Private AI infrastructure shaped around your organisation.
Tecnosfera designs private AI environments in which organisational data, knowledge, inference and operational logs can remain inside infrastructure controlled by the customer.
- Open-source model evaluation
- NVIDIA GPU systems for the workload
- Local integration with authorised data
Start with the use case and information boundary
A useful project begins with the decisions it must support, the data it may access and the people authorised to use it. We map those boundaries before selecting a model or buying compute.
This keeps an experimental assistant from becoming an uncontrolled route into documents, databases or operational systems.
- Use-case and data classification
- Access and approval model
- Evaluation and failure boundaries
Build the model and knowledge layer
The solution may combine an open-source foundation model with retrieval-augmented generation, controlled tools, structured prompts or targeted fine-tuning.
Evaluation uses representative, authorised material. Source references, refusal behaviour and observable quality matter more than a single generic benchmark.
- Model and embedding evaluation
- Governed knowledge sources
- Task-specific tests
Operate on private GPU infrastructure
We design and configure NVIDIA GPU servers around the agreed capacity, latency, model size and resilience requirements.
The topology can keep inference and logs local, with controlled administration, monitoring, backup decisions and an explicit model-update process.
- GPU sizing and architecture
- Private inference runtime
- Controlled lifecycle operations
The essentials, without ambiguity.
Does private AI require a public AI service?
No. The model, knowledge base, inference and logs can run inside customer-controlled infrastructure when required.
Is fine-tuning always necessary?
No. Prompting, retrieval and controlled tools are evaluated first. Fine-tuning is used only when evidence justifies it.
Define the use case before choosing the stack.
Tell us what the system should know, who should use it and which information must stay inside your boundary.