Start with the work your team needs done
The deployment choice should follow a bounded task: finding answers in internal documents, preparing a draft or handing off a structured brief. Write down the users, authorised inputs and what a reviewer considers a useful answer. Running a model locally is a configuration choice; usefulness needs evidence from the actual task.
What local inference changes
A locally running language model performs inference on the chosen hardware. That can make hardware, model weights and network access easier to inspect. It also creates requirements for memory, maintenance, updates and operating ownership. A document store, search service, telemetry component or connected tool can still contact an external provider. Map the complete configuration before making a data-location claim.
What cloud access changes
A cloud model can avoid some local hardware setup and offer different model capabilities. Evaluate the selected provider’s settings, processing locations, retention and permitted data use for the project. Check rate limits, latency and operating costs on representative examples. A Canadian domain name does not establish where every connected service processes information.
When a hybrid pilot makes sense
Different tasks may use different approved environments. For example, a pilot can compare a local document workflow and a cloud configuration on redacted samples, using the same review criteria. State which inputs may go to which service and which tool actions require approval. More components also mean more dependencies to document and test.
Compare the same questions in each setup
Use routine questions, missing information, obsolete sources and ambiguous language. Review source citations, unsupported statements, refusal behaviour, reviewer effort, latency and cost. French and English source sets need checks in the languages your team uses. A small browser demonstration cannot establish business performance for either option.
Include operating ownership in the estimate
Ask who maintains the hardware, updates the model, patches connected services and responds when a tool fails. Separate a feasibility pilot from deployment and ongoing support. LabSI starts with an authorised sample and a scoped evaluation so the next decision follows observed results, not a universal claim that one environment suits every Canadian business.