After an injury, it’s common to face immediate pressure—medical bills, missed shifts, and the uncertainty of whether restrictions will keep you out of work. Online tools can look like a shortcut to clarity.
An AI-based estimate typically tries to model settlement outcomes from other files by taking your inputs (injury type, treatment history, missed time, and sometimes wage info) and producing a range.
The problem is that Dunwoody claims often involve real-world factors that don’t fit neatly into an online form—like:
- Conflicting timelines (symptoms that worsened after the first few days)
- Work status changes tied to restrictions and modified duty
- Documentation gaps when treatment pauses or records don’t connect the dots
- Wage complexity for workers who rely on overtime or variable schedules
When those details aren’t captured accurately, an AI output can feel “reasonable” while still being unreliable.


