Comment by isabelleilyia
3 days ago
I think the problem relates to the core value proposition of automating an intake department with voice AI. The best voice AI customer is in an industry in which there is a clear increase in value that comes with the ability to handle a larger mass of calls. This was not the case in the legal world, when one missed client might be a loss of millions (and many firms would live off of < 10 successful cases a year).
Therefore I think the verticals of customer service and lead pre-qualification make a lot more sense. Since you guys have the numbers, I am curious to learn more about the way you define constraints for the bot and how often calls in these verticals deviate from these constraints.
I'm also curious about your opinions/if you've seen any successful use cases where the bot has to be a bit more "creative" to either string together information given to it or make reasonable extrapolations beyond the information it has.
We see the main value prop of voice AI to be to enable higher volumes of calls in a cost-efficient manner. It is clear that there is a slight trade-off on quality, because humans will do a better job in "high-stakes" calls and where creativity is more required.
It thus makes sense why it might not work for legal, since every call there might be high stakes.
Having the bot be "creative" is actually an interesting proposition. We currently do not focus on it, since the majority of our customers want the bot to be predictable and not hallucinate.