and controlled GPU allocation.
Public-facing portal layer (final development)
- Service routing
- Usage monitoring
- Private virtual instances
- Enterprise-grade AI workload isolation
Designed to evolve into
✔Private AI infrastructure for companies
✔GPU-backed SaaS environments
✔Dedicated virtual AI instances
✔Infrastructure-as-a-Service for funded startups
✔Controlled, monetized AI compute access
This is no longer a concept build.
It’s a functioning, containerized AI compute platform running on dedicated GPU hardware.
— Scott Joseph Arnold
