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Tarek and Andrew Kabrit, co-founders, Seez
The AI-powered Seez app is all set to change the way you buy cars
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By Sindhu Hariharan
e’ve all been there: asking for recommendations from social circles, relying on online classifieds, and visiting numerous showrooms before we zero down on a car to buy. In fact, according to Tarek Kabrit, the co-founder and CEO of tech startup Seez, people spend an average of 17 hours in this process, and he believes that as our cities get smarter, our efforts to buy a car should evolve positively as well. Seez is an app that helps you search, shortlist, and negotiate deals on a car of your choice- but it isn’t just another cars marketplace.
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Entrepreneur september 2017
Seez is more like Shazam for cars- if you spot the make/ model of a car you’d like to own on the roads, click an image of it on the app, and its machine learning and artificial intelligence capabilities will find out someone around you who’s selling it, assess its fair market value for you, and its personal car buying concierge chat bot Cesar will also aid the negotiation process. So, how did Seez come into being? “We were walking on the street in Beirut, and saw a Mini Cooper we liked, so we started checking it out and wondering how much a car like that would cost… While we were peeking into the car, the owner came by and we chatted with him, [and it] turned out the car was actually for sale,” Kabrit remembers. This got him thinking about a technology that could help enable transactions of a similar nature. “Cars are usually the second most expensive things people buy, and to have such inefficiencies in the process doesn’t make sense,” he says. Seez was founded in 2015 by Tarek and Andrew Kabrit, and the app launched with two key features- a machine learning enabled search engine feature that provides information on cars with images as input, and other, a marketplace model wherein people can list their cars with Seez to receive bids and offers from potential buyers. Given that any enterprise with a search engine model needs critical mass before chasing monetization, Kabrit says the Seez team is currently focusing on two key thingsproving that the service can be monetized, and building a product that solves a real problem for users. The startup, however, has planned for various revenue streams to tap in the near future, including a freemium model for users “seezing” cars, and charging sellers a fee to connect with
prospects, among others. “Over the past year, we added two new features that had a great reception with our users,” Kabrit says. “The first is a price estimator to find the value of any car, and the second is location-based contextual marketing. We realized that one of the problems for buyers or sellers is connecting logistically, and finding a time that works for both to meet and check out the car. So, we introduced the ParkCar feature, which allows buyers to park the car they are interested in, and next time they drive into a mall or a complex, they get a notification telling them that there are 2-3 cars similar to the ones they want at the mall at that point that are for sale.” As the region welcomes a new generation of car buyers open to new models and ways of buying, Kabrit believes such a trend has been met with an equal evolution in marketplaces. As companies like SellAnyCar, Dubizzle, CarSwitch, and others are addressing the need by coming up with value-added services, Kabrit stresses that he doesn’t see Seez fighting for a piece of the marketplace pie. “We see ourselves as a pure tech company, where we use AI and machine learning in almost all of our features- image recognition, price predictor, and chatbot. We obviously augment the AI systems with manual/human work to ensure a seamless experience for our users, but with time, we aim to fully automate the search process for buyers.” But are the region’s consumers ready to make one of their major investments relying on a niche tech with high novelty factor? Kabrit believes so. “Initially, Seez might be a niche solution, but over time, we definitely see it as more of a mass market solution,” he says. “At this stage, it is free and not mutually exclusive, so there is very little opportunity cost to try it in parallel with your manual