Show HN: WhisperBuddy, Privacy-first AI-transcription app built after my layoff (whisperbuddy.com)
I was laid off recently and, instead of looking for another job right away, I decided to build something I always wanted: a transcription tool that respects user privacy.
Existing transcription tools often require internet connectivity, send your private audio to cloud servers, or lock you into monthly subscriptions. I wanted something different—so I built WhisperBuddy, a privacy-first AI transcription app that runs entirely on your machine.
WhisperBuddy uses OpenAI’s Whisper model (see: https://github.com/openai/whisper). While the model may not always deliver the absolute best accuracy, it provides solid performance and, most importantly, 100% privacy—no audio ever leaves your device.
I optimized the app for local performance and usability, and I’m eager to hear feedback from the community.
Thanks for checking it out!
1 comment
[ 6.4 ms ] story [ 89.9 ms ] threadI'm torn on direction: Should I stick to privacy-first and never compromise, or add optional cloud transcription (like Whisper API) for better accuracy while keeping local as default?
The tradeoff is clear - local means decent accuracy, cloud means better results but breaks the privacy promise.
What matters more to potential users: peace of mind that audio stays on-device, or best possible transcription quality? Is there a sustainable market for privacy-focused tools, or do most people prioritize accuracy over privacy?
Would love your thoughts on this positioning dilemma.