Most AI tools work like a rough estimator: you enter details, it applies general patterns, and it produces a number. In real Ammon cases, that number can swing widely depending on evidence availability.
For example, many serious motorcycle collisions in the area involve:
- Drivers turning across lanes at intersections or when entering/exiting busy roadways
- Late braking or lane changes in heavy traffic periods
- Roadway visibility issues (lighting, traffic flow, or weather conditions)
When an insurer believes liability is unclear, it may discount the claim—even if injuries are serious. That’s why the “calculator output” should be treated as a hypothesis, not a valuation.
In practice, the details that tend to move cases forward include:
- Crash photos and short video (if you have them)
- Eyewitness statements (especially from people who saw the turn/lane change)
- Consistent medical records that match the crash timeline
- Documentation of how your injuries affect daily functioning


