AI calculators typically work by asking for broad inputs (injury type, treatment length, medical bills, and similar factors) and then generating a typical range.
In Pittsburgh, those ranges can be misleading because the underlying liability story is frequently evidence-driven. For example:
- Bridge and tunnel approaches can create disputes about speed, lane control, and braking distance.
- Steel-city intersections and turning lanes can lead to disagreements over who had the right of way.
- Hills, grades, and slick conditions can affect whether insurers argue the driver “couldn’t have avoided” the collision.
- Downtown traffic volume can complicate witness identification and video availability.
A tool may suggest a value, but it can’t review the crash report narrative, available traffic/road footage, or the medical timeline in a way that holds up against an aggressive adjuster.


