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.
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.