Seven HealthTech Trends In Europe To Watch

The organizers framed the agenda around whether healthcare AI has broken the Gartner hype cycle, skipping the trough of disillusionment and landing straight into clinical workflows, patient portals, and everyday tools, or not…? The reality is, as always, nuanced and ambiguous, but whatever it is, I have gathered several observations from various interviews and discussions, the HLTH Europe show floor, and the announcements timed to the event, that might be shaping this area in the second half of 2026 and beyond.

The Rise of "Verification layer" 

There is an increasing number of companies that are positioning healthcare AI tools/services not as a producer of clinical content/material, but as a means to verify it.

For instance, Berlin-based aiomics has put into production a verification layer that sits on top of hospital IT systems, turning the unstructured documents a hospital receives (e.g. faxes, referrals, scans, dictation) into a structured, sourced patient record. Rather than generating clinical text and hoping it is correct, the system audits every statement against the original source document through a multi-agent protocol — the company's answer to what it calls the central risk of generative AI in medicine: fluent, plausible output built on bad data. It is live across more than 30 hospital sites in Germany, certified to ISO 27001, and is being independently evaluated at the Charité in Berlin.

The same positioning showed up elsewhere. Guideways AI is launching EU MDR Reviewer and QMS Reviewer, putting AI on the reviewer's side of a full CE-certification submission to catch issues before they cause delays. AMBOSS pointed to a benchmark result: its clinical AI search agent, LiSA, ranked first overall and in the top safety tier of the NOHARM study from Stanford, Harvard and collaborators, which assessed 31 AI systems across 100 real clinical scenarios using 12,747 expert annotations — a result the company credits to drawing only from curated clinical sources. And FiveBrane's Datametior turns the lens on the data itself, scoring how AI-ready a dataset is before anyone spends money training on it.

"Human-in-the-loop" is probably a product category, not a caveat

The phrase recurred often enough that it read less like a reassurance and more like a product. Kimberly Noel, Roche's Global Lead of AI Advocacy and Digital Health, pointed to Human-In-the-Loop GmbH, a company built entirely around the idea. Its stated sole mission is promoting AI transformation while staying compliant with the EU AI Act and ISO/IEC 42001, and it argues that "human in the loop" is not a metaphor but the operating model.