Investors say positioning and distribution will determine the winning medical AI startup.
Healthcare AI startups continue to enjoy strong investor interests while gaining more adoptions in providers, payers and pharmaceutical companies.
In the first half of this year, about 58% of all healthcare fundraising transactions involved AI companies, a record pace. According to recent data, at least 10 healthcare AI startups have reached valuations of more than $1 billion in the past year, and at least $500 million in healthcare AI exits in 2025, according to recent data.
As AI companies compete for a flood of concern in the healthcare field, both investors and customers must distinguish which tool offers value vs. more tools than helping the hype.
Morgan Cheatham, healthcare and life science partner and head of Breyer Capital, noted that the difference between AI-First and AI-Spable reveals the focus of the company, and strategies naturally flow from it.
“AI-First advances computing science, and companies that support AI do well in implementation and distribution. In fact, it's not a binary, but more spectrum, and most lasting companies incorporate elements of both.”
However, this framework alone does not determine the lifespan of a company.
Cheatham believes that the last time will be those with strong positioning and distribution – companies that control key leverage points such as AI compounds, data sources, workflows, workflow streams and put together. He believes this will create value that is difficult for existing people to provide.
He highlighted Artera, an AI-powered oncology diagnostic startup, which is one of Breyer's portfolio companies. Cheatham said the startup operates at the moment when data is first created and undergoes critical transformations – turning human tissue into structured clinically available insights.
“Control this conversion point can be a leverage of arterial building. Once the raw data is converted into clinically viable information, every downstream workflow from diagnosis to treatment planning to reimbursement is affected,” he explained.
Cheatham added that it is also important to remember that for incumbents such as Epic and others like Doximity and R1 RCM entering healthcare AI arenas, it is difficult for emerging startups to compete in breadth.
For him, their edge is taking up positions that the incumbents are too slow to reach and finding ways to allocate existing businesses to easily replicate.
Cheatham notes that OpenIfdence, an AI-driven clinical decision support platform, “proves the power of agile distribution” by delivering its products directly to clinicians, gaining trust at the point of care and bypassing the enterprise procurement process.
He also praised Iterative Health as an AI startup that provides tools for gastrointestinal care to demonstrate how smart business models can pair advanced computer vision with clinical trial recruitment, benefiting both medical practice and trial sponsors. He also points to clinical evidence company Atropos Health, which demonstrates how a platform serves providers and pharmaceutical companies by generating real-world clinical evidence that everyone can use.
“In crowded verticals, data and trust, it’s faster in an aggregation platform than in a fragmented point solution, which is why the default result is why mergers rather than crashes. The convergence of technological advantages and economic alignment is exactly what startups can distinguish,” Cheatham announced. ”
He added that artificial intelligence generates richness, not scarcity.
Cheatham explains that when various companies chase the same verticals and run on similar models, differentiation eventually erodes and the market tends to scale.
“The exaggerated category marks where the market demand is clearest and the entry point is most valuable. Even in the competitive landscape, this is the main real estate – the workflow that everyone is struggling to have is the most important.”
Margin pressure is always more severe in healthcare, so buyers won’t really tolerate dozens of similar suppliers. Instead, spending will focus on platforms that have key entry points and create value among different stakeholders, Cheatham said.
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