@tortus-ai/embed-client) lets your healthcare application embed TORTUS’ AI-powered medical consultations directly into your own workflow. You load TORTUS into a container on your page, start a consultation from a few lines of TypeScript, and receive structured medical outputs (notes, letters, codes, and transcriptions) back through events.
The SDK renders the TORTUS experience inside a sandboxed iframe, so your users never leave your application and patient data stays protected.
What you can build
Ambient consultations
Capture face-to-face or live-recorded consultations and turn them into structured clinical
documentation.
Audio file processing
Send an existing recording and receive notes, letters, and coded data in return.
Meeting notes
Capture non-patient conversations and generate meeting notes (early access).
Dictations
Let clinicians dictate directly into the embedded TORTUS experience.
Why the SDK
- Easy integration: async initialisation with a single
loadTortus()call. - Secure by design: short-lived launch tokens, iframe sandboxing, and built-in validation for patient data.
- Type-safe: full TypeScript definitions for every option, event, and result.
- Flexible: multiple consultation modes and EHR integrations, or bring your own host UI.
Start here
Quickstart
Go from zero to your first consultation in a few minutes.
Installation
Configure the registry and install the package.
How it works
Understand standby mode, events, and the client lifecycle.
API reference
Every method, option, and event in one place.
You’ll need credentials from TORTUS to use the SDK: a publishable key, and a client ID +
client secret for your backend. Contact support@tortus.ai if you
don’t have these yet.