How Can I Tell If My AI Assistant Is Actually Running Locally?

October 3, 2026 · By Michel Valenzuela, Founder of Daryl

Start by checking where the selected model runs. Then check which features send information outside your computer.

A desktop application can connect to a cloud model. A local model can be paired with online search. An application can process a conversation locally while saving its history in a synced folder.

“Installed on my computer” does not answer all of those questions.

If you want a private AI setup, you need to understand the path your information takes. You should be able to do that without becoming a software engineer.

What does “running locally” mean?

For a personal AI assistant, local model processing means your computer generates the response.

Your prompt goes to a model running on your device, rather than to a hosted model service.

But an assistant can have several parts:

You may find that an application handles some parts locally and others remotely.

That can be a deliberate product choice. What matters is whether the behavior matches what you want.

Does a desktop app automatically mean local AI?

No.

A desktop application is an interface. It can display responses generated on your computer or responses received from a remote service.

The same is true of a browser interface. A page in your browser can communicate with software running on your own computer.

The appearance of the application does not establish where processing happens.

Look for an explicit explanation of the selected model’s location. Labels such as “local,” “on-device,” or a named cloud provider are useful starting points, but they should be supported by documentation.

What should I look for in the settings?

Start with the model or provider settings.

Check whether the application is using:

• A downloaded model on your computer.
• A remote model accessed through an account or API key.
• A model running on another machine you control.

Then check voice, search, integrations, and storage separately.

A setting called “local model” may describe text generation without explaining speech recognition or online tools.

You want an answer for the feature you are using.

For example:

“Typed conversations are processed on this Mac.”

“Voice transcription uses an external service.”

“Web search sends the search query to a provider.”

Those statements give you something concrete to assess.

Can I test it by disconnecting the internet?

Yes. An offline test is a useful practical check once the application and model are fully installed.

Quit the application, disconnect from the internet, reopen it, and start a new conversation with an original question.

If it generates a fresh response, that is evidence that the tested conversation can work without an internet connection.

Test voice separately if you intend to use it. Text working offline does not establish that speech recognition or spoken replies also work offline.

However, this test has limits.

It does not prove that the application never sends information when online. It also does not tell you whether saved information is uploaded later.

And an application failing offline does not automatically prove that the model is remote. Another dependency, such as an account check, could be blocking access.

Use the test alongside the product’s documentation.

Does local processing mean my conversations stay only on my computer?

Not necessarily.

Processing and storage are separate.

A conversation might be generated locally and then saved somewhere that syncs across devices. A backup system might copy that file elsewhere. An export could place it in a shared folder.

If keeping a conversation on one device matters, check where the application saves it and how that location is handled.

The same applies to recordings and transcripts. An audio file, its transcription, and the resulting conversation may have different storage behavior.

“Local” becomes meaningful when the explanation covers the whole feature.

What about diagnostics and crash reports?

Diagnostics are another separate question.

An application may send information about failures, performance, or usage while processing conversations locally.

Check what those reports contain and whether you can control them. In particular, look for an explanation of whether prompts, transcripts, or conversation content can appear in reports.

A statement about local model execution should not leave you guessing about diagnostic data.

What should a local AI product explain clearly?

At minimum, it should explain:

• Where each core feature processes information.
• What information it saves.
• Which optional features contact outside services.
• What happens when you enable those features.
• How you can review or delete saved information.

These explanations should be available before you share something important.

They should also be understandable. A long policy may contain necessary detail, but the application still needs to help people make ordinary decisions about its settings.

How are we approaching this with Daryl?

We are building Daryl as a personal AI for Mac, with local core conversations, voice and typing, and decision assistance.

Part of making that experience approachable is making its behavior understandable.

Someone talking through a difficult decision should be able to know where that conversation is processed and what the application retains.

Daryl is still in development. Its launch documentation needs to describe the capabilities and controls available in the released product. Features in development, including memory and continuity, also need clear explanations of how they handle information.

The standard is practical: people should be able to make an informed choice without interpreting technical architecture.

Frequently asked questions

Does downloading a model prove my app is using it?

No. The application might have a different model selected. Check the active model or provider for the conversation.

Does working offline prove an app never uploads data?

No. It demonstrates that the tested feature can work offline. Online behavior and later syncing require separate checks.

Does using an API key mean the model is remote?

The key alone does not tell you where the model runs. Check which service or server the application connects to.

Can voice input be remote while text responses are local?

Yes. Speech recognition and language model processing can happen in different places. Check both.

Ask for a specific answer

“Is this app private?” is a reasonable starting question.

A more useful follow-up is:

“Where does this feature process my information, what does it save, and what leaves my computer?”

That gives you a basis for choosing an assistant you can use comfortably.

It is also the clarity we want to bring to Daryl.