An own GPU server makes compute tangible. Turning it into useful AI operations requires an offer that fits your team’s tasks. The number of GPUs alone does not answer that question.
The task determines the model
Analysing documents, preparing product copy and generating images have different requirements. First establish the required quality, permitted data and concurrent users. Then choose the model, licence, memory and compute accordingly.
A large model name does not guarantee performance for your workflow. Assess representative cases and acceptable response times. Define who reviews outputs professionally and which approval is needed before further use.
Where does the data run?
The server’s location is only part of the operating model. Applications, storage, external services and telemetry may have separate data paths. Failure behaviour matters too: is a task stopped, retried or routed to another service?
These paths must be explicitly agreed and tested. Owning a model server does not automatically mean the entire HEINI platform runs locally or that operations are fully isolated.
Support belongs in the proposal
Plan for power, cooling, networking, access, updates and backups. Responsibility, support and recovery after failure are just as important. A suitable proposal identifies these services and their boundaries.
The HEINI offer in DACH
HEINI now offers consultations for own GPU servers with connected language and GenAI models. HEINI distributes this server offer exclusively in Germany, Austria and Switzerland. Hardware, setup, delivery date and service scope are agreed individually.