Size & source
Map your models, users, budget, and site requirements. Compare supplier configurations and confirm the exact bill of materials.
AI systems / RTX & professional GPUs
Local AI workstations.
Start local inference with a workstation or compact server sized to your team’s actual models and usage.
Configuration, availability, and commercial terms confirmed by quotation.
START WITH THE WORKLOAD
The right fit
starts with the details.
Small teams, development, internal knowledge assistants, and pilot inference workloads.
Deployment approach
Workstation or small-server configurations using suitable NVIDIA RTX or professional GPUs.
What we assess with you
- Model size and available GPU memory
- Noise, power, cooling, and physical space
- Concurrent users and upgrade options
We recommend an exact GPU and system configuration after assessing the model, workload, budget, and operating environment.
FROM REQUIREMENT TO RUNNING SYSTEM
A clear scope, from the start.
- 01
Choose a practical model and size the GPU, RAM, and storage.
- 02
Source and install the agreed system at your site.
- 03
Configure Ollama or another suitable serving engine, access controls, and monitoring.
THE SERVICES AROUND YOUR HARDWARE
More than the compute.
Supply & install
Coordinate hardware supply, delivery, rack or workstation installation, networking, and power and cooling prerequisites.
Configure local inference
Set up supported drivers, CUDA, containers, and serving engines such as vLLM, Ollama, or NVIDIA NIM where suitable.
Validate & support
Check the agreed workload, access controls, monitoring, and recovery procedures. Hand over documentation and scope ongoing support.
From ambition to action
Let’s size the possibilities.
Share your models, expected usage, budget, location, and target deployment window. We’ll confirm the right configuration and sourcing options.