Praedicta turns predictive mapping research into machine-readable
infrastructure context. Applications, AI agents, mobility systems,
and digital twins can query physical-world context through a simple API.
Query Pittsburgh road infrastructure by geographic coordinate or
canonical road segment. The API returns structural characteristics,
validation scope, and, where available, a validated structural percentile.
Base URL: https://api.praedicta.ai
Coordinate Context
Resolve a geographic coordinate to the nearest actual Pittsburgh road segment.
Segment Context
Retrieve structural characteristics and validation metadata by segment ID.
Route Context
Evaluate structural context across a sequence of supplied route points.
The current Pittsburgh model is based on retrospective spatial
out-of-fold validation. Structural characteristics of the road network
contained information associated with where previously crash-free
road segments subsequently experienced crashes, including when
geographically separated areas were withheld from model training.
The production API resolves queries against 19,628 Pittsburgh road
segments. Structural percentile information is returned only where
the segment belongs to the validated zero-history cohort.
A null percentile means that validation information is unavailable;
it does not mean zero risk.
Responsible use
Praedicta Road Context API is a research-preview decision-support
interface. It does not provide calibrated crash probabilities,
safety certification, or safe/unsafe road classifications.
Structural context should be interpreted alongside appropriate
operational, engineering, traffic-exposure, and domain-specific evidence.
Build with Praedicta
We are exploring integrations with mobility systems, infrastructure
planning platforms, digital twins, AI agents, and Physical AI applications.