talat - local, real-time meeting transcription and summarisation
Hi folks! This won't be the first 100% local, on-device meeting notes app you've seen recently, so I'll jump straight to what I think makes talat stand out. Timestamps in square brackets if the feature is in the video - if you want to skip to the app in action, skip to about 55s in. The recording experience Automatic call detection: when you join a Meet, Teams, or Zoom call, talat starts recording on its own [00m55s]. Configurable desktop notifications keep you informed or ask permission depending on your preference [01m05s]. Real-time transcription as you speak, sub-second end-to-end [01m10s]. The moment someone stops speaking, a second higher-quality pass runs and corrects most small errors [01m25s]. Speaker identification on both sides of the call: talat tags who said what whether you're all in the same room or split across a remote call [01m25s, 01m28s]. Clean audio separation: if you're not on headphones, most apps re-record the remote caller's voice through your speakers and transcribe it as if you said it. talat strips that bleed-through out. Auto-stops and summarises when you leave the call [01m45s]. Default summarisation LLM is Qwen-3.5-4B-4bit [02m00s], but you can swap it for any other local or cloud model if you prefer. Auto-detection works for ad-hoc calls too, not just calendar events. The only difference is that a matching calendar event pre-populates the meeting subject and attendees (see the "Who's here" panel during the live portion of the video). Footprint Only two permissions needed: microphone and system audio output recording. No screen recording. No accessibility permissions (which some others use to watch which apps you're in for call detection). No in-app telemetry. talat doesn't track which features you use, which meetings you have, or anything else about your sessions. The one outbound call talat makes on its own is an occasional license-validity check, which asks our server whether your license has been refunded. If our server is unreachable, talat just carries on. Works completely offline: turn your WiFi off and record your in-person meetings. 20MB download on macOS, instant startup, lightweight runtime. Calendar Apple Calendar and Google Calendar integration out of the box [start of video]. Customisation and integration Global start/stop hotkey - works alongside auto-detection or replaces it. MCP server so you can plug meetings and transcripts into any external AI you like (we can't guarantee privacy here, but it's your relationship and your choice). Optional webhook invocation on call finish for programmatic integration with your own systems. Multilingual support (25 European languages today, we're looking to broaden this in future releases). Output Automatic markdown export of transcripts, notes, summaries - any combination, on call finish. Manual export to clipboard, PDF, or Markdown. Split or merge recordings after the fact. Optional retention of audio recordings during a call. How talat compares Most cloud meeting notes apps work well, at the cost of every frame of audio, your transcripts, and your summaries passing through someone else's servers, and you pay forever (either with your data or your wallet, or both). Local alternatives often try to do too much, or they need driving. I wanted something that did meetings well and got out of your way. vs Granola (full comparison) I love Granola; talat exists because I wanted what Granola does without the cloud + subscription tradeoff. Audio, transcripts, summaries never leave your Mac (Granola sends them to its backend). One-time purchase vs subscription. Swappable summarisation LLM (Granola is locked to its backend). Apple Calendar + Google Calendar (Granola is Google only). vs Snaply (snaply.ai) - a very polished local option talat is singularly focussed on meeting capture, real-time, speaker ID, etc - Snaply is more general-purpose Have a look at Giacomo's recent post; the features above are where we've put our energy. Pricing and cadence Free trial: 10 hours of recording. Past data stays after the trial ends; you just can't record anything new without a license. One-time purchase, $49 during pre-release, with lifetime updates included. Automatic updates, and we ship them fast: 21 releases in 2 months since launch. About us talat is built by Nick Payne (me) and Mike, trading as Lumikey Ltd (UK company). LinkedIn: https://www.linkedin.com/in/nick-payne-6a9102267/ Email: nick@talat.app App is fully signed and notarised by Apple under my personal Developer ID (Nicholas Payne). Privacy policy: https://talat.app/privacy Terms of service: https://talat.app/terms Refund policy: https://talat.app/refund TechCrunch covered talat back in March: https://techcrunch.com/2026/03/24/talats-ai-meeting-notes-stay-on-your-machine-not-in-the-cloud/ What we're going for with talat: a meeting notes app that gets out of your way. Join a call, it records. Leave, it summarises. Everything above is in service of that. Happy to answer any questions. Find out more and download at https://talat.app/. Cheers, Nick
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Lol this is what the 3rd or 4th meeting app posted THIS WEEK? Guys, give it a break.
Honestly, even though they are a dime a dozen, I STILL can't find one that is better than the voice notes on Apple Notes. I'm still on the search for something to replace it.
We’re heading toward a world where the number of alternatives to an app matches the number of developers who want to use it.
I tried to acknowledge that in the opening sentence and concentrate on what sets talat apart - I've noticed a growing number of apps but also noticed most are low quality or incomplete (with notable exceptions, like Snaply as noted in the post). talat is the culmination of almost a year and a half of related work specifically in the audio/recording space where I've put together different parts of the puzzle. I couldn't exhaustively enumerate and compare it against everything, so tried to largely stick to showing its own merits, though I appreciate it may have missed the mark
instant startup, lightweight runtime? Except for the whisper or parakeet download and loading into memory which is 400+ MB?
Fair point, though all local transcription apps pay that same cost (we use Parakeet btw and others - full list is credited in the app). I wasn't trying to pretend otherwise - the intent was simply to clarify that the app itself has a small footprint compared to e.g. apps which use Electron and or embed a Python runtime (which I have seen done!)
This looks quite nice. I use something from my setapp sub, but it has a horrible workflow and UI. Will check it out and compare 👍🙏
Thank you - any feedback at all would be amazing
Looks well made, does it work with discord?
thanks! Yes, it does, both in browser and via the discord desktop app
Good breakdown. The main thing that stood out to me is that “100% on-device meeting notes” is becoming baseline pretty quickly. There have already been several apps in this category posted here over the past few weeks, and they’re all leading with the same angle. The more interesting differentiators are actually the infrastructure problems you mentioned halfway through the post: detecting ad-hoc Zoom/Meet/Teams calls without calendar events, and fixing speaker bleed-through when people aren’t using headphones. Those are the kinds of things that sound minor until you try to build them, and most competitors are probably going to ship flaky versions for a while. If you revisit the landing page later, I’d put those front and center instead of leaning so hard on the local/private positioning. “Local-first” will stop feeling novel pretty fast. Solid engineering that noticeably improves the experience won’t.
Thanks - I really appreciate that perspective. The private angle really felt like it wa*s **the* differentiator back at the start of my long journey which led to talat, but every day I was lurking rather than posting on Reddit I saw more and more alternatives appearing. I think it's likely a combination of the latest AI models being so capable and a better awareness of the macOS APIs which allows recording of system audio without video (which I like to think I played a minuscule part in, having open sourced a library a year ago which helps people do just that!). I'll do my best to put the 'delighters' more front and centre next time I get the chance to fettle the website.
Does it have an option to ask AI questions during the meeting? Just like the "what did I miss?" or the "make me sound smart" prompts on Granola?
Not yet, at least not directly in the app. A lot of early users have asked for it, but we're reluctant to offer it unless/until we can make the default LLM we ship with - Qwen-3.5-4B-4bit - work well enough. We could add live chat today with the caveat that users would have to point at a better model (the best they can run locally via Ollama, or a cloud provider if they're happy with the privacy tradeoff), but if it doesn't work for our lowest common denominator, we're cutting a whole load of users out and giving them a trash experience. The indirect method I alluded to is via MCP; you can point any capable AI at the live transcript and interrogate it that way, but it's not an integrated experience and requires hopping between apps.
the clean audio separation detail is the one that actually matters. every other app I've tried just transcribes the speaker bleed as if you said it, which makes the transcript useless in a noisy room. does it handle cases where two people talk over each other?
It handles speaker overlap as well as possible, but there are different scenarios: crosstalk where one person is speaking on the mic and one person is speaking simultaneously on the other end of the call is fine, because those streams are completely isolated from one another. Two or more people speaking at the same time on one channel is different: the underlying models process the same audio you'd hear in that situation, so will likely struggle to work out what's being said (much as a human would!).
Just downloaded to test it! I'm curious, how well does it understand languages? I speak french
Yes, French is supported (we offer NVIDIA's awesome parakeet v3 model for this)
Looks nice. I will give it a shot because I am currently using Char (previously known as Hyprnote), but it is subscription-based if I want to have the speaker recognition. So, in the free tier, the quality of the summary fails a bit if I am on a call with multiple people. Also, the live transcription has been removed and is not available.
Great - let me know if you have any feedback as and when you do get around to trying it out.
Well, don’t you worry about nearly all the meeting app would got this feature? Maybe you want to do something different around organizing all the meeting notes from different meeting apps. So that no matter what meeting app you just got all the notes, well, I can’t think of how to add enough value, but I guess that’s a good distinction.
I'm not sure I worry about it, having seen the quality of most of the alternatives out there (with a few notable exceptions, like the one called out in my post). I also know how hard we're both working and how much we care about what we're doing. Call it hubris on my part, but I also think the experience I have in all the auxiliary parts you need beyond basic transcription combined with how much I've put in - and continue to put in - to talat, should help set us apart from the drive-by alternatives looking to cash in and make a quick buck.
can you explain the nature of the diarization in better detail? my issue with all these transcription apps is they all suck when it comes to the effort required to enable good speaker identification. in your video, did the speaker identification work because the app was already trained to recognize your and Mike’s voice? that can be really time and effort intensive for people who meet with dozens of different people a week. The only approach I’ve seen that handles this is an app that relies on captions as opposed to recording, but that app comes with a whole host of other issues that don’t make it reliable yet.
Interested as well. They use the open-source project FluidAudio but unsure how they do live speaker identification. Is it Softformer? But then it can only pick up to 4 speakers in real-time. If not, the other method I know of with that library is not great ,with a high error rate on benchmarks.
Look great! What's the difference with Krisp, Fireflies etc?