This Indian Company is Quietly Building a Map More Powerful Than Google’s
When it comes to navigating to work, exploring a trending hotspot, or hunting for the best biryani in town, Google Maps is likely the first tool that comes to mind. However, what if there’s another player building the next-generation map stack for India—one that’s more precise, deeply insightful, and tailored to meet the country’s unique needs? Genesys International Corporation’s core offering is a map; but it’s not just any map. While a map is made up of multiple layers, the company’s solution goes far beyond what is typically seen on Google Maps. In an exclusive conversation with AIM, Sameer Sankhe, chief digital officer (CDO) of Genesys International Corporation, explained, “In addition to standard mapping data, we offer a highly accurate 3D replica with five-centimetre precision. While many talk about the metaverse in abstract terms, we have already created real-world digital twins of Indian cities.” Sankhe mentioned that the company also provides a comprehensive street-level view, similar to Google’s Street View, but on a much larger scale. Their street imagery spans 1.5 million kilometres, covering the top 1,500 towns in India. These images are proprietary and unique to them and no other company has access to the dataset. The power of this imagery lies in the different mapping layers it enables. For example, one such layer is the Digital Elevation Model (DEM), which has multiple applications. One practical use of DEM is in electric vehicle (EV) navigation. To accurately estimate an EV’s range from point A to point B, we must account for elevation changes along the journey, as inclines and declines affect battery discharge rates. DEM also becomes crucial for flood prediction. For instance, in Bengaluru, where flooding in low-lying areas is a recurring issue, the model can pinpoint the most vulnerable locations. “To generate such detailed maps, we have built India’s largest collection of sensors. We own and operate a diverse set of data collection tools, including vehicles, drones and aircraft equipped with light detection and ranging (LiDAR), and backpack-mounted LiDAR systems. Our ability to capture high-resolution data is unparalleled—we can map an entire city like Bengaluru in just a week, with a five-centimetre accuracy,” Sankhe said. He shared the example of one of Asia’s largest informal settlements, Dharavi,  which presents one of the most challenging mapping environments. The streets are so narrow that conventional mapping methods are ineffective. To overcome this, Genesys uses backpack-mounted LiDAR, a technology initially developed for mapping places like Venice. “But mapping is only the first step. Once we capture the data, we must store and process it, handling tens of petabytes of information. This requires advanced software and expertise built over decades. Simply investing money isn’t enough, it takes years of experience to master the entire workflow, from data collection to application development,” Sankhe noted. AI-Driven Mapping & Navigation Artificial intelligence (AI) has become an integral part of geospatial innovation. Sankhe mentioned that the Street View dataset covers over 1.5 million linear kilometres of road imagery, and their machine learning algorithms extract valuable insights from this vast pool of data. “By using AI, we can analyse, categorise, and enhance mapping information, making it more actionable for urban planning, navigation, and infrastructure management,” he said. One of the key applications of AI in geospatial data is sustainability analysis. AI-driven models can assess urban greenery by identifying types of tree, measuring widths of trunks, and estimating the potential for carbon capture. This information helps city planners and environmental agencies better understand urban ecosystems and develop green infrastructure strategies. Besides sustainability, AI plays a crucial role in infrastructure insights. Genesys models can automatically detect and classify various urban elements such as storefronts, stormwater drains, streetlights, and other features essential for city planning. By providing precise data on these aspects, AI helps in better zoning, traffic management, and utility planning. AI also transforms automobile navigation by enhancing in-car safety through natural language voice-based navigation systems. Instead of manually entering destinations, drivers can use voice commands for a more intuitive and distraction-free experience. Genesys’ large language model (LLM), trained on comprehensive map data, can process complex queries and provide accurate responses. For instance, if a user says, “Take me to the best mutton restaurant in Koramangala, Bengaluru,” without specifying a name, the AI will perhaps identify Champak, a restaurant renowned for its mutton dishes. Similarly, if a user requests, “Find a famous seafood place on my way,” the system could probably recognise Sea Meen Restaurant, a well-known seafood eatery, and create a route including a stop at the restaurant. “By combining machine learning with geospatial data, our AI-driven mapping and navigation solutions enhance sustainability, urban infrastructure planning, and the overall driving experience, making transportation and city management smarter and more efficient,” Sakhe said. More Data Means More Privacy Concerns The Indian government has historically maintained a strict policy regarding geospatial data due to concerns over its potential misuse. However, recognising the critical need for accurate mapping data, the Centre has now revised its approach. “The new Geospatial Policy is a significant step forward, striking a balance between security and accessibility. Under this policy, only Indian entities are permitted to map and own imagery with sub-one-metre accuracy. This ensures that highly detailed geographic data remains within the country while enabling its use for urban planning, defense, and various other applications. A key mandate is that this data never leaves India, ensuring national security and sovereignty over critical geospatial assets,” Sankhe explained. Before this policy was implemented, platforms like Google Earth had long provided satellite imagery. The Indian government carefully evaluated the advantages and risks associated with such data before formulating a policy that would allow for high-precision mapping while maintaining control over its distribution. What’s Lies in the Future? One such application is sustainability planning, which is a key focus for Genesys. Its technology can analyse the solar potential of an entire city, such as Varanasi, at the click of a button. This tool provides precise shadow profiling, allowing individual homeowners to determine the solar potential of their rooftops throughout the day. Such insights are crucial for optimising solar panel installations and maximising energy efficiency. Another practical use of its mapping technology is in fiber optic cable deployment. Many private sector players have embraced their high-accuracy maps to plan and lay fiber optic networks across India. Similarly, Genesys system aids in telecom infrastructure planning. For instance, it can simulate the placement of an 80-foot tower on a building and assess its network coverage. If the coverage is only 40%, a minor height adjustment, such as increasing it by one metre, could boost coverage to nearly 80–90%. Municipal corporations are also benefiting from this data. For example, the Brihanmumbai Municipal Corporation (BMC) has allocated ₹155 crore for mapping Mumbai, utilising Genesys technology for urban planning and infrastructure development. Its data helps the civic body plan road networks, ensuring that proposed roads do not inadvertently intersect with slum areas or permanent structures. This ability to analyse, simulate, and optimise environments with such precision makes Genesys valuable for both government and private sector stakeholders.
Genesys provides a comprehensive street-level view like Google’s Street View.
An Indian company is redefining digital mapping with ultra-precise, AI-powered technology that surpasses Google Maps in street-level detail, 3D modeling, and urban planning applications.
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