The impossible, itemized.

“We have half a century of cardiovascular data scattered across 49 systems, paper archives, and legacy registries. It’s the richest collection in Europe, but it’s unusable. Researchers spend months preparing data that should take minutes.”

A unified research data platform with version-controlled pipelines, automated reporting, and AI-driven analytics. Decades of fragmented records were harmonized into a single, compliant infrastructure where researchers query instead of collate. Each data refresh preserves historical provenance while enabling live multi-project analysis.

Heterogeneous decades-old data, strict GDPR/consent frameworks, and the need to preserve historical integrity while enabling live research. Cleaning 50 years of drift without losing provenance required rigorous version control, clinician-aligned governance, and an architecture that could scale to multinational collaboration.

Annual research reporting that once consumed three months of manual effort now runs in twenty minutes. DanHeart now powers hundreds of concurrent studies and is scaling across Europe.

“Every vendor is pitching foundation models and agentic workflows. We have the medical expertise, but we don’t know what’s actually production-ready versus marketing. We need a grounded path forward, not more demos.”

An executive AI advisory framework that mapped technical maturity to business value. We translated architectures into decision matrices, evaluated build-vs-buy trade-offs, and established governance guardrails before a single model was deployed. Leadership got a prioritized roadmap, not a feature list.

Separating genuine capability from enterprise-ready solutions in a rapidly shifting landscape. Leadership needed technical translation that respected regulatory constraints, data sovereignty, and long-term scalability. The gap between marketing demos and production architecture is where most AI programs stall.

Leadership moved from vendor-led uncertainty to a business-first AI strategy. The framework is now the standard lens for evaluating every major AI initiative across the organization.

“Our scientists spend months manually synthesizing evidence across millions of publications and internal datasets. Our internal team spent 18 months trying to build a solution. We need something that works with how researchers actually think.”

A bespoke AI research platform that automates evidence discovery, structures complex scientific data, and delivers human-readable insights. The system integrates directly into R&D workflows, turning weeks of manual synthesis into minutes of targeted review. Every output carries a traceable evidence chain.

Scientific evidence isn’t structured like a database. Extracting actionable insights from heterogeneous literature, internal datasets, and unstructured notes required domain-tuned retrieval, strict citation grounding, and a workflow that respected scientific rigor. Generic AI tools hallucinate or flatten nuance; researchers need precision.

A pilot that compressed hundreds of person-hours into a single afternoon. Leadership now sees bespoke AI as a multiplier for scientific productivity, not a replacement for expertise.

“We’re studying whether exercise improves outcomes for children on chemotherapy. But if the platform is hard to use, families won’t engage. We need something secure, compliant, and intuitive enough for a three-year-old to follow—without burdening exhausted caregivers.”

A patient-centered digital therapeutics platform with AI-assisted exercise animations, secure family authentication, and research-grade behavioral analytics. Every interaction is tracked for clinical insight, while the interface remains effortlessly simple. Caregivers log in once; researchers gain longitudinal engagement data.

Balancing clinical-grade security and analytics with extreme usability for children and stressed caregivers. Commercial video platforms lack research tracking; custom builds often sacrifice simplicity. We had to make advanced compliance invisible to the user while preserving audit-ready behavioral data.

A platform that tracks clinical-grade data while feeling like a simple video app for families. Now expanding to routine pediatric oncology care pathways.

Clinical research platforms carry an authentication problem nobody designs for. Participants include children, older adults and whole families — people for whom a username, a password, an e-mail verification and a two-factor prompt are each a reason to give up. Family studies need several caregivers on one patient account while keeping participating families completely separate from one another. Every extra step costs engagement and arrives later as a support request.

A bespoke authentication system built around a physical object instead of a memory. Each participant receives a personalised 3D-printed keychain holding a securely encoded chip bound to their own account, and authenticating is a tap against a smartphone. Every caregiver carries their own keychain, and those keychains share access to the right family account — no password to remember, no e-mail round-trip, no reset flow.

The system had to be trivial for a child or an eighty-year-old and still satisfy healthcare-grade access control and GDPR. Shared family access is the difficult part: several caregivers on one account, individual permissions, and hard isolation between families — all of it administrable across a study that runs for years, and none of it allowed to depend on a participant's e-mail address.

The same authentication architecture is already running on further clinical research platforms, including studies with adolescents and young adults. Its modular design lets an organisation deploy participant-friendly authentication across a whole research programme rather than one study at a time.

Videx holds a market-leading position in access control across eight European countries, and wanted to move beyond door entry altogether — a new generation of connected devices handling access, communication, security and building monitoring from one platform. That is not software added to existing hardware. It meant an entirely new technology foundation: facial recognition, intelligent authentication, mobile connectivity, IoT sensing for leaks and temperature, long-range communication through reinforced concrete, and enterprise-grade security, all built to expand across a whole ecosystem of devices.

Viceron designed and developed the complete technology foundation for the platform — embedded systems, cloud infrastructure, AI and the software around them — working alongside Videx's CEO, COO, CTO and senior engineering teams. Rather than modernising existing hardware, it was designed from the ground up to carry future products across residential, commercial and enterprise environments.

The work spanned hardware, embedded software, cloud infrastructure, AI, cybersecurity and mobile applications — disciplines that usually sit in separate organisations, here having to agree on one architecture. Devices must run AI locally, survive real buildings where radio has to cross reinforced concrete, and accept secure firmware updates years after installation.

Following successful pilot deployments, the platform is expected to become the foundation for a significant portion of Videx's future product portfolio, with a scalable architecture built to expand across international markets.