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).





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Honestly it's rare by volume but it clusters right where it hurts, the fast back-and-forth when a decision actually gets made, so it feels worse than the raw percentage suggests. I wouldn't chase overlapped-speech separation, it's expensive and still flaky. I'd just surface it: flag the low-confidence diarization spans so I know which two or three lines to re-listen to, instead of trusting a transcript that looks clean. The silent winner-pick is the part that bit me, not the noise.
@dipankar_sarkar thanks!
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
@ashmil_hussain give it a try and let me know! What type of noisy rooms are you thinking of? public places?
Curious how it handles crosstalk or people talking over each other in a noisy room. Does the speaker identification still hold up, or does it get messy fast?
@abdulkadirc80x Give it a try. You can start free.
How well does the speaker identification actually work when people are talking over each other or interrupting? That's usually where these tools fall apart for me.
@sedadedemen Interruptions will always be hard in in-person meetings. For virtual it's much easier because they have different audio input.
How well does the speaker identification work in a noisy cafe or group setting with people talking over each other?
@aminekorkf8bw give it a try for free.
How do you balance giving users AI coaching feedback without making conversations feel overly analyzed?
@robert_dimla Can you tell me more what you mean with overly analyzed? Appreciate your time.
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.
@yusufgbelbkvy thanks for quick test and feedback! How many people were in the standup?