Many AI tools generate a range based on simplified inputs (injury severity, age, and a few assumptions). In Quincy, the facts of how a crash or workplace incident happened often matter just as much as the diagnosis.
For example, injuries that occur in:
- Winter weather collisions near busy commuting routes
- Intersection crashes where turning vehicles and sudden braking are common
- Construction and industrial settings with falls, equipment impacts, or unsafe access
…can produce different liability theories and different proof hurdles. If the tool doesn’t “know” your actual mechanism of injury and the strength of the evidence, the number it outputs may not reflect what a Quincy insurer would realistically pay.


