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.