Ellis - AI notes for in-person meetings
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Ellis is an AI notetaker for in-person meetings. Record your meeting, get a clean transcript with each speaker identified, then ask anything — what was decided, what you missed, how it went. No laptop. No extra hardware. Just your iPhone (or Apple Watch).
Replies
Tested it in a quick coffee chat and the speaker labels actually nailed who said what, which I did not expect. Asking "what did we decide" after felt genuinely useful instead of gimmicky.
Ellis
@sgumushisa32325 happy if was useful to you. thanks for giving it a try
How well does the speaker identification actually hold up when people talk over each other or move around the room, especially in louder spaces like cafes or open offices?
Octolens
Congrats Robin!! Ellis looks super sleek.
Ellis
@charlotteschmitt appreciate it!
Used it during a quick team sync and the speaker labels were actually right on, which I was not expecting. Being able to just ask "what did we decide" after is the part that sold me.
Ellis
@birol160281 happy to hear it.
the noisy-room questions are all covered, mine's about consent instead - you list therapy and doctor visits as use cases, which means the other person in the room is being fully transcribed and analyzable without necessarily agreeing to that. recording is auto-deleted but the transcript sticks around indefinitely. a lot of US states are two-party consent for recording, does Ellis do anything to prompt "hey, tell the other person" or is that entirely left to the user's judgment
Ellis
@galdayan yes! I'm adding an info message before the start of each recording to remind users of consent. I live in Germany, where it's even more pressing :)
When it comes to therapy in particular, I've found that many therapists actually recommend their clients to take notes/record. But that's a very trusted relationship.
Do you have specific thoughts here?
How well does it handle meetings with more than like 6 people talking over each other, especially in a noisy cafe setting?
How well does the speaker identification actually work in a noisy room with multiple people talking over each other? Curious how it handles real-world chaos versus a quiet conference room.
the speaker identification worked surprisingly well in a noisy cafe setting, way better than i expected from a phone mic.
Everyone solved Zoom notes, nobody solved the conference-room whiteboard session. In-person is the harder and more valuable problem. How does it handle multiple speakers without per-person mics?
How does it handle background noise and overlapping voices in a real conference room setup?