Privacy-First, Low-Friction UX for Voice AI Products (Full Transcript)

[00:00:00] Speaker 1: Do you guys have any advice for founders who are building in general, but also with voice AI? Privacy is design. Voice data is very sensitive by default. So you need to be really intentional about what you store, how long you store it, do you encrypt it, do you avoid storing it? And actually for us, for earmark, because we view privacy so strongly, we do have an option on all of our plans, which is called temporary mode, where we actually don't store the transcript or any of your data at all. There's no retention plan. It literally just bypasses our database completely. So really designing around that and thinking about that is really important. But one of the lessons that we learned early on too, for voice AI products, is actually making the UX really forgiving. So when a user is using a voice AI product, they're actually taking action in something else. Like they could be in a meeting, they could be on a phone call, or they could be in a conversation with something. The product that you're using is almost secondary to them. So if you are trying to capture a conversation and in order to start that capture, it's like four button clicks or different configurations, the user is just not going to use it. So it needs to be dead obvious. Like, can it be one click or could it do it for you? And if there's a blip that happens, can it resolve itself or can it figure things out itself? Just removing those decisions from people while they're using something else I think is a huge thing that it's easy to overlook when building with voice AI products.