Many AI tools generate a range based on typical patterns. That can be useful for organizing questions, but it often misses key factors that matter locally, such as:
- How quickly symptoms were documented after a crash or slip incident in the Grovetown area
- Whether treatment continued consistently (interruptions can become an argument against severity)
- How work schedules and commuting disruptions translate into wage-loss evidence
- Whether the accident scene was documented before details fade—especially in busy traffic corridors where cameras and witnesses are time-sensitive
In other words, an AI output may look confident while relying on assumptions that don’t reflect your records.


