Why do you think it didn't work out in legal? We currently don't focus on that domain.
In general, we currently have really high success rates with relatively constrained use cases, such as lead qualification and well scoped customer service use cases (e.g., appointment booking, travel cancellation).
In general, voice AI is hard because WYSIWYG (there is no human in the loop between what the bot is saying and what the person on the other side gets to hear). Not sure about legal, but for more complex use cases (e.g., product refunds in retail), there are many permutations in how two different customers might frame the same issue and so it might be harder to accurately instruct the AI agent in a way to guarantee high automation results (given plentitude of edge cases).
It is our belief therefore that voice AI works the best, when the bot is leading the conversation and it is always very clear what the next steps are...
In general, we currently have really high success rates with relatively constrained use cases, such as lead qualification and well scoped customer service use cases (e.g., appointment booking, travel cancellation).
In general, voice AI is hard because WYSIWYG (there is no human in the loop between what the bot is saying and what the person on the other side gets to hear). Not sure about legal, but for more complex use cases (e.g., product refunds in retail), there are many permutations in how two different customers might frame the same issue and so it might be harder to accurately instruct the AI agent in a way to guarantee high automation results (given plentitude of edge cases).
It is our belief therefore that voice AI works the best, when the bot is leading the conversation and it is always very clear what the next steps are...