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Synopsule
On device private AI meeting transcripts
Synopsule records and transcribes your conversations on your Mac or iPhone with Whisper, labels every speaker, and only summarizes when you ask. No accounts, no uploads. Now on the App Store — one $4.99 purchase for Mac and iPhone.
I built Synopsule because every meeting tool I tried wanted my audio in their cloud, an account, and a bot in the call. I wanted the transcript without the trade.
So the whole pipeline runs on the device that recorded it: - Whisper transcribes locally. The model ships in the app, so it works offline on first launch. - On the Mac it captures both sides of a Zoom/Meet/Teams call by tapping system audio directly. No bot, no screen recording, no virtual driver. - Speaker recognition runs on-device too. It labels who said what, remembers returning voices across recordings, and learns from your corrections. Raw audio is deleted once the transcript exists.
Includes MCP functionality so you can integrate your meeting transcripts with Claude, Codex, and ChatGPT.
Summaries are the one thing that can touch the cloud, and only if you ask. Bring your own key, or run a local model on the Mac so even that stays on your machine. Only transcript text ever leaves, only when you choose.
It's $1.99 once for both Mac and iPhone. Transcription shouldn't be a subscription.
The hardest part was diarization on long, messy recordings, and making speaker recognition improve locally without a cloud model.
I'd love feedback, and I'm here all day. What would it take for you to trust an on-device transcriber over the cloud one you use now?
About Synopsule on Product Hunt
“On device private AI meeting transcripts”
Synopsule launched on Product Hunt on June 15th, 2026 and earned 0 upvotes and 2 comments, placing #115 on the daily leaderboard. Synopsule records and transcribes your conversations on your Mac or iPhone with Whisper, labels every speaker, and only summarizes when you ask. No accounts, no uploads. Now on the App Store — one $4.99 purchase for Mac and iPhone.
On the analytics side, Synopsule competes within Productivity, Meetings and Artificial Intelligence — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Synopsule performed against the three products that launched closest to it on the same day.
Who hunted Synopsule?
Synopsule was hunted by Sunny Nagra. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Synopsule including community comment highlights and product details, visit the product overview.
Sunny Nagra
I built Synopsule because every meeting tool I tried wanted my audio in their cloud,
an account, and a bot in the call. I wanted the transcript without the trade.
So the whole pipeline runs on the device that recorded it:
- Whisper transcribes locally. The model ships in the app, so it works offline on first launch.
- On the Mac it captures both sides of a Zoom/Meet/Teams call by tapping system audio
directly. No bot, no screen recording, no virtual driver.
- Speaker recognition runs on-device too. It labels who said what, remembers returning
voices across recordings, and learns from your corrections. Raw audio is deleted once
the transcript exists.
Includes MCP functionality so you can integrate your meeting transcripts with Claude, Codex, and ChatGPT.
Summaries are the one thing that can touch the cloud, and only if you ask. Bring your
own key, or run a local model on the Mac so even that stays on your machine. Only
transcript text ever leaves, only when you choose.
It's $1.99 once for both Mac and iPhone. Transcription shouldn't be a subscription.
The hardest part was diarization on long, messy recordings, and making speaker
recognition improve locally without a cloud model.
I'd love feedback, and I'm here all day. What would it take for you to trust an
on-device transcriber over the cloud one you use now?