Care services encompass:
– Tech-enabled care providers (virtual or hybrid models not previously possible).
– Tech products sold to existing care providers (like hospitals) to enhance their operations.
– Health data tools — products that process, aggregate, or anonymize healthcare data for privacy and improved interoperability.
Zanchi notes that the most concerning hype examples are in the first category, where companies claim to use AI for diagnostic or therapeutic purposes.
“That’s very close to the point of care, introducing real risks if the tech isn’t robust.”
Creating solutions in search of problems instead of understanding real value
Zanchi identifies an issue where companies build AI models that create solutions in search of problems. Instead of addressing a healthcare need and finding the best solution, they push AI into spaces where it might not fit. Healthcare is complex, requiring products appealing to patients, doctors, nurses, administrators, insurers, and regulators. Understanding the value proposition for each group is crucial.
“We often reach conviction — or decide to pass — before we open the tech’s black box. If it turns out to be AI under the hood, great. But we’re seeking the best product, not the flashiest tool,” she shared.
Nina Capital backs diverse founders creating tech for real healthcare problems
Zanchi cites diversity as key to a good startup.
“At Nina Capital, we have 12 nationalities among 10 people with backgrounds in engineering, neuroscience, pharma, medtech, regulatory, and SaaS. We seek the same diversity in founding teams.”
Though early-stage teams can’t have everything in-house, an ideal founder triangle includes someone with clinical context understanding, technical expertise, and business or market knowledge. Zanchi suggests healthcare insight can come from personal or family medical experiences driving product development.
“That kind of commitment can drive real innovation.”
Examples of investment include:
– Noah Labs: Digital health startup developing Ark, an AI-powered telemonitoring platform using smart biosensors, machine learning, and a mobile app to predict heart failure decompensation up to 14 days earlier, reducing hospitalizations.
– CryoCloud: Cloud-native SaaS platform automating cryo‑electron microscopy (cryo‑EM) data analysis with machine learning, expediting 3D protein structure visualization for drug discovery.
– LillianCare: Hybrid general practice clinics where nurses handle 60% of outpatient treatment under doctors’ remote tele‑supervision, supported by a digital platform and insurer and municipal partnerships.
“Growth alone won’t save you.”
Zanchi compares AI to the dot-com bubble, suggesting it will follow a similar trajectory.
“It’s here to stay and will become foundational. But we need to be cautious.”
She identifies two recurring issues in hype cycles: jumping into tech without defining the problem, and prioritizing growth over profitability.
“The best companies can grow quickly when rewarded by the market or shift to profitability when necessary. Others suffer from recent excesses,” Zanchi said.
In healthtech, with its long procurement cycles, Zanchi asserts that understanding financial incentives for adoption is key. Successful portfolio founders know how patients and money flow through the system, behavioral changes needed, and barriers to overcome.
“They’ve been able to pivot when hitting a dead end with a stakeholder group, adjusting their positioning. They reconfigure the product to fit healthcare workflows better and redistribute value for all stakeholders.”
“It’s about solving the problem, not just promising ‘AI.’ Address tough questions: How will this affect patient outcomes? What do regulators think? Will administrators adopt it? Can it be reimbursed? Is privacy protected? When you confidently answer these, the tool’s nature — traditional software or deep learning — doesn’t matter.”
Successful startups recognize expertise gaps, bringing in advisors or experts. They innovate with the system, not against it.
Startups overlook unexciting but impactful problems at their peril
Some impactful problems are often overlooked due to their lack of excitement. Zanchi cites an executive at a large US primary care group who struggles with vendor management.
“He’s trying to track tech spend, measure impact, identify redundancies across departments — with spreadsheets. There’s inefficiency. Addressing it would significantly impact financial and operational aspects, benefiting patients.”
Founders may overlook how healthcare reimbursement and incentive models differ between countries:
“Germany, France, the US are all different, and these incentives can change rapidly. Founders need to be attuned to these changes, which can be game-changing when effective. Successful hospital relationships can last years.”
Lead image: Nina Capital.