This talk will the integration of BERT models and advanced audio extraction techniques to for clinical note generation in EMS and explore the challenges of audio data capture in the field. By leveraging domain-specific adaptations we can enhance the accuracy of real-time transcriptions amidst the chaotic environment of ambulances. The presentation will address the unique challenges faced in EMS, such as background noise and speaker differentiation, and demonstrate how AI-powered solutions can streamline documentation, reduce cognitive load on paramedics, and improve patient care through precise and timely medical records.