SmartData · How it works
From field survey to your stack
Every layer in the SmartData portfolio is built the same full-stack way: a primary field survey, digitized into structured data, enriched with India-specific attributes, then delivered as either a licensed dataset or a self-serve API. That is why the portfolio is trustworthy at the point of use.
Get a demo →The four stages
One pipeline, every layer
Survey, digitize, enrich, deliver. The claims scroll on the left; on the right is what the pipeline hands a buyer at the end of it, a dataset delivery sheet.
Why the origin decides the trust
Most India geospatial data is only as good as where it came from. SmartData data is primary-survey origin: ground-surveyed, not scraped and not algorithmically inferred. Address points are surveyed at building level rather than guessed from a name string, and the India-specific attributes that global sets miss are recorded in the field, not approximated after the fact.
That single decision, to start from a survey, is what makes a layer trustworthy at the point you use it. Everything downstream, digitization, enrichment and delivery, preserves that ground truth rather than diluting it.
Primary field survey
The origin of every layer. Ground-surveyed data, captured in the field across India, so the record reflects what is actually there rather than what an inference predicts.
Digitization into structured layers
Field records are turned into clean, structured geospatial data: a road network classified into 11 classes, building-level geocodes, pincode and locality polygons, all aligned to a consistent PAN India model.
India-specific enrichment
The attributes global sets lack are layered on: posted speed limits, locality hierarchies, truck entry and exit timings, a FASTag-aligned toll matrix, daily fuel prices and footfall. This is the depth that makes the data usable for India decisions.
Delivery on two surfaces
The same ground truth reaches you two ways: as a licensed dataset delivered to your platform or enterprise, or as a self-serve API on leptonmaps.com with a free tier, playground and console. The sheet alongside is what the licensed surface hands over: layers with counts, schema, accuracy, projection and refresh dates.
Full-stack, end to end
SmartData owns every step from the field to your endpoint: survey, digitization, enrichment, licensing and self-serve APIs. Nothing in the chain is outsourced to a source we cannot vouch for, which is why the same data can hold up under the world's leading mapping platforms and inside a startup's first integration.
Because the pipeline is one system, a layer can be licensed as a bulk dataset or metered call by call through the API, without changing what was surveyed underneath.
Layers accuracy quoted CE90 against survey control
| Layer | Geometry | Features | Attrs | Cadence | Accuracy | Refreshed |
|---|---|---|---|---|---|---|
| road_network | line | 8,942,600 | 41 | monthly | ±3.5 m | 2026-07-28 |
| building_footprints | polygon | 24,618,000 | 12 | quarterly | ±2.0 m | 2026-07-11 |
| poi | point | 6,113,400 | 23 | monthly | ±5.0 m | 2026-07-30 |
| admin_boundaries | polygon | 7,416 | 9 | on notification | 1:50,000 | 2026-06-19 |
| pincode_boundaries | polygon | 19,300 | 6 | half-yearly | 1:50,000 | 2026-05-02 |
| landuse | polygon | 1,499,284 | 8 | yearly | 10 m raster | 2026-03-15 |
| bundle | 41,200,000 |
Attribute schema road_network · 8 of 41 fields
| Field | Type | Populated |
|---|---|---|
| road_class | varchar(24) | 100% |
| name_en | varchar(120) | 87.2% |
| name_lang | varchar(120) | 71.4% |
| speed_kmph | smallint | 64.8% |
| lane_count | smallint | 58.1% |
| surface | enum(4) | 92.6% |
| oneway | bool | 100% |
| toll | bool | 100% |
Coverage by state top six by road km, of 36
| State / UT | Road km | POI | Buildings | Refreshed |
|---|---|---|---|---|
| Uttar Pradesh | 517,640 | 731,900 | 88.6% | 2026-07-24 |
| Maharashtra | 448,120 | 782,400 | 94.1% | 2026-07-28 |
| Karnataka | 314,220 | 604,150 | 95.0% | 2026-07-28 |
| Tamil Nadu | 271,480 | 592,300 | 96.3% | 2026-07-26 |
| Gujarat | 226,940 | 438,700 | 93.2% | 2026-07-21 |
| Delhi NCT | 33,180 | 401,220 | 98.4% | 2026-07-30 |
| 30 further states / UTs | 3,048,420 | 2,562,730 | 81.7% | rolling |
| all India | 4,860,000 | 6,113,400 |
Freshness
How the data stays current
A survey is only the start. The portfolio is kept current on an annual refresh, and the layers that move fastest are refreshed in real time or daily. Infrastructure rolls continuously, road closures stream live, fuel is daily, and India's first real-time transit feeds run under the mobility layers.
When a base layer carries an older vintage, the refresh narrative, not a static snapshot, is what you are actually buying.
What you can trial
You do not have to take the pipeline on faith
The output of the pipeline is testable before you commit. The SmartData APIs on leptonmaps.com run a free tier with a playground and console, so toll, route and detection calls are self-serve from day one. Start with one layer, validate it against your own ground reality, then expand into the datasets or bundles your use case needs.
- 01
One origin, two surfaces
The same surveyed layer is available as a licensed dataset or a metered API, so the way you consume it never compromises what was captured underneath.
- 02
Depth, not just coverage
India-specific attributes are enriched in, not inferred, which is why the data answers India questions that global sets leave thin or wrong.
- 03
Current by design
Annual refresh portfolio-wide, with real-time and daily layers where freshness matters most, so the record keeps pace with the ground.
Proof
The same pipeline runs at national scale
The survey-first pipeline is not a small-scale claim. It has carried public-sector infrastructure work across the country, with Railtel and NIC, and the world's leading mapping platforms license India data built this way from Lepton.
See the pipeline behind the layer you need.
Tell us the dataset or API you are evaluating. We will walk you through how it is surveyed, refreshed and delivered into your stack.
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