AI tools typically build a value range using simplified inputs—injury severity, age, and broad categories of damages. That can be a starting point, but it often fails at the parts that make the biggest difference in real spinal cord cases:
- Local medical proof vs. assumptions. Your neurologic level, complications, and functional limits must be documented—not guessed.
- Causation details. In Vernal, incidents may involve rural roadways, shift work schedules, or jobsite safety issues. If the timeline of symptoms doesn’t clearly connect to the incident, insurers push back.
- What future care actually looks like. Settlement value often turns on a life-care plan that reflects your expected needs—not just what an algorithm thinks people “usually” need.
If you’ve been given a number by an AI tool, it should be treated like a worksheet, not a prediction.


