Ellis - AI Notes for In-Person Meetings

👋 Hey Product Hunt!

I'm Robin, creator of Ellis — a personal AI notetaker for in-person meetings.

What is Ellis?

Ellis is a simple consumer-first AI notetaker (iPhone and Apple Watch) for in-person meetings. It works anywhere being in the same room matters: coffee meetups, on-site sales meetings, therapy, doctor visits, interviews, or even your teacher-parent conference.

When the meeting ends, Ellis matches your voice against your saved voice profile, gives you a full transcript with an easy way to assign speakers, and writes notes in the format you pick.

Why Ellis? 🤔

Unlike other notetakers that are built for your org, Ellis is built for you as an individual. You can record lots of different in-person conversations, ask questions across them, and find common traits and trends spanning both your professional and personal contexts. Yes — I might want to know how my sales meeting went AND how I navigated a difficult conversation with another caregiver. Two different use cases, but one repository, built for me.

Key features 🤩

• Getting "who said what" right. Telling speakers apart in a real room is harder than online — every voice hits the same microphone. Ellis solves this with voice enrollment and diarization, plus a fast way to tag yourself and others.

• Ask anything about a conversation. Pull up what was said, decisions made, or anything you want to revisit from a meeting — just ask.

• Find it by place. Forgot a name or a detail? Ask by location — "what did we agree on during our walk in Fort Greene?"

• Private by default. Recordings are automatically deleted once transcription is complete.

Happy to answer questions — and I appreciate the support. 🙏

Love this idea. A lot of important conversations happen offline, not just on Zoom or Meet. Being able to record from an iPhone or Apple Watch and ask what was decided afterwards feels genuinely useful. Congrats on the launch!!!

Recording doctor visits and therapy sessions puts this app in about the most sensitive bucket there is, so deleting the audio right after transcription is a smart move. The transcript still says everything the audio did, though. I saw Supabase in the stack, are transcripts scoped per user at the database level, or does the app layer do the gatekeeping?

how well does it pick up multiple people talking over each other in a louder room, and what happens if someone joins the meeting late mid recording?

Recorded a quick team standup on my iPhone and the speaker identification was spot on, even with people overlapping. Asking it what got decided after felt like magic.

Runs quietly in the background and nails speaker labels without any setup. Wished I had this for those standup meetings where half my notes end up being nonsense.

The speaker identification works surprisingly well even with overlapping voices in noisy rooms. Love that it runs straight from the watch, no fumbling for the phone mid-conversation.

Used it for a coffee meeting yesterday and the speaker separation was actually solid, even with background noise. Chatting with the transcript afterwards to pull out action items felt weirdly natural.

the watch app is such a smart move, honestly didn't expect that and it makes the whole thing feel effortless instead of just another thing to remember to open.

nice, everyone builds for zoom calls and forgets real meetings exist. curious how it does with a noisy room, that's where my notes always fall apart