Thought Leaders in Artificial Intelligence: Amir Hever, CEO of UVEye (Part 2)

Sramana Mitra: Let’s do another use case.

Amir Hever: The second use case would be car rentals. When you rent, they ask you to mark all the damages that you see. Usually, it’s really hard because you probably don’t cover all of the damages. When you return it, they can charge you for damage that you either haven’t seen or a real damage that you made.

This is exactly what we’re changing right now. We are starting to work with car rentals. When you rent a vehicle, the vehicle is inspected. When you return it, the vehicle is inspected again. We compare the two inspections to see the damage that happened when you rented the vehicle.

Sramana Mitra: That’s a very rational use case. What about penetration? Have you had any of the major car rental companies using this yet?

Amir Hever: Yes, we are working with some of the major car rental companies. Soon, we will be rolling out to more companies. It takes some time. 

Sramana Mitra: Are you piloting them in Israel?

Amir Hever: We’re piloting them in Israel. Soon, we’ll start piloting in Europe.

Sramana Mitra: Let’s do a third use case.

Amir Hever: The third use case would be the car manufacturers. They’re using our system along the assembly line on critical locations to find issues during the manufacturing or the assembly, and of course, also at the end of the assembly line to make sure that the vehicle was assembled right.

Sramana Mitra: So that’s a quality assurance use case. In all of these use cases, the penetration is still very early, right? You don’t have much adoption yet.

Amir Hever: We do have adoption. We are already working with multiple car manufacturers and car rentals. But it’s still in the early stage. We have started working with most of the big players in the market.

Sramana Mitra: Are you seeing competition?

Amir Hever: There is some competition. It’s still in the very early stage. We are pioneers in the market that we are operating in. 

Sramana Mitra: I’m going to ask you to change the line of thinking a little bit. Talk to me about, in your general sphere of knowledge and observation, open problems you see where you would advise a young entrepreneur to start a company.

Amir Hever: We see a lot of use cases in the security market. The missing part is to find the sensors that will be able to penetrate and see what’s inside. There are some x-ray sensors and some sniffers. To have sensors to be able to see inside the vehicle is still missing.

A lot of organizations would definitely want that. It’s not only security compounds, but we see the need in hotels, malls, and sporting events.

Sramana Mitra: That’s a very concrete use case. Is there anything else you want to add?

Amir Hever: I’d like to emphasize that our algorithms are based on computer vision and AI. This is how we do the inspection and how we find the anomalies.

Sramana Mitra: What is the background of the people who have come up with the technology?

Amir Hever: We have deep learning, image processing, and computer vision engineers. These are most of the talents in the company. We build a very sophisticated algorithm that gives us the ability to detect everything that we are looking for in the vehicle.

Sramana Mitra: The technical talent that you tap into is trained where?

Amir Hever: Either in the university or companies they worked for. Also from the army where they bring a lot of knowledge from the things they’ve been working with. 

Sramana Mitra: Thank you for your time.

This segment is part 2 in the series : Thought Leaders in Artificial Intelligence: Amir Hever, CEO of UVEye
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