From Solo Techie Entrepreneur to High Growth, Profitable Enterprise AI Success Story: Findability Sciences CEO Anand Mahurkar (Part 1)

I always love doing stories of my readers. Anand has been following the blog since 2010. He has built a terrific, fundamentals-focused AI company. And I am thrilled.

Sramana Mitra: Let’s go to the beginning of your story. Where are you from? Where were you born, and raised, and in what kind of background?

Thought Leaders in Artificial Intelligence: Florian Eggenschwiler, Chief Product Officer of Xovis (Part 4)

Sramana Mitra: How many partners do you have?

Florian Eggenschwiler: About 200 plus of various sizes.

Sramana Mitra: Is it more of the smaller ones?

Florian Eggenschwiler: I would say there is a slight skew towards the smaller companies. They tend to be locally focused and are quite flexible to react to local requirements.

Thought Leaders in Artificial Intelligence: Florian Eggenschwiler, Chief Product Officer of Xovis (Part 3)

Sramana Mitra: Is there an online-offline data overlay as well? You’re not trying to map that customer to a real customer in retail to be able to market to that person?

Florian Eggenschwiler: When you’re online, you don’t tend to be anonymous. In our basic setup, you’re an anonymous dot with attributes like gender.

Sramana Mitra: In retail, you do have the opportunity to make it non-anonymous. You can correlate POS with behavior. You can market to that person using data.

Thought Leaders in Artificial Intelligence: Florian Eggenschwiler, Chief Product Officer of Xovis (Part 2)

Sramana Mitra: Who are the buyers?

Florian Eggenschwiler: It’s usually the airports. There are a number of stakeholders involved that get access to the data. It’s usually the airport that we work with directly. There are also the landlords. They’re the ones that install hardware into the ceiling. They usually tend to be open with this information with government agencies, security checkpoint provider, airline, or ground handling personnel. It could also be the regulator.

Thought Leaders in Artificial Intelligence: Florian Eggenschwiler, Chief Product Officer of Xovis (Part 1)

A fascinating conversation about how Xovis is applying AI to modeling human behavior in public spaces.

Sramana Mitra: Let’s start by giving our audience a bit of your background as well as the background of the company.

Florian Eggenschwiler: I’m the Chief Product Officer at Xovis. Xovis is a Swiss-based company helping the world rethink people flow. We do that by deploying our own 3D sensors that understand people’s movement. Then we have a variety of software applications that make sense of this data to help a variety of industries to understand how people move through our physical world and initiate change to optimize the flow of people.

Thought Leaders in Artificial Intelligence: Starmind CEO Marc Vontobel (Part 5)

Sramana Mitra: You have chosen certain markets to go after. What’s happening in the broader ecosystem that you’re playing in with the same kinds of applications and use cases but in different geographies or maybe different use cases. Who is playing in your space that you’re watching from the corner of your eye?

I’ve seen the solution that you’re describing. Today, AI is at its most mature state. I still remember companies that I saw in exactly the same application, but they failed. Timing is a big deal. For you, this is good timing. Who are the other players in your space that you are watching?

Thought Leaders in Artificial Intelligence: ImpriMed CEO Sungwon Lim (Part 3)

Sramana Mitra: Talk about your business model. Your doctors are your end customers?

Sungwon Lim: Yes.

Sramana Mitra: Is it a subscription service or a diagnostic model?

Sungwon Lim: We charge per service order. Our customers are hospitals and veterinarian oncologists. We sell our service to them and they add their own margin to the pet owners. Pet owners are usually the payers. We are B2B.

Thought Leaders in Artificial Intelligence: Starmind CEO Marc Vontobel (Part 4)

Sramana Mitra: Bottomline is, you’re talking about narrowing the market down more and more to figure out where you want to penetrate the market and where you really want to build the business. Then there are sales channel issues. You have to put Salesforce going after each other’s markets. Let’s get to the technology side of what you’re doing. What datasets are you working with? Let’s take the pharma use case.

Marc Vontobel: There’s always a certain set of tools focused on the use case itself. In R&D, for example, we often see some kind of application that manages the new patterns that people are working on. That’s a very good source for us to learn.