u/Bitter-Degree-9832

Over the last year, I started using AI transcription constantly — meetings, brainstorming sessions, walking notes, random ideas, personal journals, everything.

But the more I used cloud-based transcription tools, the more uncomfortable I became with one thing:

Uploading extremely personal voice data to external servers.

Voice recordings contain way more information than people realize:

emotions
speaking habits
names
schedules
client discussions
private conversations
unfinished thoughts

And unlike text, voice feels much more personal.

A lot of AI tools today normalize sending hours of recordings to the cloud without people really thinking about where that data ends up, how long it’s stored, or whether it could eventually be used for analysis or future model training.

That concern is what pushed me to build Loro.

The entire app was designed around one idea:

your recordings should stay on your device.

So everything runs locally:

no cloud uploads
no accounts
no external servers
Whisper-based on-device transcription

What surprised me most was how many people were specifically looking for privacy-first AI tools. After launch, the app reached #3 in the Korean App Store Productivity category within 3 days.

Some things users seem to like:

fast record → transcribe workflow
fully offline processing
surprisingly accurate transcription
Apple Watch support for quick capture
useful for meetings, lectures, content ideas, and personal notes

Still improving it, but building this made me realize local/private AI tools are probably going to matter much more over the next few years.

Most transcription apps upload to the cloud. I built Loro to be a 100% offline AI transcriber.

I built an AI note taker that keeps everything on-device