DATE
16/09/2025
TheraScribe: AI Clinical Platform
We partnered with a clinical startup to architect and build TheraScribe, a real-time AI clinical documentation platform designed to streamline therapist workflows, automate note generation, and integrate documentation directly into an EHR environment.
The system combines speech-to-text, structured clinical note generation, and practice management tools into a single unified platform.
AI Product
Startup
Services
AI Product Architecture & Build
Category
Clinical AI Platform / Practice EHR
Client
Confidential Medical Startup
System Analysis - Stability and Inference Performance
We structured the AI system powering TheraScribe for low-latency inference and stable output generation under real clinical usage scenarios.
Therapists and clinicians require documentation tools that can handle fragmented conversations, interruptions, and varying input quality. The system was designed to maintain reliable outputs under these conditions.
Performance
AI Systems
Optimized Inference Routing
The transcription and note-generation pipeline was structured to minimize unnecessary model calls. Preprocessing layers extract conversational structure before passing data to the language model.
Efficient Model Handling
Lightweight orchestration layers reduce compute overhead while maintaining real-time transcription and structured note formatting.
Scalability Planning
The architecture was designed to support increasing documentation volumes as clinics onboard multiple practitioners.
Reliability
TheraScribe was engineered for consistent clinical output generation across varied conversational contexts.
The system handles incomplete sentences, fragmented clinical discussions, and speaker interruptions while maintaining coherent structured notes.
This ensures reliable clinical documentation during real therapy sessions rather than controlled test environments.
Problem – Documentation Structure and Model Drift
Early prototypes relied heavily on direct generative outputs for clinical documentation.
This resulted in several issues:
• Inconsistent note formatting
• Context drift during longer sessions
• Missing clinical entities within transcripts
Clinical documentation requires strict structural consistency. Small formatting variations can impact billing, compliance, and record keeping.
System Architecture Improvement
AI Architecture
To improve reliability, the pipeline was redesigned to include:
• Entity extraction layers
• Structured conversation segmentation
• Controlled model orchestration
This ensured documentation outputs remained consistent across sessions.
Solution – Structured Orchestration and Controlled Deployment
The TheraScribe AI documentation system was rebuilt using layered orchestration logic and controlled deployment workflows to ensure reliable output formatting in production environments.
System Integration
Integration
The platform integrates multiple components into a single clinical workflow:
• Real-time speech transcription
• Clinical entity extraction
• Structured note generation
• Patient record integration within the EHR
• Documentation review and editing tools
Deployment environments were configured for:
• Version control
• Auditability
• Safe model updates
• Continuous monitoring of inference performance
This architecture allows TheraScribe to evolve without disrupting live clinical workflows.
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