Generic AI models struggle with veterinary SOAP notes because of dense abbreviations, species-specific terminology, and inconsistent documentation styles.
Purpose-built models trained on vet billing data understand that "SQ fluids" means subcutaneous fluid therapy, that "CBC/Chem" is a lab panel, and that "N/T" often means nail trim.
Confidence scoring helps billing staff prioritize high-certainty flags, reducing review time while maintaining accuracy.