Oats - Free open-source and on device meeting notetaker
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Oats is an AI meeting note-taking tool that is completely open, local, and free. Designed to not get in the way of your meetings, no bots, no subscription needed when running locally with on-device LLM. Available on both macOS and Windows.
Enhanced transcription, multi-language support, speaker recognition, assessment, coaching, auto-tracking follow ups and more features via ariso.ai cloud backend.
Replies
free and open source is refreshing to see. are there plans to support more local models in the future?
Ariso
@angelo_bram Yes, definitely! Feel free to also create an issue on our github repo!
fyi@unplug_eth0
Open source + local AI is a great combo. can users swap in their own local models?
Ariso
@james_carter35 Yes we plan to add support for user's own models soon
fyi @unplug_eth0
No meeting bot is a really nice touch. does Oats work smoothly with Zoom, Meet and Teams?
Really curious about the speaker recognition part. does that work locally too or does it require the Ariso backend?
Respect for the privacy and no-subscription approach!
Ariso
@jackdonovan thank you!
EverTutor AI
The no bot approach is probably my favorite part here. Keeping everything local while still getting useful meeting notes is a really nice balance. Open source makes this even more interesting. Congrats on the launch team!
Ariso
@suryansh_tiwari2 Thanks! Let us know if you have any feedback
Refocus
The no-bot-in-the-call part is what stands out to me. I build voice AI for daily check-in calls with older adults, and the thing that consistently bites us is not the LLM, it is the front of the pipeline: soft or slurred speech, hearing aids, a TV going in the background. Which on-device ASR did you settle on for the local path, and how much accuracy do you give up versus the Ariso cloud route on noisy audio? Also curious whether speaker recognition is cloud-only by design, or if local diarization is on the roadmap.
Ariso
@igorgurovich noise canceling does a pretty decent job most of the time, and even though the audio/transcript may not be perfect, the AI models can do a great job at summarizing the notes!
Ariso
@igorgurovich Ariso cloud version will always be better. We went for an optimization on both cost and effectiveness for the local models. If there's some other models you'd like it to use you can always open a pull request on our github repo for Oats to add them!
Congrats @maxheckel how much CPU/RAM does it typically use while recording? curious how lightweight it is on older laptops.
Ariso
@imogen_wallace Right now it requires around 2GB of ram to be effective. CPU shouldn't matter as much and should be fine with any modern laptop. If you use the cloud backend (which is also free), you can have a total potato of a laptop and still have it work effectively.
Dial
left a review above - the no-bot, fully local angle is what stands out here. curious how the diarization/speaker recognition holds up locally when the model is small enough to actually run on a laptop, that's usually where local AI notetakers fall behind cloud ones.
@galdayan diarization/speaker recognization for local backend is indeed a challenge b/c of the performance of local model. I’ve tried several STT models and Oats use the best I’ve tried.
remote model is indeed better and Ariso backend provides more features including speaker profile and auto matching. give it a try and share us your feedback!
Dial
@unplug_eth0 makes sense, that's a fair tradeoff to be upfront about rather than overselling the local mode. good to know Ariso is there for whoever needs the speaker-profile matching. will give the local backend a real try on some messier multi-speaker recordings and report back what I find.
Ariso
@galdayan Feel free to try it out! We think it works pretty great right now. But if you notice any room for improvement, let us know!