Hi HN, I built threadfork. It's an AI notetaker where the whole pipeline runs locally on Apple Silicon. Your microphone and system audio gets captured without a meeting bot and most importantly your meeting data doesn’t get sent or saved anywhere.

I've been building in the privacy + local LLM space for the past several years (I started DataFog, an OSS PII detection library with 300K+ downloads); keeping all the processing and data on-device was a day 0 condition for me when building this out. Granola's updated privacy policy, effective later this week, keeps non-enterprise users opted into model training on "de-identified" data by default. Having built PII detection for a living, I'll say plainly: de-identifying meeting transcripts is really hard. Names are the easy part; deal terms, client details, and health disclosures are the transcript. For the lawyers, consultants, and therapists I've been talking to, the only version of this that holds up is the model never seeing the data at all.

It's macOS 14+ on Apple M-Series computers (for now), 14-day trial, no credit card. I have a user running this on an M1 8GB so older machines welcome. $40/month after that. I use this product daily and you can expect regular updates.

Welcome any/all feedback.