
Collect road data.
Timestamps, location context, labels and data review. Collection permissions and data rights come first.
Right Field SDKOur engineering core: helping machines understand Indian roads.


Timestamps, location context, labels and data review. Collection permissions and data rights come first.
Right Field SDK
Calibration, synchronisation and perception interfaces, with GPU processing at the core.
Sensor Fusion SDK
An interface for road connections, restrictions and changing conditions.
RoadGraph SDK
A toolkit for sensor replay and repeatable evaluation before controlled trials.
Scenario SDK
A runtime for deployment, latency, power and system-health monitoring. Hardware support is to be defined.
Edge Runtime SDK
We’re working on the road data and computing foundations that future general-purpose intelligence will need.
Development timeline
Cameras, sensors and GPU integration.
Discuss integration
Road-data collection across India.
Share road data
Perception, simulation and joint research.
Discuss researchReviewed
Sensor fusion combines measurements from several sensors into a shared view. In a vehicle, this can help estimate where road users are and how they move. Read the sensor fusion guide.
Link to answerOnboard computing processes sensor inputs close to where they are captured. Our work includes running perception models and measuring latency, power use and system health. See Edge Runtime SDK.
Link to answerIndian roads include mixed traffic and varied road layouts. Local data helps test systems against those conditions. The India Driving Dataset documents these challenges.
Link to answerOur development path includes recorded-data replay, simulation, hardware integration and controlled-site trials. We have not published validated road-autonomy results. Read about self-driving in India.
Link to answer