Private AI Infrastructure
Run AI on infrastructure you control.
We design, deploy and look after private AI environments — from a single GPU workstation to a server room — so sensitive workloads run where you decide.
Not every workload belongs on a public AI platform.
Sensitive records, high-volume internal work and systems that reach deep into your network all raise the same question: where does the data go, and who controls it?
Sensitive data
Client records, contracts, health or financial data that shouldn't leave your environment.
Heavy internal use
High-volume, everyday workloads where owning the capacity makes more sense than paying per request.
Deep integration
Systems that need to reach internal databases and applications without exposing them.
What you get
The whole environment, not just the servers.
Hardware is only useful once models, knowledge, access and operations are in place. We deliver and look after all of it.
- GPU workstation and server design
- Private model hosting and inference
- Linux AI environments and model runtimes
- Storage and networking
- Local and cloud hybrid architecture
- Private knowledge and retrieval systems
- Identity and access integration
- Monitoring, updates and lifecycle management
Deployment options
- SarjaBox MiniFrom $10,990 AUDCompact RTX PRO hardware for your own premises
- GPU workstationA team, a contained workload or model evaluation
- Server environmentModels, knowledge systems and internal apps for wider use
- HybridPrivate capacity for sensitive work, provider models for the rest
SarjaBox Mini · In development
Professional AI hardware for your own premises.
A compact AI system built on NVIDIA RTX PRO graphics, configured around the models you actually run — so your work stays on hardware you control.
- NVIDIA RTX PRO graphics with ECC memory
- Runs on your premises, on your network
- Purpose-built chassis with integrated power
- Configured, delivered and supported by Sarja
Starts from
$10,990 AUD
Preliminary launch pricing in Australian dollars. Configurations and prices may change before release.
What changes when AI runs in your environment.
Private infrastructure gives you much more control. It also moves responsibility for security, capacity and operations to you — which is why we design and run it with those built in.
Model hosting
Public AI service: Runs on the provider's infrastructure, on their terms and update schedule.
Private environment: Selected, hosted and updated on infrastructure you control.
Data flows
Public AI service: Prompts, documents and context are sent to an external service.
Private environment: Sensitive workloads can be processed inside your environment.
Access
Public AI service: Managed through the service's own accounts and settings.
Private environment: Follows your identity, roles and network rules.
Storage
Public AI service: Retention follows the provider's policies.
Private environment: Logs, indexes and outputs are stored where you decide.
Integration
Public AI service: Limited to what the service exposes and can reach.
Private environment: Models connect to internal systems inside your network.
How we deliver it.
- Step 1
Assess
Workloads, data, users and constraints.
- Step 2
Architect
Hardware, models, network and access design.
- Step 3
Build and deploy
Install, configure, harden and test.
- Step 4
Integrate
Connect identity, knowledge sources and applications.
- Step 5
Operate
Monitor, update and improve over time.
Usually delivered alongside
- Custom AI Systems & IntegrationAI applications built for your organisation and connected to the systems you already run.Learn more
- AI Governance & SecurityPut enforceable controls around every AI system you run.Learn more
- AI Automation & IntegrationConnect AI to the workflows and software your team already uses.Learn more
Considering private AI infrastructure?
Tell us about the workloads, data and people involved. We'll help you work out whether private, hybrid or provider-based AI fits — and what it would take.