SmartData · Use cases
What teams build on India ground truth
Teams do not buy a map, they make a decision: cost a route, pick a site, ship navigation, reach a village. Each use case below starts from a real India decision and shows which primary-surveyed layers answer it, all from one portfolio of 28 datasets.
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Start from the decision, not the dataset
The portfolio is 28 datasets across 7 categories, but no one buys a dataset to own a dataset. They buy it to answer a question that global data gets wrong or leaves empty for India: where the toll points sit, who lives below the census line, what the speed limit really is, how to reach a village by name. The four use cases here are the recurring India decisions that the primary-surveyed portfolio was built to settle.
The four decisions
One portfolio, four India decisions
- 01
Route costing that knows India tolls and fuel
"We need toll and fuel-aware route costing, not straight-line estimates." Cost a route on the real network, not a guess: the road graph, toll points, daily fuel and truck timings that India runs on. Layers: Road Network 59,35,048 km, 1,780 toll points, daily fuel, Toll + Routes APIs.
Logistics - 02
Micro-market decisions, below the census
"Census-level data is too coarse for micro-market decisions." Pick a site, draw a catchment and read who lives and moves there, at a resolution census tables cannot reach. Layers: Populace+ 6,41,731 villages, footfall 100m urban grids, Catchment + Nearby APIs.
Retail and BFSI - 03
Navigation data that works on Indian roads
"Global datasets are wrong or empty for India: speed limits, addresses." Ground-surveyed navigation content for OEM and ADAS stacks: roads, speed limits, building-level geocodes and ADAS-ready closures. Layers: Speed limits, CIFS road closures, 3D buildings 922 cities, 2.17 Cr address points.
Automotive and ADAS - 04
Down to the village, across all of India
"India addresses are locality-centric; our geocoding fails." Reach every administrative tier and every village, the coverage smart-city, land-records and rural programs need. Layers: 36 states, 784 districts, 7,006 tehsils, 6,41,731 villages, IndiaPin 19,538 polygons.
Rural and government
What every use case shares
One source, not four stitched feeds
Each decision reads from the same primary-surveyed portfolio, refreshed annually, not from four datasets stitched together from different origins. That is the difference between data that agrees with itself and data that contradicts itself the moment you cross a use case. Route costing, catchment, navigation and coverage all sit on one India.
Proof
Surveyed at national scale
The same ground-survey discipline behind these decisions runs at national scale. Railtel and NIC relied on it for a 40,000+ km NOFN infrastructure survey and the enhancement of 4,08,563 sq km of mapping to 1:10,000, and the platform now serves teams worldwide from a self-serve free tier.
Proof points: Railtel, NIC, 700+ customers, 10M+ API hits, NASSCOM Top 5, self-serve free tier.
Bring your India decision.
Tell us the decision you are trying to make on India and we will show you the layers and APIs that answer it.
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