Local AI means tasks run on your hardware. Cloud AI means everything runs through an external provider. Most businesses are best served by a hybrid setup: tasks run locally, with language processing handled by a chosen provider. This article compares the options fairly.
Local AI means the AI environment, including projects, knowledge, configuration, and task execution, runs on a system at your location. You control the hardware, access, and data.
At Voltti, the Hermes environment runs locally. That does not mean everything is offline: it can use an external model for language processing. Read more on our page about local AI for businesses.
Cloud AI means everything runs through an external provider: ChatGPT, Copilot, or another SaaS solution. You send your question to the cloud and receive an answer. The provider determines where your data is processed.
| Feature | Local AI | Cloud AI |
|---|---|---|
Where data is processed | At your location | At the cloud provider |
Control over task execution | Full | Limited to provider settings |
Access to your systems | Yes, within your network | Only through cloud connections |
Hardware required | Yes | No |
Cost model | Installation + support | Usage-based / subscription |
Suited to | Businesses with recurring work | Ad hoc questions without integration |
That depends on how much you use it. With cloud AI you pay a small subscription and get started within the hour. Local AI requires a one-time investment in hardware and installation. For occasional questions, a subscription makes more sense. For recurring work (quotes, reports, customer service, data analysis) the subscription bill grows faster than the cost of running your own setup.
Do the math honestly: a hybrid setup combines a one-time investment with a smaller, predictable bill for language processing. Compared with separate per-user subscriptions, that stays manageable. Open-weight models also come without per-user license fees: the cost sits in hardware, installation, and support. What a setup costs for your business is always worked out in a custom quote.
Also count what never shows up on an invoice: data that stays within your own walls, no dependence on one provider's price changes, and an environment you can adapt as your processes change. How we handle the security and privacy of your business data is covered on its own page. That is risk and competitive advantage a subscription cannot offer.
The hardware itself does not have to be extreme: a capable computer is enough for the standard setup. What your machine needs to handle is covered in our article about what computer you need to run AI locally.
In practice, most businesses are best served by a hybrid setup. The AI environment (projects, knowledge, configuration, and task execution) runs at your location. For language processing, you use an external provider of your choosing. What leaves your environment is decided per task, by you.
Which parts of your setup stay local and which go to a provider is covered in what stays local in a hybrid AI setup.
Choose cloud AI if you only ask occasional questions and do not need an integrated work environment. Choose local or hybrid AI if you want the agent to work with your projects, use your tools, and operate within your boundaries.
Read more about the difference between an agent and a chatbot in our article on AI agents vs. chatbots.
No. Claude is a closed model from Anthropic and is only available through the cloud. Running models locally requires open-weight models, such as Qwen or Llama on Hugging Face. In a hybrid setup you combine both: task execution runs on your hardware, and for language processing you pick a suitable model per task: a local open-weight model or a cloud model like Claude.
Not necessarily. At Voltti, the environment runs locally, but language processing can use an external provider. That is called hybrid AI. A fully offline setup is possible but requires powerful hardware.
Not necessarily, but you have less control. Your data leaves your environment through the provider. With local AI, tasks run on your hardware. You decide what to send to a model provider.
Yes. This setup lets you switch model providers. If your use case and hardware justify it, we can add a local model.
Not necessarily a server: a capable computer is enough for the standard setup. Running a local language model calls for a GPU in the setup described here.
