Alt – A local AI lecture/meeting notetaker

Hacker News

Most AI notetakers have a 300 minute limit. This is not enough for uni students like me, or people who do remote work. So, I made a notetaker that runs the ASR model on-device. - Free with local ASR & LLM models - No transcription time limit - High accuracy for non-english speech, support for 100 languages - Real-time transcription - Zoom/Google Meet support - No internet needed - Efficient battery usage (~6 hours on full charge on my M2 Pro) This started as a small cli tool I made for myself, then many of my uni friends really liked it, so here it is as an app! I hope a lot of people can use this in their classes or meetings to help with their work. During the development process, I also made the fastest streaming ASR pipeline on Apple Silicon. You can see it here: https://github.com/altalt-org/Lightning-SimulWhisper

Visit product View on Hacker NewsNov 27, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, apple, google · Missing: mac, agents, macos

89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: pipe, io · Missing: https docs, excited, just released

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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