Technology
A decision-intelligence layer for mission risk.
4autonomy turns environmental, road, and vehicle data into an explainable, mission-level decision. Here is how the pieces fit together, without the buzzwords.
Architecture
From data to recommendation
Global data
- Weather
- Radar
- Satellite
- Terrain
- Traffic
Local G-Data
- LiDAR / point cloud
- Road geometry & slope
- Road surface
- Imagery
- Temperature & humidity
- Infrastructure & temporal change
Vehicle / mission model
- Dimensions & weight
- Stability limits
- Cargo
- Battery / thermal limits
- Sensor limitations
- ODD & operational rules
Pipeline
Five stages, one decision
Data sources
Global environmental and traffic data, plus hyperlocal G-Data observations.
Environmental / physical-world intelligence
Hazards resolved along the route and departure window.
Vehicle + mission model
Conditions evaluated against the vehicle, cargo, and operational rules.
Risk engine
Mission risk scored and attributed to specific, explainable factors.
Recommendation / API
GO / REROUTE / DELAY / AVOID and alternatives, delivered via API.
Integrates with your stack
Sits alongside routing, dispatch, autonomy, and simulation systems.
Methodology
Built to be explainable and validated
We prioritize outputs that operations and safety teams can inspect and trust, and we validate on real data before making production claims.
Explainable by design
Risk is attributed to specific hazards and vehicle factors, not a black box score.
Vehicle-specific
Evaluations respect the physical characteristics and limits of each asset.
Pilot-validated
Methodology is tested against your routes and, where available, historical incidents.
Research publications and benchmark results will be linked here as they become available.
Evaluate the technology on your data.
The clearest way to assess the risk engine is a pilot on your real routes.