The following is a guest article by Andreas Cleve, Co-Founder and CEO at Corti
Nordic-Style Modularity is Rebuilding Healthcare AI with Shared, Trusted Building Blocks; This Foundation Accelerates Deployment and Strengthens Care at Scale
In Denmark, we grow up with a simple lesson: systems matter.
It’s why our turbines tolerate winter storms, why our insulin pens deliver such quiet precision, and why small plastic bricks still snap together flawlessly six decades on. Danish engineering has long favored modularity – designing parts that interlock cleanly, so the next layer becomes easier, not harder, to build.
That same mindset is reshaping how we think about healthcare AI.
Unblocking the Problem
Healthcare faces a structural challenge: demand for care is outpacing the supply of trained clinicians. The world is aging, chronic disease is rising, and every system is struggling to staff adequately.
AI is often presented as the solution. Yet those building AI for healthcare encounter the same obstacle: the infrastructure required to use it safely is far harder than the AI itself.
Clinical data is scattered across formats and systems. Regulations are essential but heavy. And general-purpose AI still fails to grasp the nuance of clinical language and reasoning. Too often, teams spend months constructing the regulatory scaffolding and clinical context that should already exist before they can even begin solving the actual problem at hand.
This bottleneck slows innovation in an industry that simply cannot afford delay.
The Modular Approach
What healthcare needs is not more standalone AI tools, but a foundation – a set of reliable building blocks that let teams construct applications without reinventing the entire technical and regulatory stack each time.
Imagine the healthcare AI ecosystem built more like a LEGO set: speech recognition that truly understands clinical dialogue; models trained for medical reasoning; privacy, governance, and compliance handled at the core; deployment options that meet stringent local requirements. A system where these components connect through interoperable standards, allowing builders to combine them however a particular workflow or clinical setting demands.
Such modularity would let teams focus on their specific use case – whether that’s documentation, specialty-specific decision support, or operational efficiency – instead of rebuilding the same foundations repeatedly. And as more applications are deployed, the underlying platform becomes stronger, safer, and more efficient for the next wave of builders.
This is how infrastructure compounds: not by chasing novelty, but by refining the parts so others can assemble them into something new.
Making the Possible Practical
The shift underway in healthcare AI is a move from hand-tooled pilots to composable systems that can be deployed broadly and safely. Today, it’s not unusual for an AI healthcare application to take a year or more to reach production. A modular foundation can compress that timeline dramatically – not by cutting corners, but by eliminating redundant work.
Speed matters because delays don’t just stall innovation; they ultimately affect patients. When clinicians have access to tools that are trustworthy, contextually intelligent, and able to scale across diverse patient populations, infrastructure becomes something closer to a public-health intervention than a technical convenience.
Europe’s Industrial Advantage
Europe has a long tradition of building regulated, precision infrastructure – from energy grids to medical devices – that other industries rely on. In Europe, regulation is sometimes framed as a barrier to innovation, but it can also form an advantage: a shared language for safety, trust, and interoperability.
In healthcare AI, that foundation matters. Systems built to meet Europe’s highest standards naturally extend well to other regions, proving that safety and scalability don’t have to be opposing forces.
Building Forward
AI will not replace clinicians. But strong infrastructure can extend their reach – the way great design tools expand what’s possible for architects or engineers. It can help close the widening gap between the care people need and the capacity health systems can provide.
The next generation of healthcare innovation won’t be defined by who builds the flashiest application or the largest model. It will be shaped by those who invest in the underlying systems: dependable, interoperable, thoughtfully engineered building blocks that unlock a thousand different possibilities.
For Denmark – and for Europe – this isn’t a new idea. It’s a continuation of a tradition: solving complex problems by designing systems that work beautifully together.
Andreas Cleve is Corti’s Co-Founder and CEO. After spending nearly a decade working as a multi-entrepreneur in AI, Andreas founded Corti with Lars Maaløe, pioneering a safe and effective Generative AI platform for healthcare. Corti’s AI not only takes notes but also quality assures, journals, codes, nudges, prompts, and documents every patient interaction. With significant research findings in speech processing, dialectic challenges, medical coding, and language understanding, Corti’s artificial intelligence enhances real-time consultations across the entire patient journey across the United States and Europe.
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