Aleph Hackathon

OIRA is a local AI clinical documentation assistant that turns doctor patient conversations into structured, professional medical notes without sending sensitive patient data to the cloud.

During a consultation, OIRA captures and processes the conversation locally, transforms speech into structured clinical information, and drafts a ready to review clinical note. Physicians can review, edit, and approve the generated documentation while OIRA highlights unclear or potentially missing information instead of silently inventing details.

OIRA is designed around a simple problem we heard directly from doctors: clinical documentation takes time away from the patient. Existing workflows often require physicians to manually type, organize, and rewrite information after or during an encounter. OIRA aims to reduce that administrative burden while keeping the physician in control.

The project uses QVAC as its local AI inference layer, combining local speech processing, information extraction, and structured document generation. The entire workflow is designed around privacy first processing, making it possible to work with highly sensitive clinical conversations without relying on a cloud AI API.

The goal is not to replace clinical judgment. OIRA handles the documentation work so physicians can focus on the patient.

Lear more at https://oira.doctor

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Made by Diego Diaz Montero, Justin Vargas Rodriguez, Abraham and Antonio zhang