What you get
A workload suitability matrix, a benchmark of three to five open or local models against your real tasks, a cost comparison between API and local deployment, a pilot on the workloads that pay off, and an honest recommendation on what should stay local and what should not.
- Workload suitability matrix for local vs managed vs cloud.
- Benchmark of three to five models against your real tasks.
- Cost comparison: API vs rented GPU vs owned hardware vs hybrid.
- Pilot deployment with Ollama, vLLM, TGI, or managed GPU.
- Honest go / no-go recommendation per workload.
Why this matters
Local AI is not automatically cheaper. It pays off when utilisation is high, when data privacy is a hard constraint, when latency matters, or when you want a provider-independent option. Attnora's bias is to use the cheapest option that meets your requirements, not the most exotic one.
How a pilot starts
We pick three candidate workloads, run the benchmark, and ship a recommendation with a real cost comparison in two to four weeks.
Frequently asked questions
Do you require specific hardware?
No. We work with Ollama on developer machines, vLLM and TGI on rented GPU, and managed inference providers for production. Hardware choice follows the workload.
What about model quality?
Local models have closed the gap with frontier models on commodity tasks such as classification, extraction, and summarisation. We benchmark before recommending.
Is on-prem always better for privacy?
Not always. A managed private deployment with Swiss data residency and no-log policies can match on-prem privacy with better economics. Attnora evaluates all three.
Can we run local AI alongside the cloud gateway?
Yes. The Attnora gateway routes commodity work to local models and consequential work to managed models, with shared observability.
Related services
Next step
Benchmark local AI for one workload.
Tell us which task you want to evaluate. We will respond with a benchmark plan within one business day.
Request a private AI feasibility study