[jon-wood]

While in principle that should be great I don't even slightly trust it as a technique because you're compounding points at which the LLM can get things wrong. First you've got the speech to text engine, which will introduce errors based on things like people mumbling, or a bird shouting outside the window. That's then fed into a summarising LLM to make the meeting notes, which may latch onto the errors in the speech to text engine, or just make up its own new and exciting misinterpretations. Finally you're feeding those into some sort of document store to ask another LLM questions about them, and that LLM too can misinterpret things in interesting ways. Its like playing a game of chinese whispers with yourself.

[jaredsohn]

Understand your concerns; I'm interested in trying it to see if I get value from it (things don't have to be perfect to be useful). For the last part, you can ask it to include a source for how it answers questions and check that.