Home PublicationsData Innovators 5 Q’s for Gaurav Bubna, Co-founder of NextBillion.ai

5 Q’s for Gaurav Bubna, Co-founder of NextBillion.ai

by Morgan Stevens

The Center for Data Innovation spoke with Gaurav Bubna, co-founder of NextBillion.ai, a location technology company based in Singapore. Bubna explained how location services differ across industries and discussed the future of transportation technologies.

Morgan Stevens: What challenges does NextBillion.ai solve with its location technology?

Gaurav Bubna: We started the company with this belief that location technology is becoming increasingly important for a variety of industries, including transportation, logistics, smart cities, mobility, and more. However, the current solutions are more like one size fits all, even though each industry, each company, and each vertical may have different needs in different geographies. We wanted to differentiate our approach from the conventional approach taken by other vendors in the market. We’ve built this in a way that can handle all the unique customizations and challenges that come with each industry’s verticals and region. To give a concrete example, if you’re in the United States and transporting things on different types of trucks, Google Maps does not work because trucking has its own regulations. Similarly, if you transport something with a waste management truck, they can only approach things from a curbside because of their robotic arms. Each scenario is unique, and our platform is built to support that. It allows companies to be more efficient with their assets and lower operating costs.

Stevens: NextBillion.ai offers solutions for a variety of organizations, including last-mile grocery delivery, non-medical emergency transportation, and pest control. How does NextBillion.ai tailor its solutions to meet the needs of companies across various industries?

Bubna: We take a Lego block approach instead of offering a standalone product. The way we tailor our solutions to different industries is by putting these Lego blocks together to better fit their needs. For example, a non-emergency medical transportation company might need something different than an on-demand public transit company who might need something different than a waste management company. We take 10 to 20 building blocks and fine tune it to solve the unique challenges of each vertical. We find our customers resonate with this and often see scenarios where they have tried other vendors and haven’t found a good solution. This approach of Lego blocks tends to solve problems pretty well.

Stevens: How is NextBillion.ai preparing for advances in transportation technologies, such as autonomous vehicles or drones?

Bubna: When we started the company, we wanted to tackle the challenges of autonomous transportation and deliveries. Autonomous drones, cars, and trucks each have their own challenges, such as complying with safety regulations. It’s one thing to deploy these on the road and make it work well in a test environment. But, if you want to make them work at scale and cities have imposed regulations, you have to be extra careful with safety aspects. There are unique aspects around maps and routing behavior that our platform is pretty well designed to handle. This is an area where our platform, with a customer-focused approach, can handle local regulations and safety aspects.

Stevens: What are the biggest challenges to automating location services?

Bubna: One of the biggest challenges in location technologies is data. We’re representing the physical world in a digital manner. It is often a very expensive affair because you’re trying to keep it fresh with all the changes that are going on in the real world. There’s been a lot of effort at an industry-wide level to see how we can use things like machine learning, satellite imagery, and data from sensors. The recent wave of machine learning and AI has really helped automate and bring down the costs of these efforts. It’s a pretty challenging problem but this is another reason why we also take an AI-first approach to advancing the quality of our services. AI is going to help and improve the automation of location services.

Stevens: How do you expect the geospatial data ecosystem to evolve in the next five to ten years?

Bubna: GPS and smartphones led to the creation of things like Google Maps and Uber and introduced a completely new set of experiences for customers and businesses. We think the next 10 years or so will end with people again getting used to the Ubers and DoorDashes of the world in their everyday lives. They’re going to expect similar experiences in all aspects of consumer apps. This means that there will be a huge explosion in the use of location technologies. It also means that businesses will need better ways to incorporate location technologies in a manner that’s very easy to use. For example, if a shipping company wants to use location in a better way, that will mean something different than a city that wants to manage autonomous vehicles and traffic. We hope to play a role in giving people tools, picks, and shovels and say this is how you can use this well and incorporate them into your business and applications easily.

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