At a time when investors are falling over themselves to invest in AI, Marta Gaia Zanchi, Founding Partner at Nina Capital, takes a critical approach.
She contends, “We’re not anti-AI. We’ve backed many AI-based companies. We just care about whether it’s the right solution for the problem. That's what matters most.”
Nina Capital is a Barcelona-based healthcare technology-focused investment firm founded in 2019, making on average ten investments per year in Pre-seed and Seed startups. The Firm announced the first close of its €50M Fund III in February this year.
The AI flood: “Half the companies that pitch us say they use AI”
According to Zanchi, the ubiquity of AI in the startup ecosystem is hard to ignore.
“The bulk of emails we get are either written by AI or about an AI-based company. In preparing for this call, I looked at our database — we've screened around 9,500 healthcare tech companies since we started in 2019.
We’ve built internal tools, some of which are ironically using AI, to query that data. What we’ve seen is that nearly half — about 4,000 or so — of those companies claim that AI is a major component of their product. So we’re definitely somewhere near the peak of a bubble when it comes to AI, even if it's not quite the top yet.”
She believes that many companies overstate their AI impact, noting,
“Often what they’re describing as AI is just standard software — explicit, scenario-specific logic. Old-fashioned code, basically.
It feels like they’re catering to investor appetite for AI, rather than honestly describing the tech. And I would actually place some of the blame on our own asset class — for fueling that bubble by rewarding the AI label more than the underlying value.”
Many founders inflate their use of AI — and investors aren’t helping. Zanchi believes startups are misled about how investors perceive AI: “We’re not excited by the word 'AI.’
We’re excited by founders who truly understand the healthcare landscape and can speak to the perspectives of all its stakeholders. If they can show us why their solution fits and why it’s likely to succeed, that’s what matters.”
Inside Nina Capital’s value-based approach to health innovation
Nina Capital follows a Stanford Biodesign–inspired, need‑driven, value‑based methodology, in which innovation begins by deeply understanding real unmet needs in healthcare, then designing technology and business models to meet them, with rigour. This approach has been shown to de-risk venture creation in health technology since its inception in 2001.
Nina Capital divides healthcare investment into three categories:
- Clinical indications: Software or hardware/software combinations intended for clinical use. These are often regulated medical devices.
- Infrastructure for healthcare businesses: Tech solutions that help pharma, biotech, medical device manufacturers, and pharmacy networks operate more efficiently, improve revenue, cut costs, etc.
- Care services – This includes:
- Tech-enabled care providers (virtual or hybrid care models that weren’t possible before).
- Tech products sold to existing care providers (like hospitals) to help them operate better.
- Health data tools — products that process, aggregate, or anonymise healthcare data to ensure privacy and improve interoperability.
According to Zanchi, when it comes to hype, the most concerning examples tend to be in the first category, where companies are claiming to use AI for diagnostic or therapeutic purposes. >
“That’s very close to the point of care, and it introduces real risks if the tech isn’t robust.”
Creating solutions in search of problems instead of understanding real value
Zanchi also sees another issue. Even among companies that are building AI models, many are creating solutions in search of problems.
Instead of starting with a healthcare need and asking what the best solution is, they’re pushing AI into spaces where it might not be the right fit. Healthcare is complex. Products need to appeal to multiple stakeholders, including patients, doctors, nurses, administrators, insurers, and regulators. anchi contends that the first step is understanding the value proposition for each of those groups. What does this solution offer them? Is there alignment?
“We often reach conviction — or decide to pass — before we even open the black box of the tech. If it turns out to be AI under the hood, great. But we’re looking for the best product to solve the problem, not the flashiest tool,” she shared.
Nina Capital backs diverse founders making tech that solves real healthcare problems
In terms of what makes a good startup to invest in, in a word, diversity.
Zanchi explained:
“At Nina Capital, we’re a mix: 12 nationalities across 10 people, with backgrounds in engineering, neuroscience, pharma, medtech, regulatory, and SaaS. We look for that same diversity in our founding teams.”
While early-stage teams can’t have everything in-house, an ideal starting founder triangle is someone who understands the clinical context, someone who brings technical expertise, and someone who has business or market knowledge. Further, she contends that sometimes healthcare insight comes from lived experience, such as founders who built a product because of a personal or family medical experience.
"That kind of commitment can drive real innovation.”
Examples of investment include:
Noah Labs: A digital health startup that develops Ark, an AI-powered, Class IIa telemonitoring platform combining smart biosensors, machine learning, and a mobile app to detect and predict heart failure decompensation — often up to 14 days before clinical deterioration—for earlier intervention and reduced hospitalisations
CryoCloud: a cloud-native SaaS platform that automates cryo‑electron microscopy (cryo‑EM) data analysis using machine learning, dramatically speeding up 3D protein structure visualisation to accelerate drug discovery.
LillianCare: Establishing hybrid general practice clinics—where nurses handle about 60 per cent of outpatient treatment under remote tele‑supervision by doctors, enabled by an integrated digital platform and partnerships with insurers and municipalities
“Growth alone won’t save you.”
Zanchi views AI with a historical lens.
“Think of the dot-com bubble. The internet didn’t fail — clearly — but there was a moment of overexcitement and overinvestment, and then a collapse."
She believes AI will follow a similar trajectory.
“It’s here to stay and will become a foundational technology. But we do need to be cautious.”
Within this, she points to two recurring issues in these hype cycles: Jumping into tech before defining the problem.
Prioritising growth over profitability.
“The best companies in our portfolio can flex: they can grow quickly when the market rewards it, or shift to profitability when needed. But others are still suffering from the excesses of recent years,” shared Zanchi.
In terms of adoption in healthtech, a sector with rightful caution and long procurement cycles, Zanchi contends that the key to access for startups is understanding the financial incentives that drive adoption and behaviour.
Nina Capital’s most successful portfolio company founders know not only how patients flow through the system, but how money flows. They also understand what behavioural changes are required and what blockers exist.
“They’ve been able to pivot when needed — if they hit a dead end with a stakeholder group, they adjust their positioning. They reconfigure the product to fit the workflows of healthcare providers better and redistribute the value so all stakeholders win.”
“You’re not just promising 'AI,' you’re answering the tough questions: How will this impact patient outcomes? What do regulators think? Will administrators adopt it? Can it be reimbursed? Is privacy protected? When you can confidently answer those questions, then it doesn’t matter what’s in the tech stack—whether it's traditional software or deep learning. It’s about solving the problem."
And they’re humble enough to recognise where their expertise is lacking and bring in advisors or experts to help. The most successful startups innovate with the system, not against it.
Startups ignore the unsexy problems at their peril
In terms of innovation gaps, Zanchi admits that some of the most impactful problems are also the most boring, citing an example of a conversation where an executive at a large US primary care group shared his biggest headache:
“He said: vendor management. He’s trying to track technology spend, measure impact, and identify redundancies across departments — all with spreadsheets.
There’s so much inefficiency there. But because it’s not “exciting” or directly patient-facing, it gets ignored. If you could move the needle on that, it would have a massive financial and operational impact, and ultimately benefit patients, too.”Further, Zanchi contends that many founders overlook how healthcare reimbursement and incentive models vary between countries:
“Germany, France, the US — they're all very different. And those incentives change over time, sometimes rapidly. Founders need to be more attuned to that. When it works, it can be game-changing.
Successful relationships with hospitals can last for years."
Lead image: Nina Capital.
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