Anyone here using a local setup for AI meeting notes?
Posted by hulk14@reddit | LocalLLaMA | View on Reddit | 8 comments
I’ve been trying to move more of my workflow local, and AI meeting notes are the one thing I haven’t fully figured out yet.
Right now I’m using Bluedot because it’s simple, it records meetings without a bot joining, and I get a transcript, summary, and action items after. The searchable transcript is also really useful when I need to go back and check something quickly.
Ideally, I’d like a local AI meeting notes setup that can do something similar. In theory it’s just recording + transcription + summarization, but I’m not sure how well local models handle longer, messy conversations.
Are you running a local AI note taking setup for meetings? What models are you using for transcription and summaries? Is it reliable enough to replace cloud tools yet?
Ok-Cap-5556@reddit
you are hitting exactly why local gets tricky for meetings. The models for transcription are decent now, but getting that summary and action item pipeline running smoothly takes a lot of tinkering. I tried it and ended up spending more time configuring than I saved. We switched to using Scriptivox for this. Their meeting bot just joins and does everything automatically. I set up an automation so after each call it spits out a summary with action items and emails it to me. The searchable transcript is the real win though, makes finding that one thing someone said weeks ago way easier.
Cereal_Grapeist@reddit
If you look at OP's post history (search blue) and u/JackStrawWitchita's comment, you'll see that this post is actually an advertisement for bluedot.
Fuck off with this stealth advertising
JackStrawWitchita@reddit
Wow, calm down buddy. I'm not promoting anything. I'd rather homebrew my own solution, especially for my other projects where confidentiality is an issue, as I wouldn't trust any product such as the aforementioned tool (there are many alternatives).
Many_Translator787@reddit
As noted diarization will be the biggest hurdle, in meetings there can be allot of overlap which traditional clustering models struggle with. I'd try using neural / e2e models instead. I've had good results with the nemo models. They do require nvidia gpus and much more computationally expensive, for a diarization model but as far ive tested they yield the best results. Lil harder to work worth than say pyannote tho.
FullOf_Bad_Ideas@reddit
I am not a user but I've ran into dev of this project on this sub in the past.
https://github.com/Vexa-ai/vexa - it's a self-hosted open source project that handles bot and transcript for you. You'd have to set up some n8n workflow to send you meeting notes - https://docs.vexa.ai/n8n#basic-workflow-calendar-to-transcript-to-summary
JackStrawWitchita@reddit
It would be interesting to see the response you get as I tried to set something like this up using local models using the same workflow but the local models couldn't reliably handle the task of separating out speakers and summarising as well as bluedot. And since that tool was reasonably priced and our meetings weren't especially security-orientated, we just stuck with that.
Stepfunction@reddit
Diarization is the main issue with setups like this. Figuring out which sound belongs to which speaker when doing transcription.
If you're using a bot in a meeting to do the recording, many of them are able to separate the audio for different speakers, which trivializes this problem though. For example, we use the Craig bot to record D&D sessions on discord and that separates each speaker's audio. I then transcribe with whisper, have a script to mash it all together into a single text file, and then dump it into the context of Gemma 4 26B.
seamonn@reddit
Pyannote Community works decently well but confuses speakers a lot of the time.