Sina — Bilingual Clinical Intake Voice Agent

Created by team Codeswitch on September 30, 2026

Patients don't speak in one language on demand. Across Oman and the wider Gulf, an intake conversation moves between Arabic and English mid-sentence — a symptom in English, a history in Arabic, sometimes both in the same breath. Most voice tools force a choice. Sina doesn't. Sina is a real-time bilingual voice agent for clinical intake. A patient speaks in Arabic, English, or a mix, and Sina transcribes with AssemblyAI's streaming API in Medical Mode, extracts a structured summary (symptoms, medications, allergies, duration, severity), replies in a native Omani Arabic voice or an English voice, and escalates to a human interpreter when needed. The model doesn't get the final word on safety. A reviewed list of red-flag symptoms — chest pain, breathing difficulty, stroke signs, severe bleeding, seizure — is matched against the raw transcript in plain Python, not the model's paraphrase. If the LLM misjudges a chest-pain case as low-urgency, this layer overrides it anyway; it can only add an escalation, never remove one. Escalation doesn't cut the conversation short. It fires as a one-time banner while the conversation keeps going and asks its normal follow-ups, handing off only once intake is complete. The bilingual experience goes beyond the AI's replies. A first-load popup lets the patient choose Arabic or English, translating the whole interface with right-to-left rendering. Languages can switch mid-conversation without losing anything gathered, and low-confidence transcriptions get a real yes/no instead of a silent guess. Real-voice testing drove the hardest decisions: code-switching garbled transcription on ambiguous audio, so Sina pins one language per session; and ElevenLabs had no free Arabic voice, so Arabic speech runs on Azure's native Omani voice instead. Sina doesn't diagnose or replace emergency care — it exists so clinicians get accurate information regardless of language, and nothing urgent slips through on false AI confidence.

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