Thought Leaders in Artificial Intelligence: Gurjeet Singh, Co-Founder and Chairman of Ayasdi (Part 5)

Sramana Mitra: Do you want to talk about the healthcare use case a bit?

Gurjeet Singh: Similar to financial services, we build applications that solve problems end-to-end. The first application in healthcare that we sell to both healthcare payers and providers is the application that detects and hopes to mitigate the problem of clinical radiation.

Given the regulatory environment in healthcare and the way it’s changed over the past two years, one of the major problems is that healthcare providers in particular are beginning to have to own risk for their populations. Medicare essentially pays what’s known as a bundle payment. Think of it as I’m going to give you $100. I don’t care how much it costs to you. I’m going to pay you $100.

With the Obama regime, healthcare providers couldn’t really say no. If somebody shows up for a knee surgery, if Medicare is paying for it, you better do it. The major realization that healthcare systems have had is that one of the major contributors to the cost is a variation in the care they deliver.

Every knee surgery is unique. Physicians oftentimes are very uneven. There are physicians and surgeons who do lots and lots of surgeries and are very experienced. There are some physicians who read up on the latest literature and follow the latest protocols. There are some physicians who have been doing it for a very long time. Even though they’re super experienced, they don’t readily know the latest.

The basic idea in clinical variation management is to look at this very complex patient data as millions of patients go through healthcare systems. For each particular procedure, construct standard care practices that everybody can agree to follow and that can reduce the cost of delivering these services dramatically.

I’ll give you one particular example. Mercy hospital systems use our software against all of their knee surgery data and discovered that there were two surgeons in one of their hospitals whose outcomes were dramatically better.

When they looked at the data, it turned out that right after the knee surgery, they were administering a drug to those patients. It led to patients being able to walk sooner after the surgery. That had the effect of accelerating the recovery and it reduced the hospital stay time by about a day and a half. That’s a huge amount of cost saving for them. The data was so complicated that they had no hope of discovering these kinds of things if they went about manual intervention.

Sramana Mitra: Very interesting. How far along are you in terms of revenues, customers, and growth rate?

Gurjeet Singh: I won’t discuss any of these numbers. Suffice to say, we are growing pretty quickly. We are about 150 people. We have a large office in New York. We are growing at a rapid clip. It’s not hard to gauge the health of the company.

Sramana Mitra: Switching gears a little bit, what pointers do you have for emerging entrepreneurs in terms of open problems that you’re seeing in the general AI space? Where would you point people to look?

Gurjeet Singh: The first advice in the AI space is to not attempt to solve the general problems. It’s obviously based on what we had to do. Find problems that are very specific that you can solve end-to-end. Especially when you’re selling enterprise software, they don’t really care about the general problem. They care about their own specific problems.

It’s easier to hire and train sales forces to be able to talk about those problems. It’s easier to convince customers. Strategically, find a niche where you can solve a problem end-to-end where your AI technology gives you a leg up on the way it’s solved today and then try and expand from that niche.

Sramana Mitra: That’s where the AI startup market is right now. More than the AI algorithms, it is the domain knowledge and specific understanding of a business problem where the opportunities are.

Very nice meeting you. Thank you for your time.

This segment is part 5 in the series : Thought Leaders in Artificial Intelligence: Gurjeet Singh, Co-Founder and Chairman of Ayasdi
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