Mark Geene: We don’t do a point-to-point mapping structure. We give companies the ability to define a data structure, create a virtual representation of that, and make them all look the same.
The benefit of that is, instead of doing all these point-to-point mapping, you’re now always dealing with one common model. We help them make everything they integrate to look like that common model. That’s one of the big differentiators.
The other is that we can be fully embedded in someone else’s platform as opposed to being a standalone integration product where you’re not owning the user experience. Dialpad wants to own that user experience. They differentiate their product based on the experience they provide to the product users.
We’re the only integration platform that you can embed into other products seamlessly because we’re 100% API-based. Those are a couple of the key differentiators. Then, there’s the breadth of our catalog of integrations. We’re approaching deep integration with applications we integrate to.
Sramana Mitra: I would like you to take yourself to a 30,000-foot level. What open problems do you see from where you sit? If you were starting a company today, what kind of company would you start?
Mark Geene: I was talking to some entrepreneurs yesterday at a conference I was at. There has been such a proliferation of applications in every segment of the industry.
There are 12,000 FinTech companies. I saw a report that there are about 7,000 funded FinTech companies, not including banks and financial services. You got this fragmentation of data structures and everything else that’s just pervasive.
Some of the things I get excited about is a new company cropping up that has a format for how insurance policy data can move around across these different systems. I talked to somebody else who’s doing that in healthcare.
The ability to make intelligent decisions and move data across for different industries and different vertical markets is going to be a huge opportunity. That verticalization of platforms beyond just being horizontal in nature is a tremendous opportunity.
Sramana Mitra: Yes, I think verticalization is a very interesting opportunity as well. Everywhere you want to insert AI, AI works a lot better with a constrained data structure. Every vertical will have its own vertical implementation. Verticalization is a very interesting opportunity.
Mark Geene: I’m seeing that over and over again. If you think about SaaS, the big successful SaaS companies primarily have been horizontal. They’ve done some things to tailor it to industries, but it’s not the deep, rich knowledge in that industry.
Even vertical applications that have been built for specific industries don’t necessarily work well with the horizontal applications. Applying intelligence and machine learning at a vertical market level, normalizing data, and creating predictive intelligence is going to be a huge frontier over the next 10 years.
Sramana Mitra: Thank you very much.