Local model deployments do not necessarily require an external model API. Network and operating design still need to be agreed.
Local AI infrastructure
Professional Ollama installation for a documented local model service
Pörtner Consulting checks whether your existing systems and intended workload fit together. The runtime, models, access path and handover are then configured as a traceable starting point for operation.
Technical prerequisites
What is clarified before starting
- A suitable Linux, macOS or Windows system, or a dedicated target environment
- CPU/GPU and memory resources agreed for the intended models
- Clarified ownership for users, networking and updates
Typical use cases
Where this architecture is used
- Internal assistance for recurring text work
- A local model API for existing business applications
- A pilot deployment for selected teams
At a glance
Technical context without false precision
| Runtime | Ollama with controlled model storage |
|---|---|
| Access | local, segmented or through defined interfaces |
| Handover | documentation of installation, models and operation |
Scope and limitations
What this solution intentionally does not promise
Model size, quantisation, context length and concurrency determine practical fit. Installation does not replace access control, monitoring, backup or regular updates.
FAQ
Frequently asked questions
No. A suitable GPU may nevertheless be appropriate for interactive or multi-user use; the decision depends on the model and workload.
Sources and technical context
These sources support technical context. They are not a project commitment and do not replace individual assessment.