SODAX SDKDigital asset flows you can build and deploy with AI.
Promoted
Launching today
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.
Can Oats pick up audio from headphones as well as the laptop speakers? that’s always a tricky part with meeting apps.
Oats
@croft_benjamin Yes! We have multi channel recording, so it works with headphones and laptop speakers
Congrats @maxheckel how much CPU/RAM does it typically use while recording? curious how lightweight it is on older laptops.
Oats
@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.
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.
Oats
@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!
Oats
@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!
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.
Oats
@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!
Oats
@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!