Clinical decision support funding tracker (135 deals)

Our funding tracker covering the clinical decision support market

Below is the table listing all the deals. You may find our methodology at the end of this page.

And, if you want to gain a deeper understanding of the market and its current dynamics, get our report covering the clinical decision support market.

Is clinical decision support really a $3 billion funding market?

Clinical decision support companies attracted approximately $2.996 billion in recorded funding across 135 deals between January 1, 2024, and September 24, 2026. But most of that money went to a surprisingly small number of businesses.

We identified 118 funded companies, covering everything from medical imaging AI and clinical risk prediction to precision medicine and tools that help doctors find reliable medical evidence.

Just 15 rounds worth more than $50 million accounted for approximately $1.812 billion, or 60.5% of all recorded funding. Without those rounds, the market would have raised approximately $1.184 billion.

There is a broad market for financing the development and validation of clinical AI products, alongside a much smaller group of companies raising the kind of money needed to expand across major healthcare systems.

How much can a typical clinical decision support startup raise?

The typical clinical decision support financing is around $7.46 million, considerably less than the $22.36 million average reported across the market.

We calculated both figures from the 134 financing transactions with quantifiable amounts. The average is three times the median because a relatively small number of exceptionally large rounds pull it upward.

Looking at companies rather than transactions gives us a similar result. The median company raised $7.64 million during the period, compared with an average of $25.39 million.

There is also a clear difference between first financings and later rounds. Transactions classified as first financings had a median of $1.91 million, while follow-on transactions reached $11 million.

Consider three recent examples. Acurion raised $4.3 million in April 2026 to advance its OncoGaze precision oncology platform. In December 2025, a2z Radiology AI secured $4.5 million to expand its CT interpretation technology. French startup AI-Stroke raised $4.6 million in November 2025 to support clinical studies and its regulatory pathway.

These financings are much closer to the normal fundraising experience than the nine-figure rounds that dominate industry headlines.

How many clinical decision support startups are getting funded more than once?

Only 14 of the 118 clinical decision support companies we identified raised money more than once during the observation window.

The other 104 companies, representing 88.1% of the market, appeared in just one qualifying transaction.

That might sound like a weak repeat-fundraising rate, but the money tells a more interesting story. The 14 companies with multiple recorded rounds attracted approximately $1.531 billion, slightly more than the $1.465 billion received by businesses appearing once.

Much of that concentration comes from OpenEvidence and Aidoc, which completed five and two recorded financings respectively. Other companies, including Harrison.ai and Cleerly, attracted substantial capital through a single large transaction during the period.

We should also distinguish between a company receiving follow-on funding and one raising repeatedly within this specific window. Many businesses had already secured financing before January 2024, so a single recorded deal can still represent a mature company raising its Series C or Series D.

Which clinical decision support companies have raised the most money?

OpenEvidence is by far the largest recipient of clinical decision support funding, followed by Aidoc, with a considerable gap separating both companies from the rest of the market.

OpenEvidence raised $985 million across five transactions during the period. Aidoc followed with $260 million in recorded equity financing, while Harrison.ai and Cleerly raised $112 million and $106 million respectively.

There is considerable variety among these leaders. OpenEvidence provides AI-powered access to clinical research and medical evidence. Aidoc develops enterprise clinical AI applications across multiple medical specialties. Harrison.ai concentrates on diagnostic imaging and pathology, while Cleerly uses AI-powered coronary imaging to support cardiovascular assessment.

Further down the ranking, Qure.ai raised $65 million, Regard secured $61 million, Pearl raised $58 million for dental AI, and Navina attracted $55 million for its clinical intelligence platform.

These companies have different products and customers, but their large financings have something in common: the capital is generally being directed toward products with wider clinical deployment ambitions, rather than a single early-stage experiment.

Company	Rounds	Capital raised
OpenEvidence	5	$985M
Aidoc	2	$260M
Harrison.ai	1	$112M
Cleerly	1	$106M
VieCure	2	$88M
Qure.ai	1	$65M
Regard	1	$61M
Pearl	1	$58M
Elucid	1	$55M
Navina	1	$55M

Is OpenEvidence taking over clinical decision support funding?

OpenEvidence has become the dominant fundraising story in clinical decision support, accounting for nearly one-third of all capital raised during our observation window.

Its financing history is particularly unusual. The company raised $75 million in February 2025, followed by $210 million in July and $200 million in October. Another $250 million arrived in January 2026, followed by a further $250 million financing reported in September.

The last transaction reportedly valued OpenEvidence at $15 billion. Reporting by Becker's Hospital Review in September 2026 confirmed that the company's CEO had acknowledged the raise and identified Andreessen Horowitz and Byers Capital as lead investors.

Why has OpenEvidence attracted so much money?

Its product addresses a much broader audience than many specialized clinical AI applications. Rather than focusing on one disease or medical imaging procedure, OpenEvidence allows physicians to search and interpret medical research, clinical guidelines and published evidence.

That gives investors a potential distribution opportunity across multiple specialties and healthcare settings. The company has also built relationships with major medical publishers, including the New England Journal of Medicine, and has reported strong physician adoption.

OpenEvidence represents approximately 92.7% of all funding in the evidence and guideline support category. Removing the company from the market would bring aggregate recorded funding down to approximately $2.011 billion.

Which clinical decision support categories are attracting the most investment today?

Diagnostic decision support is the biggest category by deal count and capital raised, while evidence and guideline support stands out for its unusually large financing amounts.

We counted 70 diagnostic decision support transactions involving 64 companies, for a total of approximately $1.246 billion. That includes businesses developing tools for radiology, cardiovascular diagnosis, pathology and other medical specialties.

Evidence and guideline support attracted $1.062 billion through just ten transactions involving six companies. Its median financing reached $54 million, almost ten times the $5.45 million median for diagnostic decision support.

As we saw with OpenEvidence, most of that difference comes from one company. It would be misleading to assume that clinical evidence startups generally raise much more than diagnostic AI businesses.

Risk prediction and alerts attracted $294.2 million, while precision medicine decision support received $281.9 million. Both categories have a meaningful number of funded companies, although their aggregate financing is much smaller.

At the other end, treatment recommendation, medication decision support and care pathway support received relatively little capital. Their smaller company populations also make it harder to draw conclusions about how these markets will develop.

Category	Deals	Companies	Capital	Median round
Diagnostic Decision Support	70	64	$1,245.6M	$5.45M
Evidence & Guideline Support	10	6	$1,062.0M	$54.00M
Risk Prediction & Alerts	20	17	$294.2M	$8.00M
Precision Medicine Decision Support	19	15	$281.9M	$11.00M
Treatment Recommendation	8	8	$50.9M	$3.09M
Medication Decision Support	5	5	$38.7M	$3.00M
Care Pathway Support	3	3	$22.7M	$7.62M

Why are investors putting so much money into diagnostic AI?

Diagnostic AI attracts large funding rounds because established companies increasingly need to support entire clinical workflows, making development, validation and hospital deployment expensive.

Aidoc gives us a good example. In July 2025, the company announced a $150 million financing package, including $110 million of equity and a $40 million credit facility. Less than a year later, in April 2026, it announced another $150 million Series E led by Goldman Sachs Alternatives.

According to Goldman Sachs' announcement, the later financing was intended to expand Aidoc's clinical foundation model and enterprise AI platform.

Other companies reveal different parts of the same problem. Harrison.ai raised $112 million in February 2025 to expand its medical imaging and pathology solutions internationally, particularly in the United States. Cleerly's $106 million Series C extension in December 2024 was directed toward commercial growth and further clinical evidence generation for its cardiovascular imaging technology.

Qure.ai provides another useful comparison. Its $65 million Series D in September 2024 was intended to support international expansion, foundational AI development and potential acquisitions of complementary medical technology businesses.

A clinical AI business may need to validate performance across hospitals, obtain medical-device clearances, integrate with existing systems and support customers using its software in real clinical settings. These requirements help explain why advanced diagnostic companies can need substantially more capital than those still testing an initial product.

Are precision medicine startups getting funded earlier than other clinical AI companies?

Precision medicine decision support companies are attracting investment at a noticeably younger age than most other clinical AI businesses.

Their median age at financing is just 2.5 years, compared with six years for diagnostic decision support and seven years for risk prediction and alerts.

Despite being younger, precision medicine businesses recorded a median financing of $11 million, exceeding the median round in both of those categories.

Acurion illustrates the kind of product attracting early funding. Founded in 2021, the company raised $4.3 million in April 2026 to advance OncoGaze, which uses pathology images to predict actionable cancer biomarkers.

Its announcement specifically identified further clinical validation, regulatory preparation and commercialization among the uses of the funding.

Meanwhile, older risk prediction companies tend to operate in more established clinical environments, where the work involves identifying patient risks, triggering alerts or supporting clinical monitoring.

We cannot conclude from these figures that precision medicine businesses develop products faster. Founding dates, academic spin-offs and company classifications can all influence apparent age. But investors have been willing to back relatively young precision medicine businesses with meaningful financing amounts.

Why are treatment recommendation and medication AI startups raising so little?

Treatment recommendation and medication decision support have attracted surprisingly little dedicated venture funding compared with diagnostic applications.

Together with care pathway support, these categories account for just 16 of the 135 transactions and $112.3 million of recorded capital.

Treatment recommendation generated eight deals totaling $50.9 million, with a median round of approximately $3.09 million. Medication decision support had five transactions worth $38.7 million, while care pathway support recorded three financings totaling $22.7 million.

The medication category is particularly dependent on one company: its largest $30 million transaction accounts for more than three-quarters of the category's capital.

There is a plausible commercial explanation for the relatively limited number of standalone financings. Treatment recommendations, medication optimization and care pathway management can be embedded within larger healthcare software platforms, electronic health records or specialized disease-management systems. As a result, venture funding for these functions may appear under other company categories.

We haven't found enough independent financing activity to call these categories established standalone funding markets.

Are clinical decision support startups mostly stuck between Seed and Series C?

Clinical decision support has plenty of Seed funding, but the financing ladder narrows sharply before Series C, where only ten transactions were recorded.

Among 107 transactions with a classified stage, 46 were Seed rounds and 23 were Series A. These 69 early-stage financings represented 64.5% of classified deals.

Their combined capital, however, was approximately $549.8 million. The 38 classified Series B and later-stage transactions, including growth equity, attracted approximately $2.224 billion.

Round sizes rise sharply as companies mature. The median Seed financing was $2.14 million, increasing to $12.7 million at Series A and $20.2 million at Series B.

By Series C, the median reached $42.5 million. At Series D+, it was $87.5 million.

The first big contraction appears between Seed and Series A, where deal count halves. There is another noticeable decline between Series B, with 18 transactions, and Series C, with ten.

One reason the transition can be difficult is that clinical AI products often face a longer path from technical development to routine medical use than ordinary enterprise software.

A model can perform well in controlled testing without immediately becoming something hospitals are ready to purchase and deploy. Companies may need additional clinical evidence, regulatory clearance, compatibility with hospital systems and proof that doctors will actually use the product.

The FDA's updated clinical decision support guidance, reissued in January 2026, illustrates one of these challenges. Certain software functions can fall outside medical-device regulation, but others remain regulated, including functions that analyze medical images or particular medical signals.

We can see similar practical priorities in funding announcements. Cleerly raised money for clinical evidence generation and commercial expansion, while Acurion identified validation and regulatory preparation as important next steps.

These examples help explain why moving up the financing ladder can be difficult, although they don't prove why any particular company failed to raise a Series C. The Seed and Series C transactions also involve different company populations, so comparing their counts does not establish startup survival rates.

Twenty-eight transactions could not be assigned a reliable stage. We have kept them separate rather than forcing them into the financing ladder based on their size.

Stage	Deals	Capital	Median round
Seed	46	$156.8M	$2.14M
Series A	23	$393.0M	$12.70M
Series B	18	$636.4M	$20.20M
Series C	10	$619.5M	$42.50M
Series D+	6	$643.4M	$87.50M
Growth Equity	4	$324.3M	$31.35M
Unknown	28	$222.6M	$4.58M

How old are clinical decision support startups when they raise big rounds?

Clinical decision support companies raising more than $50 million are typically around seven years old, suggesting that serious expansion financing often comes after several years of development.

Across the full dataset, the median age at financing is five years. Companies receiving rounds below $5 million have a median age of four years, while those raising above $50 million have a median age of seven.

The age difference becomes clearer at successive funding stages. Seed-funded companies have a median age of three years, compared with six years at Series A, seven at Series B and eight at Series C.

Even the market's founding-year distribution reflects this pattern. The largest funded founding cohort dates back to 2018, several years before the financing window began.

For example, Qure.ai was founded in 2016 and completed its $65 million Series D in 2024. Aidoc was also founded in 2016 and raised its two large recorded financings in 2025 and 2026.

Their histories help explain why large clinical AI rounds often go to businesses that have already spent years building products, securing clearances and expanding into healthcare organizations.

This doesn't mean every clinical AI company needs seven years to attract serious funding. OpenEvidence demonstrates that some platforms can raise extremely large amounts much sooner.

But for investors and founders assessing the broader market, a multi-year development cycle is a more realistic benchmark than the exceptionally rapid financing history of its most prominent company.

Is clinical decision support funding growing steadily, or coming in occasional huge rounds?

Clinical decision support funding has been uneven, with occasional enormous transactions creating spikes in capital even when the number of deals remains fairly ordinary.

Across the 32 completed calendar months from January 2024 through August 2026, we counted an average of 4.09 deals per month.

The median completed month recorded approximately $43.24 million of funding. The largest month, July 2025, reached $388.4 million, almost nine times that amount.

That month included a $210 million financing, representing more than half of the capital raised.

October 2025 provides an even more striking case. A single $200 million transaction accounted for almost all the $210.6 million raised during the month.

January 2026 also recorded a major concentration, with one $250 million round inside a total of $352.2 million.

Interestingly, the busiest month by number of transactions was November 2025, with nine deals, rather than one of those exceptionally large funding months.

The monthly figures show fairly regular smaller-round activity, interrupted by huge financings to a few companies. Those capital spikes tell us little about whether fundraising became easier for the typical startup.

Is Europe actually ahead of the US in clinical decision support startups?

Europe has more funded clinical decision support companies than North America, but North America receives almost four times as much capital.

We identified 60 funded European companies across 65 transactions. North America had 41 companies and 51 deals.

Despite that smaller number, North American companies attracted $2.129 billion, or 71.1% of the market's recorded funding. Europe received $538.6 million.

The difference also appears in typical financing amounts. The median North American round was $13 million, compared with $4.29 million in Europe.

The United States accounted for 48 deals and approximately $2.107 billion. Within Europe, the United Kingdom recorded 20 deals worth $171.6 million, while France attracted $189.3 million across 13 deals.

OpenEvidence contributes substantially to this gap. Removing its $985 million would reduce North American funding by almost half, although North America would remain the largest region by capital.

Asia-Pacific has a similar concentration issue on a smaller scale. Its $303.7 million of funding includes Harrison.ai's $112 million financing, which accounts for 36.9% of the regional total.

Region	Deals	Companies	Capital raised	Median round
North America	51	41	$2,128.7M	$13.00M
Europe	65	60	$538.6M	$4.29M
Asia-Pacific	14	12	$303.7M	$12.55M
Middle East	5	5	$24.8M	$3.00M

Which investors are backing clinical decision support startups again and again?

Clinical decision support has a fairly fragmented investor base, with only fourteen named lead investors appearing in more than one financing transaction.

We identified 141 distinct named lead or co-lead investors. Khosla Ventures, Parkwalk Advisors and LUMO Labs were the most frequent, each appearing in three transactions.

Their financing activity is quite different. Khosla Ventures has backed diagnostic and risk prediction businesses, while Parkwalk has participated in diagnostic and care pathway companies. LUMO Labs appears repeatedly in smaller financings.

By contrast, some of the largest investors show up less frequently but are associated with much bigger rounds.

GV appears in two transactions with combined round sizes of $410 million. Andreessen Horowitz is associated with two rounds totaling $272 million, while Goldman Sachs Alternatives' growth equity business appears in two worth $205 million.

These totals describe the entire rounds led or co-led by the investors, rather than the amounts they personally contributed.

Some firms repeatedly finance emerging clinical technologies with modest checks. Others appear mainly when an established company is raising tens or hundreds of millions of dollars.

Are hospitals and big healthcare companies investing in clinical AI themselves?

Hospitals, healthcare companies and other strategic investors already participate in clinical AI financing, especially when a company is raising larger amounts.

We identified named strategic participation in 30 deals, representing 22.2% of all recorded transactions.

Those financings had a median size of $16.1 million, compared with $5 million for rounds without named strategic investors.

Aidoc's July 2025 financing is a particularly clear example. Alongside General Catalyst and Square Peg, investors included NVentures and four US healthcare systems: Hartford HealthCare, Mercy, Sutter Health and WellSpan Health.

The involvement of hospital operators is commercially relevant. Healthcare systems can potentially support deployment, provide clinical feedback and help companies understand the practical requirements of integrating software into care delivery.

Other strategic investors bring different advantages. Qure.ai's September 2024 Series D included Merck Global Health Innovation Fund, while Elucid's September 2026 $55 million Series D announcement highlighted participation from a major medical technology company, described as its fourth publicly traded strategic investor.

According to Elucid, that capital will support commercial expansion, product development and further clinical studies.

Strategic participation appears most often in diagnostic decision support, where we recorded 17 deals involving named strategic investors.

There is a limitation worth keeping in mind: the database tracks disclosed equity participation, so commercial partnerships without investment are not necessarily captured.

And although strategic-backed rounds are typically larger, we cannot conclude that strategic investors cause companies to raise more. Established businesses may simply be more attractive to both strategic and financial backers.

Still, the role of healthcare organizations in funding is already meaningful, particularly for businesses developing products that need to be deployed within complex clinical environments.

What's the biggest problem with clinical decision support funding right now?

The biggest weakness in clinical decision support funding is the small number of companies reaching substantial, repeated expansion financing.

The sector has no apparent shortage of initial investment activity. We identified 31 financings labelled as first rounds, 46 classified Seed transactions and a wide range of funded businesses across diagnostics, risk prediction and precision medicine.

The difficulty becomes more visible higher up the financing ladder.

Only eleven companies raised more than $50 million cumulatively during the period. Very few completed multiple qualifying transactions, and late-stage financings were considerably less common than Seed rounds.

Several categories also have limited independent financing activity. Medication decision support and care pathway support, for example, have only five and three recorded transactions respectively.

In practical terms, we have evidence that investors are willing to finance many new clinical AI products. There is much less evidence of a broad population of businesses repeatedly raising the large amounts associated with national or international commercial expansion.

That doesn't establish how many companies are profitable, have been acquired or can operate successfully without further fundraising.

What the data does show is a funding market where major financial resources are concentrated among a small group of companies that investors are willing to support at scale.

What should we actually take away from the funding data?

Clinical decision support is a sizeable funding market, but access to large amounts of capital remains limited to a relatively small group of companies. After reviewing the financings, several conclusions stand out.

The typical company raises much less than the headline figures suggest. Smaller rounds dominate transaction volume, while a few nine-figure financings account for a substantial part of total funding. For most founders, single-digit-million-dollar rounds are a more useful reference point than the market average.

Diagnostic decision support has the broadest investor backing. Its funding covers dozens of independent businesses developing medical imaging and diagnostic applications. Evidence and guideline support has attracted extraordinary capital, but that category's funding depends overwhelmingly on OpenEvidence.

Large investments usually go to companies with established financing histories. The median age of businesses raising more than $50 million is seven years, and follow-on rounds absorb the overwhelming majority of capital. Clinical AI investors appear comfortable financing long development cycles when companies demonstrate enough progress to justify further investment.

Europe supports more funded companies, while North America attracts much bigger checks. The difference is reinforced by the presence of several exceptionally well-funded American businesses.

Strategic investors are already part of the market. Hospitals, healthcare groups, technology suppliers and medical technology companies participate in a meaningful share of financings, particularly at more advanced stages.

The upper financing ladder remains narrow. Early-stage capital reaches a substantial number of companies, but relatively few recorded transactions involve the large amounts associated with commercial-scale expansion.

Overall, clinical decision support has a wide range of emerging businesses developing specialized tools, and a much smaller group of companies building platforms intended for broad clinical deployment.

For now, that smaller group commands most of the money.