Many AI tools generate a quick range based on inputs like injury severity, age, and care needs. That can be useful as a starting point—but Mentor cases often involve details that aren’t captured well by broad software assumptions.
For example, in Northeast Ohio corridors with frequent merges, lane shifts, and weather-related slowdowns, spinal injuries may be tied to:
- Rear-end collisions where impact timing and vehicle speed are disputed
- Work-zone incidents where signage, traffic control, or compliance is questioned
- Multi-vehicle crashes where fault is shared or unclear
- Pedestrian or crosswalk events where injury mechanics matter
An AI estimate can’t independently verify accident reconstruction, driver behavior, medical causation, or the exact functional losses documented in your records. Those are the elements that tend to decide whether settlement talks progress—or stall.


