Closed models win demos. Open models win sovereignty debates. Real Alberta companies win when someone maps the workflow and picks the boring correct option — sometimes both.
open source vs ChatGPTopen source vs Claudelocal AI vs cloud Canadaprivate AI vs SaaS
Why this deskOpen-source AI is hot in ads and forums. Businesses need plain answers — and paid help when DIY fails.
Decision matrix
Sensitive data + capable hardware → local/open path. Office-heavy Microsoft shop → Copilot first. Document-heavy professional work → Claude often. Broad research → ChatGPT-class tools.
Cost myth
Open source can be cheaper over years and more expensive in month one (hardware + setup). Cloud seats are predictable and can explode with heavy agent use.
Compliance is not a logo
Neither open nor closed is “PIPEDA certified” by default. Contracts, retention, training, and access logs matter more than brand.
How we charge
Discovery free. Paid pilots for local stacks. Training for either path. See open source AI help.
Opcelerate recommendationWrite your data classes first. Then choose tools. Then train. Do not start with a fan-favorite model name.