skun

That makes sense. I will make changes to the README and we will make a quick product video too :)

Hi, dev here.

Thanks so much for engaging :) I understand your point, here's sort of the philosophy behind the decisions we took regarding it:

The purpose of the app was to be as _hands off_ as possible. And because an LLM is involved in the mix, it might misclassify some emails and delete them.

For this reason, we label each email that we delete and it is possible to navigate to the email from the Run Status screen also, thereby allowing us to recover that email (if it was wrongly deleted). There is also a filter on the run status page to show all those emails marked for deletion.

In all our test runs, we found misclassification to be a minimum and hence we felt confident to go with this approach.

The "Schedule new cleanup" does indeed schedule a background task that does the actual inference + deletion.

Hey HN! We’re a small team of friends who built an app to help you clean up your Gmail inbox — privately and locally.

# The Problem

We all get bombarded with emails, making inbox management overwhelming. Many tools can help, but they often require cloud access, risking your data privacy.

# Our Solution

Our app uses local large language models (LLMs) to smartly organize your emails, highlighting what’s important and filtering out the noise — without sending data to the cloud.

# Why It’s Different

- Private: Runs entirely on your device; no data leaves your machine. - Open Source: You can review everything before using it.

# Why It Matters

In a world where data privacy is crucial, our app provides AI-powered inbox decluttering without sacrificing control of your information.

We’d love to hear your feedback and ideas to help us improve. Thanks for checking us out!

Author here. In case any of y'all have any questions/suggestions, I'd be more than happy to address them :)