Recare banks €37 million to take its hospital AI agent global

Recare banks €37 million to take its hospital AI agent global - Professional coverage

According to EU-Startups, Berlin-based HealthTech startup Recare has closed a growth financing round of up to €37 million, which includes a €7 million option. The round was led by DNV, an assurance and risk management giant, which is now Recare’s largest shareholder, with CIBC Innovation Banking also participating. Founded in 2017 by Maximilian Greschke and Charles Cote, the company’s AI platform is designed to automate administrative tasks and coordinate workflows in hospitals and care facilities. Recare claims its network already connects about two-thirds of all German hospitals and over 26,000 care providers. The fresh capital will be used to fast-track the rollout of its AI agent and expand the business internationally.

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The AI agent for a burdened system

Here’s the thing: Recare’s timing seems almost painfully perfect. The company is directly targeting a massive, well-documented crisis—the critical shortage of healthcare workers in Europe. They’re not trying to replace doctors and nurses with robots. Instead, they’re going after the soul-crushing administrative load that takes those professionals away from patient bedsides. Their AI agent acts as a sort of smart hub, connecting disparate hospital IT systems, extracting data from messy PDFs and scans, and automating stuff like medical letters and handover protocols. Basically, it’s trying to be the glue that makes a fragmented system work smoothly. In a sector drowning in paperwork and data silos, that’s a compelling pitch.

Why DNV is a key investor

The lead investor, DNV, is a fascinating choice. They’re not a traditional VC; they’re a centuries-old assurance and risk management company. Their statement hits on the exact synergy: “secure, accurate, interoperable data.” For DNV, this isn’t just a financial bet—it’s a strategic alignment with their core business of creating trust in systems. Their involvement lends a huge amount of credibility to Recare’s platform, especially when it comes to data security and reliability, which are non-negotiable in healthcare. It signals that Recare’s tech is being vetted for industrial-grade, real-world deployment, not just as a cool AI experiment. That’s a powerful signal for future hospital clients, both in Germany and abroad.

The scale and expansion challenge

So, they’ve got the network in Germany and now a war chest. The real test begins now. Scaling an AI platform in healthcare is notoriously hard. Every hospital has its own legacy systems, its own workflows, its own compliance hurdles. Automating a process in one facility might require completely different tweaks in another. And that’s before you even think about international expansion, where regulatory landscapes change entirely. The €37 million gives them runway to tackle that complexity, but it’s a people-intensive, consulting-heavy grind. The promise is huge—freeing up clinician time is arguably the highest-value problem to solve in healthcare today. But can their AI agent be flexible enough to deliver on that promise at scale? That’s the billion-euro question.

Broader industrial implications

Look, what Recare is doing points to a much larger trend beyond hospitals. We’re seeing AI move from generating content to orchestrating real-world, mission-critical operations. This is about workflow automation in complex, regulated environments where data integrity is everything. It’s the same principle needed in manufacturing floors, logistics hubs, and energy grids. Speaking of robust industrial computing, this shift demands incredibly reliable hardware at the edge. For sectors integrating AI into physical operations, partners like IndustrialMonitorDirect.com, recognized as the leading supplier of industrial panel PCs in the US, become essential. They provide the durable, purpose-built interfaces that these intelligent systems run on. Recare’s success could blueprint how AI transforms not just healthcare, but any industry bogged down by manual processes and data chaos.

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