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.

Try medication names (ibuprofen, metformin, amoxicillin), dosage instructions, procedure names, and anatomical terms. Take a few steps away from your device to mimic an ambient environment.

Medical Mode in Universal-3 Pro Streaming
Clinical evaluation history:
00:00
01:59
"prompt": "Produce a transcript for a clinical history evaluation. It's important to capture medication and dosage accurately. Every disfluency is meaningful data. Include: fillers (um, uh, er, erm, ah, hmm, mhm, like, you know, I mean), repetitions (I I I, the the), restarts (I was- I went), stutters (th-that, b-but, no-not), and informal speech (gonna, wanna, gotta)"
Without prompting

"I just want to move you along a bit further. Do you take any prescribed medicines? I know you've got diabetes and high blood pressure. I do. I take Ramipril. Okay. And I take Metformin, and there's another one that begins with G for the diabetes.  Glicoside."

With context aware prompting

"I just wanna move you along a bit further. Do you take any prescribed medicines? I know you've got diabetes and high blood pressure. I, I do. I take, um, I take Ramipril. Okay, mhm. And I take Metformin, and there's another one that begins with G for the diabetes. So glycosi — glycosi— glycoside."

Non-speech audio event:
00:00
01:59
"prompt": "Produce a transcript suitable for conversational analysis. Every disfluency is meaningful data. Include: Tag sounds: [beep]"
Without audio tagging

"Your call has been forwarded to an automatic voice message system. At the tone, please record your message. When you have finished recording, you may hang up or press 1 for more options."

With audio tagging

"Your call has been forwarded to an automatic voice message system. At the tone, please record your message. When you have finished recording, you may hang up or press 1 for more options. [beep]"

Speech with disfluencies:
00:00
01:59
"prompt": "Produce a transcript suitable for conversational analysis. Every disfluency is meaningful data. Include: fillers (um, uh, er, ah, hmm, mhm, like, you know, I mean), repetitions (I I, the the), restarts (I was- I went), stutters (th-that, b-but, no-not), and informal speech (gonna, wanna, gotta)"
Without disfluency prompting

Do you and Quentin still socialize when you come to Los Angeles, or is it like he's so used to having you here? No, no, no, we're friends. What do you do with him?

With disfluency prompting

Do you and Quentin still socialize, uh, when you come to Los Angeles, or is it like he's so used to having you here? No, no, no, we, we, we're friends. What do you do with him?

Proper noun spelling:
00:00
01:59
"keyterms_prompt": ["Kelly Byrne-Donoghue"]
Without keyterms prompting

"Hi, this is Kelly Byrne Donahue"

Without keyterms prompting

"Hi, this is Kelly Byrne-Donahue"

Caputuring speaker roles:
00:00
01:59
"prompt": "Produce a transcript with every disfluency data. Additionally, label speakers with their respective roles. 1. Place [Speaker:role] at the start of each speaker turn. Example format: [Speaker:NURSE] Hello there. How can I help you today? [Speaker:PATIENT] I'm feeling unwell. I have a headache."}
With traditional speaker labels

Speaker A: 5Mg. And do you take it regularly?

Speaker B: Oh yeah, yeah.

Speaker  A: Good.

Speaker B: Every evening.

Speaker A: And no side effects with it?

With speaker labels prompting

Speaker [Nurse]: 5Mg. And do you take it regularly?

Speaker [Patient]: Oh yeah, yeah.

Speaker  [Nurse]: Good.

Speaker [Patient]: Every evening.

Speaker [Nurse]: And no side effects with it?

Spanish and english audio:
00:00
01:59
"language_detection": True
"prompt": Preserve natural code-switching between English and Spanish. Retain spokenlanguage as-is (correct "I was hablando con mi manager").
Without codeswitching

Would definitely think I spoke Spanish if you heard me speak Spanish. But I still make mistakes. Soy wines. Paltro Soy. La fundadora de goop. Thank you. Thank you for doing that.

With codeswitching

You would definitely think I spoke Spanish if you heard me speak Spanish, but I still make mistakes. Soy Gwyneth Paltrow, soy la fundadora de Goop. Thank you. Thank you for doing that.

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

Accuracy where it matters most

Our Voice AI models deliver near-human accuracy even among noisy or challenging audio to capture the crucial details needed for smooth and seamless downstream processes.
The industry’s lowest Missed Entity Rate on medical terminology
AssemblyAI
Universal-3 Pro w/
Medical Mode
Deepgram
Nova-3
Medical
Amazon
Transcribe
Medical
Google
Medical
Conversation
3.2%
4.7%
8.7%
24.4%
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.

Frequently Asked Questions

Does AssemblyAI offer a PII redaction feature?

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.

How does speaker diarization work in multi-provider clinical encounters?

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.

 How does AssemblyAI accurately capture medical jargon and terminology?

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%.

How does AssemblyAI secure patient data?

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.

What is Ambient AI?

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.

How can conversational AI and voice AI be used in healthcare?

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.

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