Two million consultations a week, 116 countries, 200 specialties. The numbers are extraordinary. The strategic questions they raise are harder.
Speaking today at the Digital Health Festival in Melbourne, Ben Condon, who leads enterprise deployments for Heidi Health, directly addressed whether a single product could genuinely work across every clinical setting — from a rural GP in outback Queensland to a cardiologist in a London teaching hospital to an NDIS support worker in suburban Melbourne.
“We recognise that whilst there are individual nuances across specialties and between telehealth and acute care,” he told the audience.
“Foundationally the product works across all environments, because we’ve been able to synthesise and listen and improve,” Condon told delegates.
It is a confident claim, but from a company that has moved fast and built genuine momentum.
According to Heidi its platform has supported 73 million patient consults and currently manages over two million weekly consultations in 110 languages across 116 countries.
It is valued at $860 million after its most recent $120 million Series B round, and it is the company everyone in clinical AI is watching.
But as the sector matures, the questions around its mile-wide strategy are getting harder to sidestep.
What Condon’s numbers suggest
Condon presented impact data from Heidi’s Australian hospital and enterprise deployments in 2025 —which claims a median utilisation rate of 86% across those deployments, with clinicians using the tool for the majority of their consultations every working day.
Compelling numbers.
They are not a picture of the broader market.
A HealthEd and The Medical Republic survey of 1,535 Australian GPs in May 2026 found just 18.7% said they personally use an AI scribe for consulting.
In the UK, a Nuffield Trust and RCGP survey of 2,108 GPs found just over a quarter reported using AI in their workplace at all. In Australian general practice, the market is split between Heidi and Lyrebird Health, and neither owns it outright.
What the data does consistently show is stickiness: clinicians who adopt AI scribes use them heavily and almost never stop.
That loyalty is Heidi’s most important strategic asset to date. The product is not merely tolerated — in health systems where it has been well implemented, it is loved. That is rare in clinical software and should not be underestimated.
What the big deployments show
Some compelling stories for Heidi’s institutional model comes from a few health systems that have committed seriously.
Condon presented data from New Zealand, following a national government endorsement, in which Heidi rolled out to every emergency department in the country — 1,100 clinicians onboarded in six weeks, documentation time dropping from 17 minutes per patient to four.
In the United States, Beth Israel Lahey Health — a 14-hospital system with more than 6,000 providers — announced last month it is rolling Heidi out to all its physicians following a six-month pilot.
Results: 89% satisfaction with note quality, 82% reporting reduced cognitive load, 74% reporting less time working outside standard hours, adoption driven almost entirely by word of mouth across 47 specialties.
Critically, BILH chose to deploy Heidi unintegrated first — before later connecting to Epic and athenahealth — on the deliberate theory that a tool clinicians want to use delivers more value than one that is perfectly integrated but half the workforce ignores. It retained physicians who had threatened to retire rather than deal with a new Epic implementation.
In Australia, Monash Health — 40 facilities including seven hospitals, serving 1.6 million people — is an active partner, as is Queensland Health’s Children’s Hospital and Health Service.
Public outcomes data from these deployments is not yet available in the way BILH’s is, but the institutional commitment across a complex Victorian public health network is a meaningful signal.
The pattern across all these deployments is consistent: Heidi does not need to be the infrastructure layer to deliver value. It needs to be the layer clinicians want.
But for how long will this idiom hold?
The EMR problem is accelerating
The BILH experience complicates the integration critique but doesn’t dissolve it.
In Australian general practice, Best Practice has partnered with Lyrebird Health as its preferred native scribe integration. Genie Solutions, which dominates the specialist market, has signalled plans to build its own or partner in the manner BP has with Lyrebird.
Both follow the same logic: a scribe with access to the full patient record, current medications, previous consultations and billing context is clinically more useful than one without.
Epic launched its own AI Charting in February 2026. Cerner is moving in the same direction.
Heidi has push-to-chart integrations with Epic, athenahealth and eClinicalWorks in the US market. That isn’t a deep integration though. It’s not calling a patient history and considering it when it considers the summaries from a consult. That’s a big hole.
In Australia’s primary care market, where Best Practice and Medical Director hold the vast majority of GP desktops, the integration story is still developing.
The BILH model leaves open the idea that Heidi can build clinical relationships first and deep integration second. EMRs are notoriously clunky and integration could kill off the productivity of the consult if done the wrong way. Condon alluded to this idea in his talk. Heidi is clearly thinking that it doesn’t want to get sucked into the poor clinician experience that nearly all EMRs have.
Whether that sequencing works in Australian general practice, where the EMR incumbents are simultaneously building competing native solutions, is an more open question.
Related
The local and specialty-specific challenge
A GP consultation in Brisbane and one in Boston involve the same basic documentation task. But the clinical frameworks are completely different: RACGP guidelines, PBS prescribing and Medicare item numbers in Australia; insurer billing codes and liability frameworks in the US; NHS contract conditions in the UK. The scribe layer is largely agnostic to these differences.
The evidence and decision support layers are not so much (they shouldn’t be at all of course).
This is the opening local and specialty-specific players are exploiting in Australia.
Medluma, developed by Australian medical education company Medcast, is building a guideline and evidence layer calibrated specifically for Australian clinical practice — the right formulary, the right pathways, without international noise.
More pointed still is MBSPro, built by a rural Queensland GP and used only in Australia by GPs only.
MBSPro listens to consultations in real time and does more than generate a clinical note: it suggests the appropriate Medicare item numbers based on the conversation, flags preventive care and health assessments that are due, helps audit-proof billing against MBS criteria, and integrates with Best Practice to track daily item numbers billed.
For an Australian GP working under fee-for-service Medicare, MBSPro is addressing workflow problems that Heidi, built for every clinician in every country, is structurally unable to solve with the same depth.
The question this raises is not whether Heidi’s universal base is useful — it clearly is — but whether, as the AI layer in the consult matures from pure transcription toward billing support, coding, local evidence, and preventive care workflows, a product built for everyone everywhere can keep pace with products built from the ground up for one country and one type of doctor.
A surgical AI that understands operative notes and theatre scheduling from the ground up is a different product from a general scribe configured to approximate it.
MBSPro is the GP version of that argument made in practice.
The strategic moment
None of this is a verdict against Heidi. The stickiness data is real. The NZ system-level results are real. The BILH deployment — 6,000 physicians, 14 hospitals, spread by word of mouth across 47 specialties — is real. A company that has returned 18 million clinical hours to frontline workers in 18 months through largely organic adoption has clearly found something that works.
But the scribe and evidence layer that got Heidi here are increasingly table stakes.
Lyrebird is building. Best Practice is partnering with Lyrebird.
Genie might just be building its own or doing the equivalent with a tight partner. Epic launched AI Charting.
Every major EMR vendor is asking whether ambient documentation should be a platform feature rather than a separate product.
And locally-built, specialty-specific tools like MBSPro are building upward from a depth of local context that a global platform cannot easily replicate.
What Heidi has that none of those products have is the clinician relationship at scale — the loyalty of users who chose Heidi before their EMR offered an alternative and who trust it in a way they don’t trust software procured for them by their hospital.
That is genuinely valuable and, as BILH demonstrated, durable enough to survive alongside a competing EMR rollout.
The question is how long it holds as the integration gap narrows, and as locally-specific and specialty-specific products build the depth that a platform designed for everyone, everywhere is structurally challenged to match.
That moment has not arrived yet.
But the companies building toward it are already in the room.
