Heidi has helped make "ambient voice technology" a familiar phrase for many UK clinicians. The wider significance is that AI is no longer sitting outside the consultation in a separate browser tab or reference tool. It is beginning to support the consultation itself — capturing clinical conversations in real time and generating structured documentation that clinicians review and approve.
For clinicians who have heard of Heidi but want to understand the broader category, this article explains what ambient voice technology is, how it works, why it matters, and where it fits alongside other clinical AI tools.
What Is Ambient Voice Technology?
Ambient voice technology (AVT) systems listen to clinical consultations in the background — without requiring the clinician to dictate, type, or interact with a separate recording device — and use AI to generate structured clinical documentation. The outputs may include consultation summaries, clinical notes, referral letters, patient messages, coding suggestions, and task lists.
NHS England describes these tools as AI-enabled ambient scribing products used for clinical or patient documentation and workflow support. The technology uses a combination of speech recognition (converting audio to text) and large language models (summarising, structuring, and formatting the text into clinically useful outputs). Critically, these are "human-in-the-loop" systems: the AI generates a draft, and the clinician reviews, edits, and approves before the output enters the permanent record.
Why Heidi Has Become a Prominent UK Example
Heidi Health, founded in Australia, has achieved significant adoption in UK healthcare. The company reports that its ambient AI scribe is used by one in two UK GPs and supports 1.8 million NHS appointments per month. Modality Partnership — one of the UK's largest GP groups with 53 sites serving nearly half a million patients — became the first to roll out Heidi across its entire network, representing the largest deployment of this kind of technology in UK primary care.
Heidi raised $65 million in Series B funding in October 2025, lifting its valuation to $465 million with nearly $100 million in total funding. It holds MHRA Class I registration for summarisation functionality, is DTAC assessed, ISO 27001 and SOC 2 Type II certified, and employs three NHS-accredited Clinical Safety Officers. The company has expanded beyond GP consultations into dental (PortmanDentex partnership, 60 new clinicians per month) and is partnered with 15+ NHS trusts.
How AI Scribes Work in Practice
The clinical workflow is straightforward. The clinician informs the patient that an AI scribe will be used for note-taking. The consultation proceeds normally. The AI listens, transcribes, and generates a structured draft. After the consultation, the clinician reviews the draft — checking accuracy, completeness, coding, and clinical nuance. The clinician edits where necessary and approves the final version for the clinical record.
The process typically adds no time to the consultation itself — the AI operates in the background. The review step takes 30-90 seconds for a straightforward consultation, longer for complex cases. The net effect, as reported by Heidi and supported by the GOSH-led NHS evaluation, is reduced total documentation time, increased patient interaction time, and reduced after-hours administrative work.
Why Clinician Review Remains Essential
AI scribes are not autonomous documentation systems. They generate drafts that require professional review. NHS England's guidance is explicit: healthcare professionals retain full responsibility for the accuracy of clinical records. Outputs must be checked and corrected before being saved.
This is not a limitation — it is a safety feature. Speech recognition can misinterpret drug names, medical terminology, and clinical context. Language models can hallucinate examination findings, create false diagnostic certainty, or generate plausible-sounding but clinically incorrect summaries. The clinician's review catches these errors before they enter the permanent record.
Why Patients May Benefit
The Modality Partnership deployment reported that over 75% of GPs felt a stronger connection with patients. One hundred per cent of patients accepted the technology, and many noted better eye contact and more personable consultations. When the clinician is not typing during the consultation, they can maintain eye contact, listen actively, and respond to non-verbal cues — the aspects of communication that build trust and therapeutic rapport.
Patient consent and transparency are important. NHS England's guidance requires clinicians to inform patients at the start of any session that an ambient scribe is in use. Patients should understand what the tool does and that they can ask questions about it.
Why AVT Is Only One Part of the Clinical AI Stack
Documentation is the most visible clinical AI use case because it solves the most universal pain point. But the clinical workflow involves more than documentation. Clinicians also need to retrieve guidelines, check prescribing safety, calculate risk scores, verify referral criteria, safety-net patients, and reflect on learning.
Ambient scribes like Heidi capture the consultation. Clinician-facing tools like iatroX help with the clinical knowledge layer: guideline-grounded answers, calculators, exam preparation, and CPD.
These are complementary layers. Documentation and clinical knowledge serve different moments in the same workflow — and clinicians benefit from both.
Try iatroX for guideline-grounded clinical answers, calculators, and CPD →