Build reliable ambient AI scribes for clinical environments

Get clinical-grade accuracy in far-field, multi-speaker exam rooms and transparent pricing that scales with your growth.

Transform clinical processes and create better patient experiences with Voice AI

Automate manual processes and speed up routine encounters while extracting actionable insights from every patient interaction

Industry leading accuracy in far-field ambient conditions

Capture medical conversations from 20+ feet away as providers move, perform procedures, and interact with patients.

Robust far-field performance: Get precision-grade accuracy, no matter how close the provider stays to the microphone
Background noise resilience: Maintain accuracy no matter the background audio, equipment noise, or multiple speakers present at once
Reduce medical entity errors by 87% with Medical Mode: Correctly identify pharmaceutical names, anatomical terms, and medical acronyms

Price-performance and scalability that grows with you

Build workflows that are powerful and compliant at a price point that scales.

Industry-leading price-performance: Get industry-leading accuracy at a fraction of what you'll pay legacy medical speech providers
Full HIPAA compliance: Business Associate Agreement included with no additional costs or commitments
Enterprise-grade reliability: Consistent performance across millions of conversations, production SLAs, and hands-on technical support

Features and capabilities purpose-built for clinical applications

Build powerful products on models that are engineered for patient interactions and clinical environments.

Advanced speaker diarization: Accurately identify and separate speakers as patients, providers, and staff move in and out of conversations.
Ultra-low latency real-time transcription: Enable immediate clinical decision-making and live documentation
Automatic PHI redaction and structured output: Remove sensitive information while generating precise summaries for EHR integration

Capturing speech is where it starts. Creating outcomes is where it counts.

Learn why today's leading healthcare companies choose AssemblyAI to power their product experiences.

In the medical context, accuracy is highly important….[and] there can be multiple people present. Separating them is key to accuracy. The biggest impact AssemblyAI has had has been in enabling our technical team to focus on workflow-specific features rather than a general speech-to-text pipeline,

Jackson Bierfeldt, Cofounder + CTO, JotPsych

36%

improvement in WER

By leveraging AssemblyAI's accurate transcription capabilities through Dovetail, Careship can truly understand the needs of caregivers and patients, turning qualitative research into the foundation for better healthcare experiences across Europe.

More accurate on medical terms than every other provider

The terms that determine patient outcomes — medication names, dosages, and diagnoses — transcribed more accurately than ever.

MER & WER across medical transcription models Lower is better · % of entities not correctly transcribed
	AssemblyAI Universal-3 Pro w/ Medical Mode	Deepgram	Speechmatics Enhanced Medical	Deepgram Nova-3 Medical	AWS Transcribe Medical	Google Medical Conversation
MER	3.2%	3.6%	4.7%	8.7%	24.4%	—
WER	5.3%	5.5%	6.1%	5.9%	12.9%	—

Explore all benchmarks

AssemblyAI correctly transcribes clinical terms while other providers miss key medical entities

Modern tools for superior intelligence

Insights that power Voice AI innovation

Get insights, industry trends, and breakthroughs on how Voice AI is powering today's provider and patient experiences.

Insights

Building Ambient AI Scribes: Your guide to evaluating Voice AI for healthcare

Blog

Medical voice recognition: How AI solves terminology problems

Blog

Conversation Intelligence: The complete guide for 2025

Common questions

: Yes—when enabled. Set redact_pii: true to automatically replace PHI in the transcript, and optionally use redact_pii_policies. You can also mute PHI in audio with redact_pii_audio: true.
: AssemblyAI segments clinical audio into speaker‑labeled turns. Enable speaker_labels (optionally set speakers_expected) and use role-based Speaker Identification (e.g., Doctor/Patient). In streaming, format_turns returns structured, speaker-aware output. The platform supports multi-speaker clinical settings (consults, rounds) and improves separation in noisy/overlapping speech.
: AssemblyAI captures medical jargon using its Slam-1 model built for clinical transcription, plus context via a Keyterms prompt (patient history, specialty, visit context). For live use, Universal-Streaming is optimized for medical contexts. The platform handles pharma names and acronyms and reduces missed medical entities by up to 66%.
: AssemblyAI secures patient data with AES‑128/256 encryption at rest and TLS 1.2+ in transit. It offers HIPAA‑compliant workflows with Business Associate Agreements (BAA) and optional EU data residency, and provides PII redaction to automatically remove sensitive information.
: Ambient AI refers to AI that operates in the background during real‑world interactions, turning conversations into structured data and automation without manual effort. In practice, systems transcribe live speech with low latency and extract insights to automate documentation and agent assist in domains like healthcare and contact centers.
: Healthcare teams use conversational/voice AI for ambient clinical documentation (real-time transcription, speaker diarization, and LLM‑generated SOAP notes), telehealth and ED encounters with low‑latency streaming, and HIPAA‑compliant PII redaction (text and audio). Beyond documentation, systems also support intelligent triage and patient education.