Local vs Cloud: The Real Cost of AI
See what you are actually paying — and what you could save
Three Ways to Deploy AI
Each model has trade-offs. The right choice depends on your volume, data sensitivity, and budget.
Cloud AI
Pay per API call or rent cloud VMs from Azure, AWS, GCP. Simple to start, but costs scale with usage and never stop. Your data leaves your network every time.
Edge / Hybrid
Models run on infrastructure we host at our facility or at a local data center. You get cloud-like convenience with local-like costs. Your data stays in the region. Fixed monthly or one-time investment.
Local / On-Premise
Models run on your hardware — a server in your office or server room. One-time infrastructure cost, zero ongoing AI fees. Your data never leaves your building. We set it up, train your team, you own it. Hardware that replaces $5,000/month cloud VMs can be built for $20,000 or less, plus install and setup.
Interactive Cost Comparison Calculator
Enter your current or estimated cloud AI spend and see how deployment models compare over time
Your Assumptions
| Period | Cloud | Edge / Hybrid | Local |
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Cumulative Cost Over Time
What Edge Means
Edge computing means running AI models closer to where the work happens — not in a distant data center. For MIA clients, this can mean:
- A server in your office running local language models (on-premise)
- Infrastructure hosted at our facility in Miramichi, managed by us (hosted edge)
- A hybrid setup where sensitive processing stays local and only non-sensitive work touches the cloud
We also offer hosted local cloud — we run and maintain the infrastructure at our facility, you access it like a cloud service, but your data stays in Atlantic Canada and your costs are predictable.
Real Numbers: How We Built This Website
Ready to see what local-first looks like for your business?
We will map your current spend, model the alternatives, and show you exactly where the savings are.
Let's Break It Down