Which brings up the answer to your question: We're targeting developers. Companies that build integer programming solvers and similar tech have great tools for PhDs in Operations Research who have a lot of mathematical sophistication. We think there is an underserved market of software engineers who can benefit from different technology.
One thing that's struck us is the lack of accessibility of optimization tools to software engineers. I worked as a developer long before I ever got into OR. When I switched over to being an analyst, it felt like there was an invisible divide between the two worlds.
A great success of the Data Science movement over the last decade seems to be making statistics and visualization easier for and more widely adopted by tech. We think optimization and simulation are about to go through the same thing.
A general thought, which might be important in the future. This kind of optimization tools work best at scale, I would go even as far as saying only at scale. And that can make a MVP a hard thing. I have seen people try something similar without the necessary scale, or rather density as routes were spread out over to large a region. And it didn't work out that good.
What I didn't get, but then might be just me, is who your customers are. Developers or users? If it's the latter I could provide some operational insight.