Scribend: 100% Offline Edge AI Medical Scribe

Scribend addresses the critical need for secure, automated medical documentation in clinical environments where cloud connectivity is inconsistent or data privacy is paramount. By leveraging an entirely on-device Edge AI architecture, Scribend transforms spoken doctor-patient interactions into structured clinical records without ever transmitting data to the cloud. The system utilizes a modular, multi-model pipeline optimized for the Qualcomm Snapdragon NPU: Transcription: We utilize Distil-Whisper Small for high-accuracy speech-to-text, augmented with an 80-term medical vocabulary hint to ensure precise capture of clinical terminology and phonetic typo correction. Context Retrieval: Using MiniLM vector embeddings and a local SQLite database, the system performs semantic searches on a patient’s historical records, providing the LLM with relevant medical context before note generation. Reasoning: Meta Llama 3.2 3B Instruct acts as the system’s "brain." It performs zero-shot speaker diarization to separate Doctor and Patient dialogue, applies contextual logic to identify medical facts, and outputs a perfectly structured JSON SOAP note. Formatting: Finally, the system automatically converts the JSON output into a polished, timestamped Markdown document, complete with tables, bold headers, and bullet points for instant clinical review. Designed specifically for modern mobile hardware like the Samsung Galaxy S25, Scribend achieves this performance with a sub-2.5GB memory footprint, proving that complex, context-aware AI is not only possible but efficient on edge devices