Now in Private Beta

From Conversation to Clinical Note, With Every Claim Verified

AI-generated clinical notes you can trust. Every sentence is grounded in transcript evidence, verified against medical knowledge bases, checked for hallucinations, and delivered in real time with full HIPAA compliance — so you can focus on what matters most: patient care.

HIPAA Compliant
Audio AI
Transcript Grounded
PubMed Verified
30-Day Free Trial
Features

Trusted, Evidence-Grounded Clinical Documentation

From real-time transcription to hallucination detection, every note is grounded in transcript evidence and verified against PubMed — so clinicians can trust what they read.

Core Platform

Rich Audio Transcripts

Produces turn-by-turn transcripts with word-level timestamps and automatic speaker role identification (patient vs. clinician).

Transcript Segmentation

Organizes conversation content into clinically relevant sections (Subjective, Objective, Assessment, Plan) for quick information retrieval.

Clinical Q&A

Ask clinical questions and get evidence-based answers powered by LLM and RAG from external medical knowledge bases and internal patient records.

Real-Time Transcription

Stream live audio for instant transcription with WebSocket support, perfect for in-session documentation.

HIPAA-Compliant Privacy

Built for healthcare with HIPAA-eligible architecture, automatic PII redaction, zero patient data retention, and full control over transcription storage.

Advanced Intelligence

AI Clinical Note Generation

Automatically generates structured clinical notes (SOAP, progress notes, discharge summaries) from patient-clinician conversations in real time.

Evidence Mapping

Every sentence in a generated note references the original transcript, enabling clinicians to verify accuracy and trace AI output back to its source.

Structured Medical Term Extraction

Automatically extracts clinical entities (conditions, medications, dosages, procedures) for downstream coding and workflow automation.

Hallucination Alert

Flags AI-generated content that cannot be grounded in the original conversation, giving clinicians clear visual warnings of unsupported claims.

Keyword Grounding

Anchors generated notes to specific keywords and phrases from the source transcript, ensuring clinical accuracy with auditable links.

Drug Info & Interactions

Instant access to drug details, adverse events, and interaction checks via OpenFDA and RxNorm integration.

EHR & Hospital Integration

Flexible and seamless integration with target clinics, EHR systems, and hospital deployments for streamlined workflows. Easy API access and support for custom connectors.

How It Works

From Conversation to Clinical Note in Minutes

Step 1

Record

Upload an audio file or start a live recording of the clinical encounter.

Step 2

Transcribe

State-of-the-art Audio AI transcribes speech to text with speaker labels and PII redaction.

Step 3

Generate

AI generates structured clinical notes, extracts medical terms, and maps evidence from the transcript.

Step 4

Review

Clinicians review grounded notes with visual hallucination alerts and clear evidence links, then approve.

Testimonials

Trusted by Healthcare Professionals

By cutting our documentation time, our physicians and nurses can finally focus on patient care instead of paperwork.

Dr. Ella Huang

Professional Practice Consultant, Provincial Health Services

This tool can be useful in situations where nurses cannot record information in a timely manner, such as wound care, stoma care, intravenous management, and emergency codes.

Dr. Lori Block

Clinical Informatics Specialist, Vancouver Coastal Health

In healthcare AI, trust is non-negotiable. We need tools that are HIPAA-compliant with zero data leakage, and that back every claim with evidence — not hallucination.

Dr. Jun Ma

Machine Learning Lead, University Health Network

HIPAA Compliant
SOC 2 Type II
Audio AI
Low Latency
Our Team

Meet the People Behind Med-Scribe

Xiaoxiao Li

Science Lead

Tenured professor at UBC, Canada Research Chair in Responsible AI, CIFAR AI Chair. Drives the research vision behind Med-Scribe, from hallucination detection to evidence-grounded clinical NLP.

Ruinan Jin

Machine Learning Lead

Audio and NLP machine learning expert. Architects the ML pipeline powering transcription, note generation, and medical term extraction.

Ryan Liu

Tech Lead

Over 10 years of experience in software engineering and databases. Leads platform engineering, from real-time audio infrastructure to HIPAA-compliant deployment and EHR integration.

Get Started

See Med-Scribe in Action

Schedule a personalized demo and discover how Med-Scribe can transform your clinical documentation workflow.

  • Live 30-minute personalized walkthrough
  • See Med-Scribe configured for your specialty
  • Q&A with our clinical and engineering team
  • Get up and running in under a week

Book Your Demo