Reading Time: 5 minutes

Nextbillion.ai is slowly revolutionising the way that companies build, scale, and manage their own mapping systems. The Singaporean start-up has developed an AI-powered spatial data platform that helps enterprises build, scale, and manage their own mapping ecosystems.

The idea behind NextBillion.ai was formulated when we realised that one map doesn’t fit all and that the future of geospatial is decentralisation,” says co-founder Ajay Bulusu. “Our team comes from Grab, Google, Waymo, and many other transportation and mapping companies.”

In fact, Bulusu and fellow co-founders Shaolin Zheng and Gaurav Bubna were all part of the senior management team at Grab before starting Nextbillion.ai early last year.

Ajay Bulusu
Ajay Bulusu.

“In terms of the problem we’re trying to solve, NextBillion.ai is a mapping platform for enterprises. Maps were always built for billions of end-users like us, but not for the millions of enterprises like the consumer companies we work with. We are bridging this gap by building a new era in the mapping ecosystem to help enterprises succeed better with targeted, customisable, scalable solutions.”

NextBillion.ai’s one-of-its-kind mapping solution has solved the underlying mapping issues that many enterprises face. For example, it allows for hyper-local nuances and provides tailor-made solutions for specific business needs, based on company data and geography.

“We use OpenStreetMap to power our solutions, which are supported by proprietary APIs and our ability to seamlessly merge first- and third-party data – the result is relevant, fresh, enterprise-grade custom maps,” explains Bulusu.

“NextBillion.ai’s unique ability to combine the ease of use, low cost, and customisability of open-source solutions with the high performance and quality of proprietary solutions. This sets us apart from the competition.

“As a unified geospatial platform, we cater to the needs of any organisation that requires mapping services, like those in on-demand delivery such as food and grocery delivery, e-commerce logistics, courier services, ride-hailing, automotive OEMs, navigation software, route optimisation, fleet management, emergency services, government, micro-mobility, and long-haul trucking,” he adds.

Nextbillion Custom Stack

Mapping has become significantly more important to businesses thanks to the shifting mobility landscape. Bulusu thinks that Nextbillion.ai has a crucial role in supporting the mobility businesses of tomorrow.

“In the current environment, there has been a tremendous uptick in customer demand for last-mile delivery services,” he explains.

“This presents a large opportunity for these organisations and their logistics partners to accelerate growth and get ahead of the competition — if they can rise up to the challenge. NextBillion.ai helps them do just that, with focused, purpose-built solutions that account for the intricacies of the market, environment, and context they operate in. We understand the need for customisability. A mapping solution for Jakarta won’t hold good in Mumbai. An on-demand delivery solution won’t work for the freight industry. Enterprises struggle with solving these issues, as mapping technology is complex.

“NextBillion.ai is the first mapping solution to truly solve this,” he continues. “Our solution offers the most accurate ETAs, precise pick and drop locations, and the best routes for any given use case and vehicle type. Relative to our competitors, we have seen up to 50% better accuracy and 10x higher scalability at a fraction of the cost.”

Nextbillion.ai’s hyper-local solution is helping streamline operations for logistics companies, as well as food and grocery delivery platforms.

“Every region has differing trucking laws, various vehicle types that drive in different ways, malls and warehouses have multiple entry/exit points, apartment complexes have confusing layouts, and each organisation has specific operational rules for fleet behaviour,” Bulusu explains. “In addition to addressing the above, we apply AI to learn local traffic and weather conditions, unstructured addresses, and unique driving behaviours to build custom map APIs for every use case.

“This means that our customers are always equipped with the most relevant and up-to-date geospatial information to enhance their operations. Highly precise ETA and distance predictions, automated routing, real-time updated navigation — whatever they need to keep their fleets operating at maximum speed and efficiency, we can provide.”

However, Nextbillion.ai still has a big role to play in the ride-hailing sector.

“One of the first things we do in our engagements with ride-hailing companies is to mine their historical trip data and run it through our AI systems,” says Bulusu. “This helps us understand where deficiencies lie and how to address them.”

“For instance, we can analyse behaviour patterns for better AI-driven route and ETA predictions and refine distance and ETA calculations with our high-precision Distance Matrix API. We can also identify and solve for blind spots in existing operations with custom map stacks and enable client teams to make real-time changes as per hyper-local nuances like serviceability conditions.”

“We did exactly this for one of our ride-hailing clients and were able to meet their business needs by increasing fare accuracy by 12%, reducing operating costs by 60%, and improving ETA accuracy by 8%.”

Intelligent mapping will also play a big role in bringing driverless cars to our roads and Nextbillion.ai is promising that its maps will lead to big improvements from the status quo.

“Autonomous vehicles need a lot more customisable map data, routing, dispatch, fleet management, incorporating local regulations and other capabilities, which are just not possible to support on today’s platforms,” says Bulusu.

With the increasing adoption of autonomous, electric, and connected vehicles, Bulusu says these problems will only be exacerbated.

“NextBillion.ai’s mapping platform can be seamlessly extended to support all of these use cases. We are already working with mobility companies that are making a shift to electric, connected, and shared mobility. Autonomous is a natural extension.”

“Historically, maps were thought of as an esoteric thing, which only governments, defence, maybe old-school industries like utilities and telcos, and at best, some automotive companies were using. They were never seen as ‘mainstream’ like other technology areas such as Artificial Intelligence,” explains Bulusu.

“B going forward, we think maps and location will become a critical component of a wide range of everyday use cases, and adoption of mapping tech will become pervasive across businesses of all shapes and sizes. Every business will have resources dedicated to ‘location’ in their technology departments”.

If Bulusu’s predictions ring true, then the future certainly looks exciting for NextBillion.ai. “We’re responsible for creating a whole new market segment in Map Data Management as a Service (MDaaS). NextBillion.ai offers turnkey map data solutions that collect, curate, and maintain location data specific to any given organisation’s use case(s), and this will be a large part of our focus for the near future.”

“It’s an exciting offering,” Bulusu continues. “We can seamlessly merge third-party and proprietary data, enabling easy management of custom data layers. Our flexible update cycles and dedicated support ensure that the maps stay fresh and accurate, and the ability to gather data on pedestrians, motorbikes, cars, trucks, and public transit, across developing and developed markets, maximises relevance to the use case. To keep updates quick, accurate, and cost-effective, our proprietary AI works with satellite and street imagery as well as GPS probes.

“Before us, enterprises had no easy way to efficiently achieve all of this.”

Leave a Comment