ClinNote AI app icon

Medical Transcription & Clinical Reporting Software

ClinNote AI

A cross-language desktop product for capturing clinical audio, transcribing it locally, and producing structured medical reports.

Client-Used Software
  • Tauri
  • TypeScript
  • Rust
  • Python
  • WASAPI
  • Whisper
  • Firestore
Audio to clinical reportVerified Production Architecture
ClinNote AI desktop medical audio waveform and clinical transcription software
Ownership

Engineered the product end to end across its desktop interface, native audio layer, transcription pipeline, and supporting services.

Domain

Medical Transcription & Clinical Reporting Software

Store Status

Client-used product

01Challenge

Product Constraints & Engineering Scope

Build a high-reliability desktop clinical recording and transcription solution that captures clean multi-channel audio, executes local AI speech-to-text without cloud latency, and generates structured medical documentation.

02Architecture

Mobile Architecture & State Patterns

  • Architected using Tauri desktop runtime with a TypeScript frontend and high-performance native Rust core.
  • Implemented cross-language inter-process communication (IPC) bridging the UI with native audio pipelines.
  • Engineered patient records, clinic management, and customizable clinical report templates.
03Integration

Backend, APIs & Platform Boundary

  • Integrated Windows WASAPI in native code for dual microphone and system-audio loopback capture.
  • Integrated local Whisper transcription pipeline with fallback to OpenAI cloud endpoints.
  • Synchronized structured patient clinical notes and templates with Google Cloud Firestore.
04Performance

Performance & Data Optimizations

  • Utilized Rust for low-overhead audio buffering and WASAPI hardware interaction, minimizing CPU footprint during active consultations.
  • Local Whisper speech processing ensures confidential patient audio remains on-device whenever required.
05Outcomes

Verified Outcomes & Production Delivery

  • Delivered end-to-end desktop software currently deployed and used by the healthcare client.
  • Eliminated transcription delays and streamlined clinical SOAP note documentation.
  • Showcases systems-level engineering breadth across Rust, Python, Tauri, and native audio APIs.