Most AI tools work the same way: you answer questions about injuries, treatment, and lost income, and the tool applies generic ranges.
That can be useful if you’re trying to understand categories like:
- medical costs
- wage loss
- out-of-pocket expenses
- non-economic impact (pain, limitations, daily life changes)
But in Mitchell, the parts that often swing a claim—what the truck company knew, what records exist, and whether symptoms match the crash—aren’t reliably captured by a questionnaire.
Common breakdowns include:
- Liability disputes after the initial crash narrative (especially when multiple vehicles were involved)
- Pre-existing conditions arguments that require medical record review, not guesswork
- Gaps in documentation when treatment pauses, changes providers, or evolves over time
- Truck-specific defenses tied to maintenance, logs, and compliance issues


