Local AI Setup for Canadian Businesses
A self-hosted, on-premise local LLM running on your own hardware. Your team gets the productivity of generative AI; your sensitive documents never leave your network. Practical setup, model selection, and rollout for Canadian SMBs that can't risk public cloud AI.
What's included in a local AI setup
A pragmatic, end-to-end engagement — not a one-time install that leaves your team stuck.
Hardware sizing
Right-sized recommendations based on your team size, document volume, and budget. From a single laptop for a 3-person clinic to a dedicated server for a 50-person agency.
Model selection & benchmarking
Gemma 4, Llama 3, Mistral — benchmarked on your actual documents, not generic prompts. We pick the smallest model that meets your quality bar, because smaller is faster and cheaper to run.
Install & integrate
A clean install with a UI your team can actually use — not a command-line tool. Where possible we integrate with your existing tools (file shares, document folders, internal apps).
30-day tuning window
After install, a month of light-touch tuning as your team starts using it. Prompts that need refining, edge cases to handle, integration tweaks — caught and fixed before they become friction.
When local AI is the right answer
Not every team needs local AI — but some teams really do.
Strong fit
- —Healthcare clinics handling patient records
- —Law and accounting firms with client privilege
- —Property management with tenant data
- —Non-profits handling beneficiary information
- —Any team where contracts forbid cloud AI
Probably overkill
- —Teams that only use AI for public marketing copy
- —Solo founders just exploring AI
- —Workloads that need real-time GPT-4-class reasoning
In these cases, a vetted cloud AI workflow with proper data discipline often beats running your own infrastructure.
Try DocBee, my local AI document tool
DocBee is a local AI document generator and formatter — built on Gemma 4, runs on your own hardware, never sends data to the cloud. The product version of this service for teams that want to start fast.
Learn about DocBeeFrequently asked questions
What is a local LLM, and how does it protect my business data?expand_more
A local LLM is a large language model that runs entirely on your own hardware — laptop, server, or office machine — rather than calling a cloud service. Because the model is on-premise, every document you give it stays on your network. Nothing is uploaded, logged, or used to train someone else's model.
Is a local LLM as capable as ChatGPT?expand_more
For most office work — drafting, formatting, summarizing, rewriting — modern open-weights models like Gemma 4 and Llama 3 are very close. They're not quite at GPT-4-class reasoning, but for the document-heavy workflows where privacy matters most, the gap is small enough to be a worthwhile trade.
Do I need special hardware?expand_more
It depends on model size. Small models (4B–8B parameters) run well on a modern laptop with 16GB+ RAM. Larger models benefit from a dedicated GPU. For most Canadian SMBs, the right starting point is a single dedicated machine — often less than the cost of a 1-year ChatGPT Enterprise license.
How is this different from using ChatGPT with a privacy policy?expand_more
With any cloud AI, your data leaves your network. Even if the vendor promises not to log or train on it, you're trusting that promise — and you're still exposed to subpoenas, vendor breaches, and policy changes. With a local LLM, the data never leaves. The privacy guarantee is technical, not contractual.
What's included in a local AI setup engagement?expand_more
Hardware sizing recommendations, model selection and benchmarking against your real documents, installation, a UI your team can actually use, integration with your existing tools where possible, and a 30-day support window for tuning. Optional follow-on for team training.
Run AI on your own hardware.
A 30-minute call to scope the right setup for your team and the documents you handle.
Book a Call