← ALL WORK

PRODUCT ARCHITECTURE

Clara Care.

AI-powered healthcare application platform

MY ROLESolution architecture and hands-on engineering across web, extension, mobile and ML services
STATUSTeam-built product
STACKAWS · React · Gemini Live · PyTorch · SpeechBrain · SwiftUI · Chrome extension · S2 streams
FIELD NOTE / 01

See the system in motion.

Architecture walkthrough · 00:10

SBV / CLARA CAREARCHITECTURE WALKTHROUGH
WHAT THIS SHOWS

The application, backend authority, ephemeral AI access and event stream form a documented live interaction path.

SOURCE / LIMIT

Illustrative sequence based on technical documentation; it is not patient data or product footage.

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FROM THE SOURCE

A closer look at Clara Care.

01 ORIGINAL VISUAL

01 / Clinical workflow in contextClara Care public site · product screenshot

The public Clara Care site shows its recording and transcription widget beside a clinical form. The visible sample fields belong to the published demonstration; this is team-built product work.

CLARA CARE / 01 OF 01
Public Clara Care product screenshot showing a clinical form beside the recording and transcription widget with sample information.

Clinical workflow in context

The public Clara Care site shows its recording and transcription widget beside a clinical form. The visible sample fields belong to the published demonstration; this is team-built product work.

SYSTEM MODELSELECT A COMPONENT TO EXPLORE →
SELECTED COMPONENTApplication / widget

React interface for live consultation workflows.

01 / THE PROBLEM

Live clinical sessions cross four trust boundaries.

A clinical session touches application state, user identity, a live AI conversation and external services at the same time. If the boundaries between them are vague, sensitive data ends up where it shouldn't.

02 / THE APPROACH

The backend owns identity. The browser borrows access.

I lead the solution architecture within the team: API and service boundaries, AWS integration, persistence, session design and AI data flows. The consultation widget asks the backend for a short-lived token and uses it to connect to Gemini Live and to an event stream that sends analysis updates back. I also built the product surfaces that bring Clara into the clinic: a widget embedded in the clinic's own EMR that listens to the consultation and fills the existing form, a Chrome extension with a side panel, the clinician platform, and a native SwiftUI prototype for iPhone. Live session state is synchronized through S2 streams. Underneath runs a real-time speaker identification service: voice activity detection, ECAPA-TDNN voice embeddings and online clustering tell the clinical record who is speaking, while voiceprints stay encrypted and are never written to logs.

03 / THE DECISION

Credentials that expire by design.

Identity, short-lived credentials and real-time streams each need one clear owner across the browser, the backend and the external AI service. The backend keeps identity and issues access that expires, so the browser only ever holds temporary credentials.

04 / THE OUTCOME

Implemented flows, team-owned results.

The widget flows and platform components described here are implemented, as the platform's architecture documentation shows. Clara Care is a team product: its results belong to the team, and its operational data stays private.

SOURCES

Clara's platform architecture documentation. Code and internal links stay private. This page summarizes what those documents show.

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