Online tools tend to work the same way everywhere: you enter your diagnosis, injury date, treatment history, work limits, and wage information, and the tool returns a projected range.
For Eureka residents, the problem is that the inputs people commonly use aren’t always the inputs that matter most to insurers and adjusters. For example:
- Commute- or shift-related impacts may be described casually (“I can’t do my normal schedule”), but the record needs to translate that into medically supported work restrictions.
- Gaps in treatment—sometimes caused by difficulty getting timely appointments—can be interpreted as improvement or lack of severity.
- Wage entries may not reflect how your pay was actually structured (overtime patterns, shift differentials, variable hours), which can affect how lost earning capacity arguments are framed.
An AI tool can’t see those gaps the way a claims file review does. So the estimate can feel “reasonable” while still missing the evidence issues that change outcomes.


