Which clinical decision support startups earn the most?

The ranking of top startups in the clinical decision support market by revenue

Below is a table ranking the startups of this market by their current revenue scale. You can find our methodology at the end of this page.

If you want a deeper understanding of the market and its current dynamics, get our report on the clinical decision support market.

Which clinical decision support startups make the most money today?

OpenEvidence currently ranks first among clinical decision support startups, ahead of HeartFlow, Harrison.ai, DentalMonitoring, and SOPHiA GENETICS.

The gap between these companies is substantial, and their financial figures tell different stories. OpenEvidence has an estimated ~$300M annualized revenue run-rate as of July 2026. HeartFlow reported $176M in audited FY2025 revenue, while Harrison.ai's estimated 2025 revenue was ~$138M. DentalMonitoring follows with an estimated ~$91M for 2024, and SOPHiA GENETICS reported $77.3M for FY2025.

The ranking covers several types of clinical decision support. OpenEvidence helps physicians find medical evidence and earns money primarily through pharmaceutical advertising. HeartFlow provides coronary diagnostic analyses, Harrison.ai develops medical imaging AI, DentalMonitoring focuses on orthodontic monitoring, and SOPHiA GENETICS helps interpret genomic and other medical data.

We identified 20 startups with usable financial revenue indicators, alongside 19 others with quantified evidence of clinical adoption. Four additional companies remain unranked because their revenue and available commercial-scale information do not support a comparable position.

The financial ranking is shown below. It keeps the original reporting periods and metric types visible because annualized run-rate, estimated annual revenue, and audited fiscal-year sales are not interchangeable.

Rank	Startup	Revenue indicator	Metric and period
1	OpenEvidence	~$300M	Revenue run-rate, Jul 2026
2	HeartFlow	$176M	FY2025 revenue
3	Harrison.ai	~$138M	Estimated 2025 revenue
4	DentalMonitoring	~$91M	Estimated 2024 revenue
5	SOPHiA GENETICS	$77.3M	FY2025 revenue
6	Lunit	KRW 83.1B	FY2025 revenue
7	AMBOSS	€62M	FY2024 revenue
8	Aidoc	>$60M	Jun 2025 revenue run-rate
9	Ada Health	€37M	FY2024 revenue
10	Overjet	~$40.7M	Estimated 2025 revenue
11	Caresyntax	~$29.3M	Estimated 2025 revenue
12	VUNO	KRW 34.8B	FY2025 revenue
13	Qure.ai	INR 1.76B	FY2025 revenue, ended Mar 2025
14	Scopio Labs	~$21.9M	Estimated revenue, Jun 2024
15	Quibim	~$18.8M	Estimated 2025 revenue
16	FIZE Medical	~$17.1M	Estimated 2025 revenue
17	Covera Health	~$15.8M	Estimated revenue, Jun 2024
18	Infermedica	PLN 23.5M	FY2025 revenue
19	Cleerly	~$24.6M	Estimated 2023 revenue
20	Mediktor	€2.6M	2025 revenue

Why are clinical decision support AI startups making so much money now?

Clinical decision support AI startups are making serious money today because several have found ways to charge for work that doctors and healthcare organizations already do every day.

The clearest change is the arrival of AI assistants that can be used frequently without requiring hospitals to buy and deploy another traditional software system. OpenEvidence demonstrates this model. According to Sacra's September 2026 analysis, its clinical consultation volume reached approximately 20 million per month in January 2026, compared with roughly 3 million per month a year earlier. That is nearly seven times the activity in twelve months.

Specialized diagnostic AI has been growing through a different route. HeartFlow has commercialized coronary CT analysis since 2015, while Lunit, Aidoc, and other imaging companies sell software that fits into existing clinical workflows. Hospitals have to deal with the cost of implementing these products, but once integrated, they can become part of routine care.

Several companies are also expanding beyond their original products. Aidoc has moved from radiology-focused AI toward a broader clinical AI platform. OpenEvidence has added capabilities beyond medical literature search, including documentation and other physician workflows. SOPHiA GENETICS has expanded its data analysis platform across genomic and multimodal applications.

How much revenue does OpenEvidence make?

OpenEvidence has the highest selected revenue indicator among clinical decision support startups, and its estimated annualized revenue has grown extraordinarily fast.

Sacra estimates that OpenEvidence reached $7.9M in annualized revenue at the end of 2024, $150M at the end of 2025, and roughly twice that level by July 2026. Across those nineteen months, its estimated revenue pace increased approximately 38-fold.

Much of the growth comes from a model that differs from traditional medical reference software. Physicians can use OpenEvidence without paying a conventional individual subscription, while pharmaceutical advertisers pay to reach verified medical professionals. This removes much of the friction associated with selling hospital software, since doctors can adopt the assistant without waiting for a hospital-wide purchasing decision, provided institutional policies permit its use.

Sacra reports gross margins around 90% and advertising prices that can exceed $1,000 per thousand impressions in certain placements. Its September 2026 analysis also estimated that OpenEvidence had monetized only around 5% of available advertising inventory.

That last figure deserves attention, although the remaining inventory should not be treated as guaranteed future sales. Pharmaceutical advertisers have spending limits, and expanding advertising density could affect the experience of physicians using the product. Maintaining physician trust becomes particularly important when medical information and pharmaceutical marketing appear within the same product environment.

OpenEvidence has nevertheless reached a remarkable commercial position. It has turned a widely used clinical assistant into a major advertising business without depending on hospitals to purchase a subscription for every doctor.

Is HeartFlow the largest clinical AI startup with audited revenue?

HeartFlow has the largest audited annual revenue figure in our clinical decision support startup ranking, with its FY2025 results showing a business that has grown consistently for several years.

HeartFlow's SEC filings give us a useful three-year record. Revenue increased from $87.2M in 2023 to $125.8M in 2024, then to $176M in 2025. We calculate growth of approximately 44% in 2024 and 40% in 2025, meaning sales roughly doubled over two years.

The company earns substantially all its revenue through usage-based fees when physicians request its FFRCT or Plaque Analysis products. These tools help clinicians assess coronary artery disease using information from CT examinations.

One particularly revealing detail in HeartFlow's 2025 Form 10-K is that FFRCT remained its commercial foundation, representing 98% of total revenue. Its newer Plaque Analysis product had not yet become a similarly large revenue contributor.

So HeartFlow's growth has largely come from selling more of an established diagnostic service, rather than rapidly adding unrelated products. That gives us a clearer explanation for its revenue trajectory than a series of product-launch announcements would.

The company also reported a 76.8% gross margin in 2025. Its business is already substantial, although high operating expenses mean that strong gross margins have not yet translated into operating profitability.

How big is Harrison.ai compared with other medical imaging AI startups?

Harrison.ai ranks third overall and is one of the largest radiology AI startups in the ranking by estimated revenue.

Latka estimates Harrison.ai generated $137.7M in 2025 revenue, which we represent as ~$138M. That would put the company substantially ahead of most specialized imaging AI developers by reported commercial scale.

Harrison.ai's work focuses on applying AI to medical imaging, particularly through radiology applications. Its technology is designed to help clinicians identify abnormalities and prioritize findings across imaging examinations.

The size of the reported revenue figure is impressive, but its source needs attention. Latka provides an external estimate rather than audited company accounts, and the underlying financial records are not publicly available for us to verify.

For comparison, Lunit publishes audited consolidated financial statements, while Aidoc has a revenue run-rate confirmed in an investor report. Their smaller ranking positions should not be interpreted as proof that Harrison.ai has a correspondingly larger audited radiology software business.

Which clinical decision support startups have more than $50 million in revenue?

Eight clinical decision support startups have selected financial indicators above $50M, although only some of those figures represent completed annual revenue.

The group consists of OpenEvidence, HeartFlow, Harrison.ai, DentalMonitoring, SOPHiA GENETICS, Lunit, AMBOSS, and Aidoc.

HeartFlow, SOPHiA GENETICS, and Lunit have audited annual revenue above the threshold, while AMBOSS has reported €62M through German financial accounts. Harrison.ai and DentalMonitoring rely on external annual-revenue estimates, while OpenEvidence and Aidoc are represented by annualized run-rates.

Eight of the twenty financially ranked startups reach this threshold, while the remaining twelve sit below it on their selected financial indicators. There is already a clear upper tier, even though the gaps between companies cannot always be measured precisely.

Are medical imaging AI startups making more money than general clinical AI assistants?

Medical imaging AI has produced more revenue-ranked startups than clinical evidence assistants, but OpenEvidence remains the highest-ranked individual company.

Seven financially ranked businesses fall into our dedicated imaging decision support category: Harrison.ai, Lunit, Aidoc, Qure.ai, Scopio Labs, Quibim, and Covera Health. Their products range from radiology interpretation to microscopy, medical imaging biomarkers, and diagnostic quality analysis.

Clinical evidence and medication guidance has two companies in the financial ranking: OpenEvidence and AMBOSS. The latter combines medical education with clinical reference software, making its revenue broader than clinician decision tools alone.

We can compare the number and type of commercially established businesses, but a precise category revenue total would be misleading. The selected financial indicators include different fiscal years, estimates, and annualized run-rates.

Imaging AI has developed a wider collection of measurable revenue businesses. Clinical evidence assistants, meanwhile, have produced the single highest-ranked startup through a very different way of making money.

Can dental AI startups really make tens of millions of dollars?

Dental AI is already a serious commercial niche, with DentalMonitoring and Overjet both appearing among the ten highest-ranked clinical decision support startups.

DentalMonitoring helps orthodontists monitor treatment progress remotely through patient imaging and AI-assisted analysis. Overjet works mainly with dental radiographs, helping dental professionals interpret images and communicate clinical findings.

There is a practical reason these products can attract paying customers. Dental professionals already rely heavily on images, and the software fits into procedures that generate revenue for practices. Orthodontic monitoring can also be used repeatedly throughout a treatment rather than only during a single examination.

The two companies have different commercial models. DentalMonitoring is tied closely to ongoing orthodontic care, while Overjet is built around dental imaging and analysis, including applications involving insurers.

Both revenue indicators come from Latka estimates, so we should avoid treating their exact amounts as audited facts. Still, their places in the ranking show how far dental AI has moved commercially.

How much money does SOPHiA GENETICS make from clinical AI?

SOPHiA GENETICS is one of the largest clinical decision support startups with audited financial reporting, and its genomic AI platform is continuing to grow.

Its 2025 Form 20-F reports revenue growth of 19%, up from $65.2M in 2024. The company also completed more than 391,000 analyses through its SOPHiA DDM platform in 2025, according to its annual report.

Those figures give us two ways to assess the business. Revenue shows what customers paid, while analysis volume gives a more direct indication of platform activity. We cannot simply divide one by the other to infer the price of every clinical analysis because the business includes different services, applications, and commercial arrangements.

SOPHiA GENETICS has expanded from genomic interpretation toward broader multimodal data analysis, including applications for oncology and biopharmaceutical research.

The company has shown that complicated diagnostic data can support a meaningful software business. It also reported a substantial net loss for 2025, so its financial statements make clear that revenue growth and profitability remain separate questions.

Are Lunit and Aidoc becoming major medical imaging AI businesses?

Lunit and Aidoc are already major commercial medical imaging AI startups, with financial evidence that goes beyond announcements about pilots and hospital partnerships.

Lunit's 2026 business report shows FY2025 consolidated revenue of KRW 83.1B, equivalent to approximately $58.5M. That was up from KRW 54.2B in 2024, meaning revenue grew about 53% in the reporting currency.

The company sells imaging AI technology and has expanded into oncology-related products through acquisitions, including breast-risk software and biomarker applications. Consequently, its consolidated revenue covers a wider business than one diagnostic AI algorithm.

Aidoc's position is supported by the Venture Capital Opportunities Fund's June 2025 annual report. The investor stated that Aidoc had exceeded US$60M in annualized revenue and was growing at 50% year over year.

Aidoc's move into broader clinical AI is especially interesting because the company began with a strong focus on identifying findings in radiology images. It now aims to connect more AI applications across the healthcare workflow.

We have two credible commercial stories here: Lunit's audited sales growth and Aidoc's investor-confirmed recurring revenue pace. The difference in reporting format limits a precise side-by-side financial comparison, but both have crossed the threshold where clinical AI becomes a meaningful software business.

How much revenue do AMBOSS and Ada Health generate?

AMBOSS and Ada Health are two of the larger European clinical decision support startups with reported financial accounts, although they make money from different healthcare needs.

AMBOSS recorded €62M in FY2024 revenue according to German financial accounts. Its platform combines medical education, clinical reference information, and tools used by doctors in their daily work.

Ada Health reported €37M in FY2024 consolidated revenue. Its main focus is symptom assessment and triage, with technology used across consumer health and enterprise healthcare applications.

AMBOSS serves medical students as well as practicing clinicians, whereas Ada Health works on symptom assessment that can occur before a patient even sees a doctor. Their revenue figures therefore cover different kinds of healthcare activity.

Are surgical AI and hospital risk prediction startups making real money?

Surgical AI and clinical risk prediction startups have started generating meaningful revenue, but the best available figures show a much smaller commercial tier than the market's top five.

Caresyntax ranks eleventh with an estimated ~$29.3M in 2025 annual revenue. Its software brings together surgical data and analytics to help hospitals evaluate procedures, performance, and operating-room workflows.

VUNO follows in twelfth place with KRW 34.8B in audited FY2025 revenue, approximately $24.5M. The company develops medical AI systems, including tools used for clinical monitoring and identifying patients at risk of deterioration.

FIZE Medical ranks sixteenth with estimated 2025 revenue of ~$17.1M. Its technology combines patient monitoring with predictive clinical information, making it different from a purely software-based hospital alert platform.

The three businesses show how clinical decision support increasingly overlaps with monitoring devices, operating-room technology, and hospital analytics. Caresyntax and FIZE Medical, though, still depend on estimates rather than audited disclosures.

Which smaller clinical decision support startups are already earning revenue?

Qure.ai, Scopio Labs, Quibim, FIZE Medical, Covera Health, Infermedica, Cleerly, and Mediktor complete the revenue-ranked group, covering a wide range of diagnostic and patient-care applications.

Qure.ai has one of the stronger financial records within this group. A Fractal Group financial disclosure reports INR 1.76B for its fiscal year ended March 2025. The company develops AI for medical imaging, including chest X-rays and CT examinations.

Scopio Labs works on digital microscopy, while Quibim develops medical imaging biomarkers. Covera Health focuses on diagnostic quality and analytics, and Cleerly develops coronary imaging analysis technology.

Their revenue estimates should be read with care. For example, Cleerly's selected figure comes from 2023, which makes it less informative about current sales than a newer filed financial statement. That is why the company appears below Infermedica despite having a larger nominal historical figure.

Among patient assessment businesses, Infermedica reported PLN 23.5M in FY2025 revenue through Polish financial records. Its software supports symptom assessment and clinical triage.

Are patient triage AI startups still growing?

Patient triage AI startups have produced real revenue, but Mediktor's recent results show how easily growth can reverse when customer contracts are lost.

The clearest evidence comes from MTIP Fund II's investor report published in May 2026. Mediktor's revenue fell from €4.5M in 2024 to €2.6M in 2025, a decline of approximately 42%.

The report linked the difficult year largely to customer churn following the Sensely acquisition. Mediktor subsequently introduced a new AI Medical Agent in September 2025 and set a revenue target of €2.9M for 2026, with €1.7M visible through renewed contracts when the investor report was prepared.

The target suggests management expected some recovery, but it should not be confused with completed sales.

Ada Health and Infermedica demonstrate that symptom assessment and triage can sustain larger businesses, while Mediktor illustrates the pressure that customer retention and acquisitions can put on results.

Clinical triage clearly has commercial demand. What we cannot conclude is that every company operating in the category is growing quickly today.

Which clinical decision support startups are used in the most hospitals?

Glooko, Proscia, RapidAI, AZmed, and Viz.ai have some of the largest reported healthcare deployment footprints among the operationally ranked clinical decision support startups.

Glooko reported supporting 9,000 clinics in 2025 through its diabetes management technology. Proscia reported a network reaching more than 4,000 hospitals and clinics, while RapidAI and AZmed each reported deployment footprints above 2,500 healthcare institutions.

Viz.ai announced in July 2026 that its technology had reached 2,000 US hospitals, ten years after the company's founding.

These are meaningful adoption numbers. But a clinic supported through a technology platform, a hospital using an AI application, and a facility reached through a partner network do not necessarily represent equivalent commercial contracts.

We kept the operational indicators in their ranking order below. They provide evidence of scale where dependable revenue figures are unavailable, without assuming that the companies earn more than startups with published financial results.

Overall rank	Startup	Selected commercial indicator
21	Glooko	9,000 clinics, Dec 2025
22	Proscia	>4,000 hospitals and clinics, Oct 2026
23	RapidAI	>2,500 hospitals, Oct 2026
24	AZmed	>2,500 healthcare facilities, Oct 2026
25	Viz.ai	2,000 hospitals, Jul 2026
26	InsightRX	>1,000 hospitals, Dec 2025
27	Navina	>20,000 users, Apr 2026
28	Ibex Medical Analytics	2.4M slides analyzed per year, Sep 2026
29	Brainomix	>300 hospitals, Mar 2025
30	Optellum	>250 clinical sites, Jun 2026
31	Glass Health	>120,000 clinicians, Oct 2026
32	Regard	>150 hospitals, period undisclosed
33	Corti	>100,000 daily patient interactions, Aug 2024
34	VieCure	~30,000 patients under management, Jan 2026
35	FeelBetter	>450,000 patients supported, period undisclosed
36	Etiometry	>50 hospital partners, period undisclosed
37	xWave Technologies	>20 NHS Trusts, May 2026
38	Telepatia	>25 hospitals, Aug 2026
39	Mednition	~3.99M cumulative emergency patient visits, through Oct 2026

Are doctors actually using AI clinical decision support tools every day?

Doctors are already using clinical AI tools at considerable scale, although the available usage figures vary widely in what they measure.

Glass Health says more than 120,000 clinicians use its diagnostic reasoning platform. Navina reported more than 20,000 clinician and care-team users across over 1,300 clinics in April 2026. These figures show substantial professional adoption, even though the number of paying users within those totals is not disclosed.

There are also companies measuring clinical activity rather than individual users. Ibex Medical Analytics reported processing 2.4 million pathology slides annually as of September 2026. Corti previously reported supporting over 100,000 patient interactions per day, while Mednition's KATE AI had evaluated approximately 3.99 million emergency department visits cumulatively by October 2026.

Clinician counts show how widely a tool has spread among professionals, while examinations and patient interactions reveal activity in clinical workflows. The number of paying users, and the revenue generated from that activity, remains less clear.

Are the highest-revenue clinical AI startups profitable?

High-revenue clinical AI startups are not necessarily profitable, and HeartFlow's financial statements make the distinction especially clear.

In FY2025, HeartFlow generated $135.2M in gross profit but recorded $199.3M in operating expenses. Its operating loss was approximately $64.1M, according to its SEC filing.

The business had strong gross margins, but research, development, sales, and administrative spending still exceeded the gross profit generated from diagnostic services.

SOPHiA GENETICS also reported a net loss of $79.0M in 2025, despite revenue growing 19%. Its financial disclosures describe continued spending on product development, commercial expansion, and regulatory work.

OpenEvidence has been reported as operating with high gross margins and around cash-flow breakeven, but that information does not offer the same independently audited profitability detail as the public companies' financial statements.

We can identify successful revenue generators. A reliable profitability ranking, though, would require much more consistent disclosure of operating income, net income, and cash flow.

Can ChatGPT replace clinical decision support startups?

ChatGPT and other general-purpose AI assistants are becoming serious competitors to clinical evidence startups, particularly where the product mainly helps doctors search, summarize, and understand medical information.

The competition has become more direct. Sacra's September 2026 analysis examined OpenEvidence against ChatGPT for Clinicians, traditional reference products, and other physician-facing applications.

OpenEvidence's position is based on its medical focus, professional user base, and growing distribution among physicians. But general-purpose AI companies have access to large engineering budgets, broad consumer adoption, and the ability to add medical features to existing products.

For a doctor looking up a guideline or asking about a medication, competing AI assistants may increasingly serve similar purposes. That creates pressure to improve answer quality, coverage, speed, and integration with clinical work.

Specialized diagnostic companies are harder to compare directly. HeartFlow's coronary CT analysis, Lunit's imaging products, and SOPHiA GENETICS' genomic applications involve clinical data, validation, and workflows beyond ordinary text-based question answering.

So the competitive threat is strongest where the product is a clinical information assistant. For imaging and genomic AI, general-purpose models may become part of the technology, but replacing complete clinical products is a much more demanding task.

Does FDA regulation make clinical decision support startups harder to grow?

FDA regulation can make clinical decision support startups harder to launch and expand, especially when their software provides patient-specific diagnostic information rather than general medical reference material.

The FDA updated its Clinical Decision Support Software guidance in January 2026, clarifying which software functions may fall outside the medical-device definition and which remain subject to medical-device regulation.

The distinction depends on the software's intended use and specific capabilities. A tool helping clinicians review medical literature may face different requirements from software interpreting medical images or generating diagnostic outputs.

This affects product development, clinical validation, marketing claims, and sometimes the time needed to reach customers. Regulated products can require evidence that a simpler clinical information assistant does not need to produce.

The other side is that clinical validation and regulatory authorization can help companies win trust from hospitals and physicians. For specialist diagnostic applications, years of clinical testing and integration can also make a product harder for competitors to replicate.

Regulation has shaped the commercial paths of companies in this ranking, but it does not determine revenue by itself. Distribution, clinical usefulness, reimbursement, and customer spending remain just as important.

Which clinical decision support startups have been acquired or still keep revenue private?

Atropos Health, CathWorks, Artera AI, and PathAI remain unranked because we could not establish sufficiently comparable revenue or quantified commercial-scale figures.

They are nevertheless relevant businesses. Atropos Health develops technology for generating clinical evidence from healthcare data. Artera AI focuses on predicting treatment response in oncology. PathAI develops computational pathology software and related technology.

CathWorks is a particularly important acquisition case. Medtronic completed its acquisition in April 2026 for a stated $585M, with potential additional earn-out payments. CathWorks develops FFRangio, which uses AI and computational techniques to assess coronary physiology.

The acquisition followed a strategic partnership announced in 2022, so it extended an established commercial relationship rather than introducing CathWorks' technology to Medtronic for the first time.

CathWorks remains eligible within the recent-acquisition window, presented as part of Medtronic. But the $585M transaction value cannot be used as revenue, and Medtronic has not published a standalone sales figure that would justify assigning CathWorks a financial rank.

The same caution applies to the other unranked businesses. Their technology, customers, or investor backing may be important, but those facts do not establish a defensible position against companies with financial disclosures.

Which clinical decision support startups are actually winning the revenue race?

OpenEvidence is currently winning the clinical decision support startup revenue ranking, with HeartFlow and Harrison.ai taking second and third place. DentalMonitoring and SOPHiA GENETICS complete the leading five.

The more interesting result is how differently the winners make their money.

OpenEvidence has grown rapidly by monetizing a large physician audience through advertising. HeartFlow has built a usage-driven diagnostic business with several years of documented revenue growth. Harrison.ai represents the scale that medical imaging software may reach, although its financial estimate is less independently verifiable. DentalMonitoring has developed a substantial orthodontic technology business, and SOPHiA GENETICS has established a significant genomic analysis platform.

There is also a broad second tier of companies generating tens of millions of dollars, particularly in imaging, dentistry, clinical evidence, surgery, and patient triage.

Beyond them, startups such as Glooko, Proscia, RapidAI, and Viz.ai show widespread clinical adoption without publishing enough financial information for a dependable revenue comparison.

We see a market with a small number of clear commercial leaders and a much larger group of companies already being used in healthcare. The strongest revenue growth currently belongs to businesses that have solved distribution and monetization, whether through physician advertising, reimbursed diagnostic use, or specialist software contracts.

For now, OpenEvidence holds first place. HeartFlow offers the strongest audited annual revenue evidence among the ranked startups. Those two conclusions give us the clearest picture of who is making serious money in clinical decision support today.