Do customers tend to upgrade from duct-taped solutions to automated or AI-based tools like Levity?

Definitely. That's also why we’d rather focus on companies with 100+ full-time employees because with the really small ones or sometimes, larger companies with "small processes”, if there's insufficient data, there are multiple issues. 

First, you can't really train something that works well if you don’t have enough historic data. Second, if the volume that you're processing is low, there's no urgent need to automate it. It only really gets painful, if some person is spending 10 to 20% of their time doing this task, so, when you scale, you need to hire more such people. That's what we've seen often. 

Initially, people tell us, "We're doing it with two interns or two working students right now. It's not an issue." A year later, they have 50 of those people and then, it becomes huge. That's why the amount of data that's being processed is an important factor for how much of a pain it is and how likely it is that they will succeed.