AI Medical Scribe

The pipeline has three stages. Speech recognition turns the conversation into text and separates who said what. A large language model then extracts the clinically relevant parts (complaint, history, examination findings, assessment, plan) and writes them in the template the clinic uses, leaving out small talk. Finally the doctor reviews the draft, corrects anything wrong, and signs it into the electronic medical record. The scribe never makes a diagnosis and never files a note on its own; it removes typing time, not clinical judgment.

Arabic clinics are harder than English ones for two reasons. The consultation happens in dialect (Najdi, Hejazi, Emirati, Egyptian), while medical terms are usually said in English inside the Arabic sentence, so the system must handle code-switching and dialect speech recognition at the same time. The note itself is often expected in English or in a mixed format, which means the scribe translates as it summarises. Market research in 2026 found that none of the twenty AI vendors audited in the region offered an Arabic medical scribe, so most of the products a clinic will see were tuned on English recordings.

Before buying, ask a vendor four things: how the patient's consent to recording is captured and stored, where the audio and notes are processed (Saudi PDPL and UAE PDPL both treat health data as sensitive), how the model was tested on your dialect, and how the note reaches your clinic system. Nano AI builds the Arabic medical scribe as an implementation project with data handling aligned to Saudi PDPL, UAE PDPL and GDPR, evaluates it against dialect golden sets before go-live, and connects the output to the clinic system through its API.