Alex Godbehere is betting that not everyone wants a bot in their Zoom calls.
His privacy-first transcription app, Trace, sits in the macOS menu bar and does something that's become almost countercultural in the AI era: it keeps your conversations entirely on your machine. No uploads. No accounts. No cloud servers processing what your boss just said about Q3 targets. The app launched on the Mac App Store on May 23, 2026, for $9.99—one-time purchase, which itself feels like a throwback—and has been quietly picking up steam among the Hacker News crowd and privacy-conscious remote workers who've grown wary of the Otter.ai paradigm.
The pitch landed 85 upvotes on Product Hunt and 150 points on a Show HN post on June 15, 2026. Not viral numbers, exactly, but enough signal to suggest Godbehere might be onto something.
Trace does what you'd expect from any meeting transcription tool: it captures microphone and system audio from Zoom, Teams, Google Meet, and Slack calls, then spits out timestamped Markdown transcripts with automatic speaker labels. The difference is where the processing happens. Everything runs locally using speech models that live on your Mac—NVIDIA's Parakeet and OpenAI's Whisper, depending on whether you prioritize speed or accuracy. The app's privacy label on the App Store is about as sparse as they come: "Data Not Collected."
Which is the whole point.
A small detail that matters
What caught my attention, though, isn't just the privacy angle—it's a single keyboard shortcut. Press Cmd-Shift-K mid-meeting, and Trace drops an inline marker at that exact moment in your eventual transcript. Add an optional note if you want. The app calls these "key moments," and it's the kind of small UX flourish that signals someone actually thought about how people use transcripts in the real world.
You're not just archiving what was said. You're flagging what mattered while it's still fresh, before the context evaporates. Godbehere has made this feature central to how he talks about the app—press kit, community forums, the works. Whether that's enough to differentiate Trace in a suddenly crowded field of offline transcription tools remains an open question.
There's also a live recap feature (Cmd-Shift-?) that surfaces a rolling two-minute transcript if you need to double-check what someone just said without derailing the conversation. It runs on the same local models. Nothing leaves the machine.
The technical bits
Under the hood, Trace offers two transcription modes. "Fast" leans on NVIDIA's Parakeet-TDT 0.6b v3, running through FluidAudio's Swift package and Apple's Core ML Neural Engine. "Accurate" mode uses WhisperKit with OpenAI's Whisper large-v3-turbo, which Godbehere says handles accents, industry jargon, and quieter audio with more fidelity. Speaker identification is handled through Pyannote-based segmentation and WeSpeaker v2 embeddings—participants show up as "Speaker 1," "Speaker 2," and so on. Your microphone track stays separate from the rest.
First-time setup pulls roughly 500 MB of models from Hugging Face. After that, you're offline. Sessions save inside the app's sandboxed container as raw WAV files—16 kHz mono float32, clocking in around 60 MB per track per hour. The app auto-deletes those files once transcription finishes, though you can keep them if you prefer. If the app crashes mid-session, you can retry from the saved audio, which is a nice fallback.
Requirements: macOS 14.4 or later, Apple Silicon. Echo cancellation runs by default to prevent your voice from bleeding into the system audio track. Core actions—start, pause, flag moments, hide the floating pill—are all mapped to global keyboard shortcuts you can remap if you're particular about that sort of thing.
Privacy as a positioning strategy
Trace is hardly alone in this. The past several months have seen a small surge of Mac-native meeting tools explicitly positioning themselves as the anti-Otter: HushScribe, trnscrb, Kian, Whisper Notes. All promise some version of "no bots, no cloud, no third-party servers." The contrast with incumbents like Otter.ai is deliberate and pointed. Otter's desktop app can record locally, sure—but the processing still happens in Otter's cloud. Granola, another Mac notetaker that's gained some traction, records offline but sends audio to Deepgram and OpenAI once you're back online for transcripts and summaries.
Godbehere's app skips all of that. Optional Google Calendar integration is read-only and disabled by default; Mac Calendar stays entirely local. The app doesn't even request screen recording permissions—just microphone and system audio. The terms of service, last updated June 10, hammer home the buy-once model and on-device operation. The seller is listed as FSCharter Ltd., a UK entity. On the App Store, the developer goes by AG Labs UK.
Whether this wave of privacy-first tools represents a lasting shift or just a momentary reaction to how invasive cloud AI has started to feel is tough to say. But there's clearly an audience willing to pay for the reassurance that their meeting notes won't end up training someone else's language model.
What it doesn't do (yet)
Trace is English-only for now. Feed it a conversation in Spanish or Mandarin, and you'll get garbled English-mapped nonsense. Heavy cross-talk can still trip up the accuracy, and highly technical or domain-specific terminology doesn't always land cleanly, though echo cancellation helps smooth over some of the rougher edges.
On Hacker News, Godbehere hinted that speaker naming—actually labeling participants instead of just "Speaker 1"—is on the roadmap. A non–App Store distribution is under consideration if enough people ask for it. The version history shows an initial 1.0 release on May 23, 2026, followed by a 1.0.1 patch on June 1, 2026.
Pricing sits at $9.99 in the US. One-time. No subscription. Product Hunt posts and scattered Reddit threads in r/macapps and r/AiNoteTaker popped up a few days before the Hacker News wave hit.
For Godbehere—an indie developer working out of the UK without the backing of a VC war chest—the early traction is probably encouraging. Whether that translates into sustainable revenue or just a niche win among privacy diehards, well, we'll see. But if nothing else, Trace is a reminder that not everyone wants their meeting transcripts processed in the cloud, and some are willing to pay a tenner to keep it that way.
