Local AI: what a model on your infrastructure changes

When the model runs on your side, three things become possible that a cloud service cannot offer. And two limits that must be stated plainly.

Three concrete gains

• Traceability. Every analysis is produced by a frozen version of the model and the prompt. Same input, same output: you can audit, compare and reproduce — impossible with a remote model that changes without notice.
• Predictable cost. No per-request billing. The cost is your hardware, known in advance, independent of the volume analysed.
• Multilingual work without leakage. Sources arrive in several languages. Translating and analysing locally lets you process foreign content without sending it to a third party — decisive in Switzerland, where people work in French, German, English and often Italian.

Two limits, stated plainly

• Local models are smaller than the large frontier models. You do not compensate with size, but with framing: a narrow task (qualify, summarise, propose an action) succeeds better than an open conversation.
• It takes hardware. Running models locally requires a suitable machine and its upkeep. That is the price of independence.

What it changes in practice

The model does not need to be the brightest; it needs to be framed, deterministic and on your side. That combination — a precise business profile, frozen versions, local execution — turns a news feed into a report you can decide on.