When businesses decide to use AI, one of the first decisions is where the AI runs: in the cloud or on your own hardware. Both have trade-offs, and the right choice depends on your situation.
Cloud AI: fast to start, hard to predict
Cloud-based AI (like OpenAI, Google Gemini, or AWS Bedrock) is quick to set up and requires no hardware. The downside is that your data leaves your network, costs scale unpredictably, and you are dependent on a third party for uptime and pricing.
Local LLMs: private, predictable, yours
A local LLM runs on hardware you own. Your data never leaves your building. Costs are fixed after the initial setup. The trade-off is higher upfront investment and the need for someone to set it up and maintain it.
When local makes sense
If you handle sensitive data (healthcare, legal, financial), if your AI costs are growing, or if you want full control over your systems, local is usually the better long-term choice. We help businesses make this transition every month.