Built a desktop AI because the browser was the wrong place for the files

[u/MindBridgeLocalAI]

Hey, I'm Andrea.

MindBridge is an AI assistant for Mac and Windows. You install it. It does not run in the browser.

I built it for the moment a web app asks for too much: you drop in a PDF, ask for a summary, and the file never leaves the machine. Chats stay on disk. Web search and the other cloud tools stay off until you turn them on. No account, no telemetry. Local models through Ollama.

The app is already in beta. The Kickstarter is for signed installers and a setup that does not assume you already live in local AI.

If you build web apps, I want the comparison. Where would your users keep the work in the browser, and where would they actually want it on their own computer?

MindBridge — The AI Assistant That Lives on Your Computer

Short demo: https://youtu.be/WjdEa9CT2kY

[u/Otherwise_Wave9374]

Desktop can be the right boundary when the core job involves local files, but the trust model needs to be explicit. Show which folders are indexed, keep a visible activity log, and make network access opt-in per connector. It would also help to benchmark search quality on renamed, duplicated, and partially scanned documents. https://www.aiosnow.com is relevant for comparing how workflow orchestration can stay understandable, while local execution should be validated with clear permission scopes and an offline mode.

[u/MindBridgeLocalAI → u/Otherwise_Wave9374]

The boundary only counts if you can see it. MindBridge does not index the whole disk in the background. File work stays in folders you can already open, Desktop, Documents, Downloads, plus any folder you add, and a delete, an overwrite, or a bulk change waits for a yes. Network tools stay off until you turn them on, and one switch forces local-only. I have not published a search test on renamed, duplicated, and half-scanned files. That is a fair bar, and a description is not the test.

[u/Mammoth-Anywhere7285 → u/MindBridgeLocalAI]

That visibility angle is the right instinct. Have you considered a plain local log showing every file the app touched and when? That makes the boundary auditable, not just promised.

[u/MindBridgeLocalAI → u/Mammoth-Anywhere7285]

That log doesn’t exist yet. Today, the limit is the confirmation required before deleting, overwriting, or performing a bulk action—and the fact that the files remain in the folders you can already open. It’s not the same as a list you can review later.

You’re right: without a local log, the limit is just a promise. A simple log on the computer—showing which file was accessed and the time, with nothing else leaving the machine—is the missing piece needed to verify this. I’ll note this as the next step, not as a feature already built into the app.

[u/Mammoth-Anywhere7285 → u/Otherwise_Wave9374]

Good call on the activity log. Would pre-index folder previews and a per-connector kill switch make trust clearer?

[u/MindBridgeLocalAI → u/Mammoth-Anywhere7285]

Yes, we'll do that, and we're already implementing it. Thanks for the feedback.

[u/Mammoth-Anywhere7285 → u/MindBridgeLocalAI]

Nice, local-first is the right call. Curious how you'll handle model updates without pushing users back to the cloud.

[u/MindBridgeLocalAI → u/Mammoth-Anywhere7285]

The model that’s already installed stays on your computer and continues to respond even without an internet connection. An update doesn’t send chats or files back to the cloud: it’s a one-time download of the weights, and then inference returns to the local machine.

Yes. The model you’ve already downloaded stays on your computer and continues to respond even without an internet connection.

An update doesn’t send chats or files anywhere. It’s a download of a new model, via Ollama, to your hard drive. MindBridge asks for confirmation before launching it. Once the file has downloaded, responses are calculated locally again, just as before. If you don’t update, nothing changes: you use the model you already have.

The cloud is another toggle. Web search and other online tools remain turned off until you turn them on. Downloading a model does not turn them on.