AI-based tools can be useful as a starting point because they tend to organize potential losses into buckets—like medical bills, lost income, and the impact of pain or impairment.
However, for an Amsterdam-area resident, the bigger problem is what AI usually can’t see:
- The medical record details that show what was known at the time and what should have happened next
- Causation evidence (the “but for” link between the mistake and the harm)
- Documentation gaps that often exist when patients are transferred between providers, seen in urgent care, or follow up late
- New York-specific litigation realities, including how claims are supported and challenged
A calculator can’t assess whether a provider’s conduct matched the standard of care for the circumstances in that timeframe—or whether the injury would have occurred anyway.


