Hyperlocal startup Nextbillionai uses an AI-first approach to enable location-based experiences
Nextbillionai co-founders: Gaurav Bubna (left) and Ajay Bulusu
The capabilities of artificial intelligence (AI) are boosting enterprise efficiencies worldwide, but cost concerns and lack of customisation often act as barriers when it comes to large-scale adoption.
Enter Singapore-headquartered AI-powered startup , which aims to deliver a range of hyperlocal solutions beginning with the area of mapping and moving on to NLP, content moderation, and facial recognition.
Founded in 2020 by Ajay Bulusu, Gaurav Bubna, and Shaolin Zheng, Nextbillionai aims to be the global leader in AI-powered hyperlocal solutions and serve the unserved/underserved next billion users.
The three founders met while working at Grab, the Singapore-headquartered multinational ride-hailing company, and realised that there was much to be done with mapping technology.
“At Grab, we were leading the maps team and built the technology literally from the ground up. During this time, we realised that there were many other challenges and the problems were global,” Ajay says.
He says the fundamental problem was on the cost side as the use of third-party map technology such as Google Maps was progressively rising and “many companies could not afford it”.
Also, most companies providing mapping technology were targeting the retail consumer, not enterprise clients or businesses. For example, most maps provide information on distances taking a car into account and not a mini-truck.
Nextbillion AI is working on building geospatial infrastructure essential to enable location-based experiences for the next billion users.
The founders claim their AI solutions are aligned with hyperlocal nuances in emerging markets and developed markets, which is ideal for companies keen to expand on a global level. It targets customers in the logistics, ride hailing, fleet management, ecommerce, delivery, and autonomous driving industries.
The company, which has a 50-member team, has offices in Bengaluru and Hyderabad.
An AI-first approach
The founders of Nextbillionai felt that they could reimagine the entire mapping technology leveraging technologies like AI and machine learning and provide applications across geographies.
“We decided to build an AI-first company, starting with maps that could solve the needs of the next billion users,” Ajay says.
Given the penetration of internet across the world, especially in continents like Asia and Africa, a new set of users are coming into the picture. This is expected to lead to a higher demand for services like booking rides, delivery, transportation, and more. Maps technology will be vital to fulfil these demands.
Nextbillionai decided to work on an AI-driven mapping technology platform that would be open, easy to use, and highly customised for enterprises or businesses.
“Companies today generate a lot of data through various sources; we take certain components of this and apply our proprietary technology,” Ajay says.
Nextbillionai takes publicly available information on maps and combines it with specific information provided by a company to create a new platform. The AI platform creates a full-stack application programming interface (API) that helps clients to customise the entire mapping technology, based on specific requirements.
Nextbillionai co-founder Shaolin Zheng
How Nextbillionai differentiates itself
At present, in the mapping technology industry, most controls are with the provider. Nextbillionai is changing things by offering a high degree of customisation.
The three differentiators of Nextbillionai are customisation, control, and cost.
Ajay says the most important component of the platform is that the entire technology stack is open to give “more autonomy to our users.” The AI engine can take any location data from any customer, build a specific use case, and offer solutions.
“Most companies provide this technology on a DIY basis, but our API is highly modularised and customised,” he says. “This is a critical infrastructure platform for enterprises. Earlier, they never used their own data; they used somebody else’s.”
On customisation, Gaurav gives an example of a situation where the roads are narrow and certain vehicles cannot pass. A conventional map platform will probably not take this into account, but technology built by Nextbillionai will provides these insights based on customer data.
“We can solve for individual cases but will give control to our clients,” Gaurav says.
Ajay says the AI startup’s pricing “is competitive, and offers the whole ecosystem of APIs, customisation, and support”,
The founders of Nexbillionai say “the start has been good” and they have clients across eight countries, including Southeast Asia, Africa, and US.
“Today we are working with anybody who wants to move something,” Gaurav says.
Into the future
The startup unveiled its first product, Nextbillion Maps, around two months ago and has been engaged in pilot projects with companies in segments such as mobility, food delivery, ecommerce, logistics, and freight.
Gaurav says the one immediate impact many Nextbillionai customers have seen has been a reduction in costs, often up to 30 percent.
The team is extremely careful about data privacy, and has strict internal protocols in place so there is no breach of privacy.
Despite the startup launching operations during the time of COVID-19, it has successfully managed to deploy its solution at customer locations remotely.
“This indicates that we are building something good as many of our customers in the US have already started pilot projects,” Ajay says.
Nextbillionai follows the SaaS business model with a dynamic pricing structure. The co-founders did not reveal pricing, but said their prices are much lower than what a Google Maps or other mapping tech companies charge.
The startup notched up a Series A round of funding of $7 million, co-led by Lightspeed Venture Partners and Falcon Edge Capital.
As part of its future plans, Nextbillionai plans to expand its team, move into new markets, and focus on newer areas of technology application like natural language processing and facial recognition.
“We are building critical infrastructure for the long-term wellbeing of enterprises,” Ajay says.